Research output

% VERIFIED; verified 2026-10-11
@article{orbit-b7a9b36bff7fbe36,
  title = {A decomposition-based matheuristic for the passenger-oriented integrated passenger-freight transport problem},
  author = {Li, Siqiao and Stokkink, Patrick and Cats, Oded and Saeednia, Mahnam},
  journal = {Transportation Research Part C: Emerging Technologies},
  year = {2027},
  volume = {194},
  part = {Part A},
  pages = {105996},
  eid = {105996},
  doi = {10.1016/j.trc.2026.105996},
  url = {https://doi.org/10.1016/j.trc.2026.105996},
  issn = {0968-090X, 1879-2359},
  publisher = {Elsevier},
  abstract = {Integrating passenger and freight transport has become increasingly important for improving the efficiency of urban mobility systems, as planning them separately often results in underutilized capacity and redundant vehicle movements. Coordinating the two enables more effective use of existing transport resources for public transport operators, helps logistics providers maintain cost-effective and reliable deliveries, and assists public authorities in alleviating urban congestion. When implementing such integration, railway stations play a key role as urban hotspots with limited access, where road-rail connections can facilitate efficient intermodal operations. In this work, we introduce a passenger-oriented pickup and delivery problem with explicit road-rail connections and a fleet of shared-use light vehicles. The problem is formulated as a mixed-integer linear program to jointly determine fleet size, routing, and scheduling plans, ensuring a balanced service quality for both passengers and freight. A decomposition-based matheuristic is developed that iteratively coordinates a routing-oriented master problem and a scheduling-oriented subproblem, with feasibility partially restored through a schedule-shifting strategy. The master problem is tackled using an adaptive large neighborhood search enhanced with variable neighborhood search, featuring a novel adaptive selection mechanism based on the relative contributions of service quality indicators. The resulting routing decisions are then passed to the scheduling subproblem, which is solved efficiently using a propagation-based approach that guarantees local optimality. Extensive sensitivity and benchmark analyses demonstrate the benefits of integrated transport in reducing delays, particularly in resource-constrained settings and across different passenger–freight demand compositions.},
  keywords = {Pickup and delivery problem, Integrated transport, Matheuristic, Adaptive large neighborhood search},
}

% VERIFIED; automatic policy
@article{orbit-auto-b8612ceceddbc9f0,
  title = {Hybrid predictive rebalancing control of perceived usability in shared e-scooter systems},
  author = {Momen, Sara and Maknoon, Yousef and van Arem, Bart and Sharif Azadeh, Shadi},
  journal = {Transportation Research Part C: Emerging Technologies},
  year = {2027},
  volume = {194},
  pages = {106093},
  eid = {106093},
  doi = {10.1016/j.trc.2026.106093},
  url = {https://doi.org/10.1016/j.trc.2026.106093},
}

% VERIFIED; verified 2026-10-11
@article{orbit-5b40dc103a823723,
  title = {Service design for shared micromobility: Long-term planning under gradual user adoption},
  author = {Farhani, Mahsa and Rezaei, Jafar and Azadeh, Shadi Sharif and Maknoon, Yousef},
  journal = {Research in Transportation Business \& Management},
  year = {2026},
  volume = {69},
  pages = {101818},
  eid = {101818},
  doi = {10.1016/j.rtbm.2026.101818},
  url = {https://doi.org/10.1016/j.rtbm.2026.101818},
  issn = {2210-5395, 2210-5409},
  publisher = {Elsevier BV},
  abstract = {Service design for shared micromobility services, such as e-mopeds, involves decisions on service location, fleet size, pricing, and resource allocation, which are typically based on potential demand estimates. In practice, however, potential users adopt the service gradually, leading to market penetration over time. Ignoring this gradual penetration can lead to suboptimal decisions and service failures. We propose a phased optimization model to maximize profitability over a planning horizon divided into discrete periods. The model jointly determines service locations, fleet size, and spatio-temporal resource allocation while ensuring a targeted service level. To model gradual adoption, we apply an extended Bass diffusion framework in which adoption depends on service quality, defined by accessibility and availability, and social influence, reflecting the impact of current users on others’ adoption. The phased deployment strategy aligns service expansion and investment decisions with adoption growth (market penetration) over multiple periods. Applied to a bike-sharing case in Manhattan, the proposed approach improves resource allocation and increases profitability by up to 47\% compared with an upfront strategy under parameter misestimation. Furthermore, ignoring service quality in the adoption model leads to a profit loss of up to 54\% when user expectations are high The results shed light on the value of synchronizing service design decisions with user adoption dynamics.},
  keywords = {Bass diffusion, Phased planning, Service design, Shared micromobility, Social influence},
}

% VERIFIED; verified 2026-10-11
@article{orbit-acfda03c40168bfa,
  title = {Role of topology and recovery strategies on multi-dimensional resilience of road networks},
  author = {Balakrishnan, Srijith and Stokkink, Patrick},
  journal = {International Journal of Disaster Risk Reduction},
  year = {2026},
  volume = {144},
  pages = {106366},
  eid = {106366},
  doi = {10.1016/j.ijdrr.2026.106366},
  url = {https://doi.org/10.1016/j.ijdrr.2026.106366},
  issn = {2212-4209},
  publisher = {Elsevier BV},
  abstract = {This paper examines how road network topology and post-disruption recovery strategies jointly shape recovery processes following disruptions. We develop a scalable stress-testing framework to simulate disruption scenarios and generate recovery data for road networks, which is subsequently analyzed with regression models to identify the effects of structural characteristics, recovery strategy, and disruption severity on multi-dimensional resilience. Using 224 real-world road networks, we assess their post-disruption recovery across five resilience dimensions: operational efficiency, accessibility, local redundancy, global connectivity, and spatial fairness. The results yield three key insights with significant implications on infrastructure design and management. First, road network resilience is fundamentally multidimensional: no single recovery strategy consistently performs best across all dimensions. Second, topological characteristics influence recovery outcomes. Third, strategy-based recovery provides limited benefits under minor disruptions but substantially accelerates recovery under severe damage. These findings highlight the need for policies that integrate robust and diverse network design with post-disaster recovery planning for resilience management.},
  keywords = {Disaster resilience, Disruptions, Restoration, Statistical analysis, Topological metrics, Urban transport planning},
}

% VERIFIED; verified 2026-10-11
@article{orbit-866cac1d1b0899c6,
  title = {A two-stage stochastic programming approach for strategic rolling stock scheduling in passenger railway transport},
  author = {Li, Siqiao and van Lieshout, Rolf and Stokkink, Patrick},
  journal = {Omega},
  year = {2026},
  volume = {144},
  pages = {103593},
  eid = {103593},
  doi = {10.1016/j.omega.2026.103593},
  url = {https://doi.org/10.1016/j.omega.2026.103593},
  issn = {0305-0483, 1873-5274},
  publisher = {Elsevier BV},
  abstract = {Conventional railway planning follows a sequential approach in which rolling stock scheduling is performed only after timetables are constructed, forcing early-stage line-planning decisions to rely on simplified rolling stock cost approximations. The lack of precise cost information hampers line-plan evaluation and limits the design of cost-efficient services. This study considers rolling stock scheduling in a strategic setting, aiming to estimate fleet size and operational costs for a given line plan without solving the timetabling problem. Since predefined train services are unavailable at this level, unlike in tactical planning, we introduce a network representation incorporating shunting movements like coupling and uncoupling. To account for demand uncertainty, a two-stage stochastic programming approach is proposed, in which first-stage decisions determine fleet acquisition and second-stage decisions optimize rolling stock circulation, including shunting, under each demand scenario. Two models are developed, differing in whether the fleet size is estimated using a flow-based or circulation-based approach. The applicability of the proposed models is demonstrated using instances derived from the Dutch Intercity network. Compared to a trip-based benchmark, the circulation-based model yields more accurate cost estimates, while short and simple cycles retain most of its value at much lower computational cost. Moreover, stochastic planning better captures the procurement–service trade-off under demand uncertainty and produces more robust fleet plans than a deterministic approach. Under strong emphasis on investment costs, fleet choices are dominated by flexible, cost-effective unit types. Allowing shunting enables flexible capacity redistribution, reducing fleet requirements and investment costs while maintaining comparable service levels.},
  keywords = {Railway planning, Rolling stock scheduling, Shunting, Uncertain demand, Stochastic programming},
}

% VERIFIED; verified 2026-10-11
@article{orbit-775908644fcf5cd8,
  title = {Time Preference in Decisions With Recurring Payoffs},
  author = {Gülüm, Pelin and Maknoon, Yousef and Montibeller, Gilberto and Rezaei, Jafar},
  journal = {Journal of Behavioral Decision Making},
  year = {2026},
  volume = {39},
  number = {4},
  eid = {e70091},
  doi = {10.1002/bdm.70091},
  url = {https://doi.org/10.1002/bdm.70091},
  issn = {0894-3257, 1099-0771},
  publisher = {Wiley},
  abstract = {ABSTRACT Time preference plays a central role in decision‐making, shaping how individuals value outcomes that occur at different points in time. While most research on time preference focuses on one‐off payoffs, many real‐world decisions generate recurring consequences that unfold continuously over time. Despite their prevalence, little is known about how recurring payoff structures influence intertemporal preferences. We propose that recurring payoffs reduce discounting by promoting temporal integration. By highlighting the continuity of future consequences, recurring payoffs encourage individuals to form a more temporally integrated representation of outcomes rather than evaluating consequences as isolated events. Drawing on the choice isolation argument and the literature on choice bundling and choice bracketing, we argue that this representation reduces the salience of immediate‐versus‐delayed trade‐offs and ultimately lowers discount rates. We test this hypothesis in two experiments involving 284 individuals. Participants completed intertemporal choice tasks in either the gain or loss domain, with choices varying along two additional dimensions: payoff structure (one‐off vs. recurring) and outcome magnitude (small vs. large). Results revealed significantly lower discounting in recurring payoff conditions than in comparable one‐off conditions. The findings are consistent with the proposition that recurring payoff structures encourage a more temporally integrated evaluation of future outcomes, leading individuals to place less weight on immediacy when making intertemporal choices. This study extends the time‐preference literature by introducing recurring payoff structures as a distinct class of intertemporal outcomes and identifying temporal integration as a potential mechanism through which payoff structure influences discounting. It further demonstrates that the magnitude effect extends to recurring payoff environments, suggesting that outcome size continues to shape discounting even when consequences unfold repeatedly over time. These findings suggest that making the recurring nature of future consequences salient may be a promising avenue for promoting more future‐oriented decision‐making.},
  keywords = {discount rate, recurring payoffs, temporal integration, time preference},
}

% VERIFIED; verified 2026-10-11
@article{orbit-6ba9bfc7dcd9b629,
  title = {A synthesis of the European copper supply chain under the Critical Raw Materials Act},
  author = {van Citters, Veerle and van Binsbergen, Arjan and Stokkink, Patrick},
  journal = {Cleaner Logistics and Supply Chain},
  year = {2026},
  volume = {20},
  pages = {100344},
  eid = {100344},
  doi = {10.1016/j.clscn.2026.100344},
  url = {https://doi.org/10.1016/j.clscn.2026.100344},
  issn = {2772-3909},
  publisher = {Elsevier BV},
  abstract = {The European Union’s (EUs) Critical Raw Materials Act (CRMA) aims to strengthen the EUs resource resilience by increasing the autonomy of Critical Raw Material (CRM) supply through EU-based extraction, processing, and recycling, thereby reducing external dependencies and promoting a circular economy. Copper, a key CRM, faces growing demand that cannot be fulfilled by mining alone. This research analyzes the European copper supply chain under the CRMA and evaluates the role of recycling in meeting its requirements. An initial qualitative analysis suggests that recycling is the most promising solution to comply with the CRMA. The study develops a Mixed Integer Linear Programming (MILP) model to optimize the European copper recycling network under the CRMA recycling requirement and to validate the potential of recycling in a quantitative way. Results identify four optimal facility locations spread through Europe based on geographic centrality weighted by supply and demand quantities. Although the collection of European waste can feasibly satisfy the minimum recycling requirements as set out by the CRMA, changing regulations, disruptions, or changes in demand and external supply may lead to shortages. Improving recycling efficiency has therefore been marked as an important direction of future research.},
  keywords = {Copper, Critical Raw Materials Act, Mixed integer linear programming, Recycling network optimization, Sustainability},
}

% VERIFIED; verified 2026-10-11
@article{orbit-9279300322b318ea,
  title = {Redesigning urban intermodal transit for passenger and freight co-modal mobility: Metro line planning with integrated truck routing},
  author = {Lu, Yahan and Peng, Yuwen and Xia, Dongyang and Stokkink, Patrick and Sharif Azadeh, Shadi},
  journal = {Transportation Research Part B: Methodological},
  year = {2026},
  volume = {211},
  pages = {103538},
  eid = {103538},
  doi = {10.1016/j.trb.2026.103538},
  url = {https://doi.org/10.1016/j.trb.2026.103538},
  issn = {0191-2615, 1879-2367},
  publisher = {Elsevier BV},
  abstract = {Urban transportation systems are under increasing pressure to efficiently accommodate both passenger and freight mobility within limited infrastructure and operational budgets. Operators face growing pressure to make more efficient use of existing infrastructure due to economic and environmental constraints. In this regard, we investigate the capacitated line planning problem with integrated truck routing for passenger and freight co-modal mobility in an intermodal network composed of an urban rail transit (URT) system and road-based truck services. Different from existing research that either focuses on passenger-oriented line planning in a single-modal network or optimizes tactical- and operational-level decisions for passenger and freight co-modal mobility based on fixed line plans, we consider a strategic-level problem where urban planners aim to fundamentally re-optimize the allocation of existing infrastructure resources and budget across the intermodal network. We formulate this problem as a path-based mixed-integer linear programming model. The model determines line plans and frequency for both URT and truck services, as well as the passenger and freight routing, with the aim of optimizing the total weighted travel time of passengers and freight. To solve large-scale instances, we develop a column generation algorithm with a two-phase diving procedure. Our algorithm incorporates acceleration techniques and budget reservation strategies derived from the mathematical properties of the formulation. We evaluate our approaches on both artificial instances and real-world case studies from the Rotterdam intermodal network. The results show that our algorithm obtains solutions with an average optimality gap of 0.77\%, while reducing computation time by 95.53\% compared to GUROBI. Using the existing Rotterdam URT line plan with optimized frequencies as a benchmark, we demonstrate that our approach improves service quality by 6.50\% without increasing operational costs. From a practical perspective, real-life case studies suggest that accommodating the passenger and freight co-modal mobility in existing passenger-oriented metro systems requires redesigning the line plan from scratch, rather than merely adjusting frequencies or incrementally expanding the current network. The results further indicate that effective freight integration depends on reallocating budget across modes, with URT serving as the backbone of the intermodal system and truck services providing a complementary function.},
  keywords = {Intermodal transit networks, Line planning, Truck routing, Passenger and freight co-modal, Column generation},
}

% VERIFIED; verified 2026-10-11
@article{orbit-12a1791a0a4fab30,
  title = {A rolling horizon approach for multi-objective optimization of two-way logistics with postponed orders},
  author = {Tran, Phuong Anh Thi and Stokkink, Patrick},
  journal = {Computers \& Industrial Engineering},
  year = {2026},
  volume = {217},
  pages = {112046},
  eid = {112046},
  doi = {10.1016/j.cie.2026.112046},
  url = {https://doi.org/10.1016/j.cie.2026.112046},
  issn = {0360-8352, 1879-0550},
  publisher = {Elsevier},
  abstract = {Last-mile delivery of e-commerce is a complex mix of simultaneous delivery of goods and pickup of returned goods. With return rates being substantial in the e-commerce sector, this problem is highly relevant. To address this challenge, this study formulates a rolling horizon simultaneous pickup and delivery problem with time windows in a two-way logistics system. The proposed approach integrates a multi-objective mixed-integer linear programming model with a rolling-horizon framework, allowing forward deliveries and reverse pickups to be postponed based on different priorities and penalties, while capturing the interdependence between outbound and return flows. Economic efficiency, environmental impact, and social factors are explicitly incorporated into the objective function. For large-scale instances, an adaptive large neighborhood search with simulated annealing metaheuristic is designed and compared against a weighted-sum mixed integer linear program approach. Numerical experiments on Solomon datasets demonstrate that the proposed method efficiently achieves high-quality solutions, reveals trade-offs among sustainability objectives, and shows how coordinating forward and reverse flows can enhance operational adaptability. The results also highlight an unintended outcome of the proposed rolling-horizon planning: generation and propagation of backlog of demand. This highlights the need for adaptive mechanisms that can manage such issues in multi-period planning.},
  keywords = {Last-mile delivery, Multi-objective optimization, Rolling-horizon planning, Two-way logistics},
}

% VERIFIED; verified 2026-10-11
@article{orbit-84189f25b1924300,
  title = {Intertemporal Judgements in Multi‐Attribute Decision‐Making: Biases and Mitigation Ideas},
  author = {Gülüm, Pelin and Maknoon, Yousef and Rezaei, Jafar},
  journal = {Journal of Multi-Criteria Decision Analysis},
  year = {2026},
  volume = {33},
  number = {2},
  eid = {e70035},
  doi = {10.1002/mcda.70035},
  url = {https://doi.org/10.1002/mcda.70035},
  issn = {1057-9214, 1099-1360},
  publisher = {Wiley},
  abstract = {ABSTRACT Intertemporal judgements are susceptible to biases that can distort evaluations and lead to inconsistent choices. While time‐related biases have been studied extensively from a descriptive perspective, little attention has been given to prescriptive approaches and the complex trade‐offs involved in multi‐attribute decision‐making (MADM). This study provides a comprehensive review of the effects of such biases on the MADM process. Drawing on evidence from behavioural economics, psychology, and decision analysis, we identify six time‐related biases and analyse the vulnerabilities they can introduce at each step of the MADM procedure. We also outline preliminary ideas that may help analysts and decision‐makers reduce these biases in the unique context of intertemporal multi‐attribute problems. Our findings highlight the importance of addressing biases from the earliest stages, such as problem structuring, and underscore the need for further empirical research to test and refine these proposed strategies.},
  keywords = {cognitive biases, intertemporal discounting, multi-attribute decision-making, time preference},
}

% VERIFIED; verified 2026-10-11
@article{orbit-a6d0cfb002e9daf2,
  title = {The value of delay compensation in online food delivery: Analysis of willingness to pay and preference heterogeneity},
  author = {Chen, Junlin and Sharif Azadeh, Shadi and Maknoon, Yousef and Jiang, Hai},
  journal = {Research in Transportation Business \& Management},
  year = {2026},
  volume = {67},
  pages = {101710},
  eid = {101710},
  doi = {10.1016/j.rtbm.2026.101710},
  url = {https://doi.org/10.1016/j.rtbm.2026.101710},
  issn = {2210-5395, 2210-5409},
  publisher = {Elsevier BV},
  abstract = {In recent years, it has become the norm for restaurants to offer Online Food Delivery (OFD) services to expand their customer base and improve profitability. Despite efforts to ensure timely deliveries, delays still occur, leading to customer dissatisfaction and even complaints. To address this issue, platforms and restaurants have collaboratively introduced a complimentary service, namely Delay Compensation (DC), where OFD customers can be compensated if their delivery is delayed beyond a certain threshold. However, empirical research regarding heterogeneous customer preferences for DC in OFD and its interaction with other delivery attributes remains limited. To address this gap, we analyze data from a stated preference survey conducted in China using a two-step modeling framework. In the first step, we estimate a Mixed Logit model using the hierarchical Bayes approach; in the second step, we employ a linear regression model to further examine customer heterogeneity. Results show that under a representative scenario (10-minute delay threshold with platform-affiliated riders), customers’ average Willingness To Pay (WTP) for DC is 1.20 Chinese Yuan (CNY). We also find that the WTP for DC varies across types of riders, delay threshold values, usage scenarios, and customer characteristics. For example, we find that the WTP for DC is 0.89 CNY higher when the meal is delivered by riders employed by restaurants rather than those affiliated with OFD platforms, and that the WTP is 19.9\% higher when the order is placed at the workplace rather than at home.},
  keywords = {Delay compensation, Mixed logit model, Online food delivery, Stated preference survey},
}

% VERIFIED; verified 2026-10-11
@article{orbit-836157e89810f796,
  title = {Time's Influence: A Systematic Review of Biases in Intertemporal Decision-Making},
  author = {Gülüm Taş, Pelin and Maknoon, Yousef and Rezaei, Jafar},
  journal = {Annual Review of Psychology},
  year = {2026},
  volume = {77},
  number = {1},
  pages = {223--254},
  doi = {10.1146/annurev-psych-091924-040158},
  url = {https://doi.org/10.1146/annurev-psych-091924-040158},
  issn = {0066-4308, 1545-2085},
  publisher = {Annual Reviews},
  abstract = {Cognitive biases significantly influence decision-making by distorting how individuals perceive and evaluate outcomes over time. This systematic review synthesizes research from various domains, including behavioral economics, psychology, and health, to explore six time-related biases affecting intertemporal judgments and trade-offs. We analyze the underlying mechanisms of each bias, map their interrelationships, and uncover their impacts on both individual choices and societal decisions. Drawing upon empirical evidence, we propose tailored strategies to mitigate the adverse effects of these biases. Our findings contribute to the literature not only by enhancing the understanding of time-related cognitive biases but also by providing practical insights for improving decision-making and policy design aimed at promoting long-term well-being. The review concludes by highlighting critical gaps in the literature and outlining a future research agenda to further investigate and address biases in intertemporal decision-making.},
  keywords = {cognitive biases, intertemporal decision-making, time preference},
}

% VERIFIED; verified 2026-10-11
@article{orbit-0ff17dc05ca7a7fc,
  title = {Trade-offs in multi-channel delivery network design with perishable and non-perishable goods},
  author = {Cao, Luyang and Tavasszy, Lóránt and Stokkink, Patrick},
  journal = {Journal of Supply Chain Management Science},
  year = {2025},
  volume = {6},
  number = {3-4},
  doi = {10.59490/jscms.2025.8229},
  url = {https://doi.org/10.59490/jscms.2025.8229},
  issn = {2451-9901},
  publisher = {TU Delft OPEN Publishing},
  abstract = {This study focuses on optimizing last-mile delivery in e-commerce by balancing cost efficiency and customer preferences, particularly for mixed perishable and non-perishable goods distribution. As online grocery shopping grows, ensuring the timely and efficient delivery of perishable products while maintaining quality remains a critical challenge. The problem is modelled as a variant of the multi-objective Vehicle Routing Problem (VRP), where customer utility and operational costs are incorporated as two objectives. Customer utility is computed with parameters estimated using the Best-Worst Method (BWM). The multi-objective model is solved by linearizing the non-linear objectives and using a weighted sum method. The model evaluates home delivery, attended pickup points, and lockers, revealing that cost-driven strategies shift deliveries toward self-pickup, with perishable items primarily assigned to attended pickup points due to temperature control. The findings provide insights for improving delivery network design, enhancing service quality, and optimizing the distribution of both perishable and non-perishable products.},
  keywords = {Last mile delivery, Perishable goods logistics, Vehicle routing problem, Mixed integer linear programming, Best-World Method},
}

% VERIFIED; verified 2026-10-11
@article{orbit-a204c054b4312934,
  title = {On the optimal micro-hub locations in a multi-modal last-mile delivery system},
  author = {Stokkink, Patrick and Geroliminis, Nikolas},
  journal = {Transportation Research Part E: Logistics and Transportation Review},
  year = {2025},
  volume = {203},
  pages = {104344},
  eid = {104344},
  doi = {10.1016/j.tre.2025.104344},
  url = {https://doi.org/10.1016/j.tre.2025.104344},
  issn = {1366-5545, 1878-5794},
  publisher = {Elsevier BV},
  abstract = {Last-mile delivery is one of the most polluting parts of the supply chain. This is partially caused by increased congestion in urban areas and repetitive stop-and-go traffic. One possible alternative to this is to use micro-mobility to replace large motorized vehicles. However, these vehicles are usually slower and have lower capacity. In this work, we propose a multi-modal logistics system for last-mile delivery that combines the use of trucks, metro and micro-mobility. This innovative type of system uses the metro to distribute the parcels to micro-hubs across the network and uses micro-mobility only for the final part of the parcel's itinerary from the micro-hub to the front door of the customer. We focus on finding the optimal micro-hub locations in such a system. We use a continuum approximation of the operational and tactical decisions which includes routing of the micro-mobility vehicles. The whole problem is then modeled as a Mixed Integer Linear Programming (MILP) model for the strategic decisions regarding the micro-hubs, which include location, capacity, and fleet-assignment decisions. We evaluate the results of a case study of the city of Madrid, which illustrates that a multi-modal last-mile delivery system can significantly improve a traditional last-mile delivery system in terms of operational costs and pollution.},
  keywords = {Continuum approximation, Last-mile delivery, Location problems, Mixed integer linear programming, Multi-modal transportation},
}

% VERIFIED; verified 2026-10-11
@article{orbit-612ca8a1aca33200,
  title = {Optimal matching for ridesharing systems with endogenous and flexible user participation},
  author = {Stokkink, Patrick and Yang, Zhenyu and Geroliminis, Nikolas},
  journal = {Transportation Research Part B: Methodological},
  year = {2025},
  volume = {200},
  pages = {103290},
  eid = {103290},
  doi = {10.1016/j.trb.2025.103290},
  url = {https://doi.org/10.1016/j.trb.2025.103290},
  issn = {0191-2615, 1879-2367},
  publisher = {Elsevier BV},
  abstract = {The performance of ridesharing systems is intricately entwined with user participation. To characterize such interplay, we adopt a repeated multi-player, non-cooperative game approach to model a ridesharing platform and its users’ decision-making. Users reveal to the platform their participation preferences over being only riders, only drivers, flexible users, and opt-out based on the expected utilities of each mode. The platform optimally matches users with different itineraries and participation preferences to maximize social welfare. We analytically establish the existence and uniqueness of equilibria and design an iterative algorithm for the solution, for which convergence is guaranteed under mild conditions. A case study is conducted with real travel demand data in Chicago. The results highlight the effect of users’ flexibility regarding mode preferences on system performance (i.e., the average utility of users and the percentage of successful matches). A sensitivity analysis on the level of subsidy and the distribution of utility between matched riders and drivers shows that uneven distributions of utility may lead to a higher percentage of successful matches. Additional insights are provided on the effect of a user's origin and destination locations on their role choice and likelihood to be matched.},
  keywords = {Linear programming, Mode choice, Random utility model, Repeated multi-player non-cooperative game, Ridesharing},
}

% INCOMPLETE; verified 2026-10-11
@article{orbit-8aca3117095bcafd,
  title = {Integrated mobile inventory and fleet management for an on-demand delivery system},
  author = {Yang, C. and Maknoon, Yousef and Jiang, Hai and Azadeh, Shadi Sharif},
  journal = {Transportation Research Part C: Emerging Technologies},
  year = {2025},
  volume = {179},
  pages = {105264},
  eid = {105264},
  doi = {10.1016/j.trc.2025.105264},
  url = {https://doi.org/10.1016/j.trc.2025.105264},
  issn = {0968-090X, 1879-2359},
  publisher = {Elsevier BV},
  abstract = {This study introduces an optimization framework for deploying Mobile Fleet Inventories (MFIs) to address operational inefficiencies in on-demand delivery systems. Traditionally, these systems rely on stationary facilities to organize operations and manage resources. While stationary facilities provide stability and structured coverage, they are inherently rigid and struggle to adapt to the spatial and temporal fluctuations characteristic of urban service demand. By leveraging urban waterways, MFIs act as dynamic, mobile facilities, enabling real-time resource redistribution and offering greater flexibility to meet evolving demand patterns efficiently. We formulate the problem as a mixed-integer linear programming model to optimize MFI deployment, minimizing total system costs. The model incorporates both capital investments (e.g., MFI leasing and docking infrastructure) and operational expenses (e.g., rider idle time). Key decisions include determining the optimal number, placement of MFIs, and fleet size. To validate the approach, we apply it to a meal delivery platform in Amsterdam, demonstrating its practicality and scalability. Results show that implementing MFIs reduces overall system costs by 17\% and decreases rider idle time by 35\% compared to stationary facility operations. These findings underscore the transformative potential of MFIs to enhance the efficiency, sustainability, and adaptability of on-demand delivery systems in urban settings.},
  keywords = {Capacitated facility location, Meal delivery problem, Mobile fleet inventory, Urban waterway logistics},
}

% VERIFIED; verified 2026-10-11
@article{orbit-203e5c6925fc8644,
  title = {Estimating the value of safety against road crashes: A stated preference experiment on route choice of food delivery riders},
  author = {Kavta, Kuldeep and Azadeh, Shadi Sharif and Maknoon, Yousef and Wang, Yihong and Homem de Almeida Correia, Gonçalo},
  journal = {Transportation Research Part C: Emerging Technologies},
  year = {2025},
  volume = {179},
  pages = {105272},
  eid = {105272},
  doi = {10.1016/j.trc.2025.105272},
  url = {https://doi.org/10.1016/j.trc.2025.105272},
  issn = {0968-090X, 1879-2359},
  publisher = {Elsevier BV},
  abstract = {The rapid growth of the online food delivery industry has led to a significant increase in the number of delivery riders navigating urban streets, predominantly using bikes and e-bikes. This growth has been accompanied by a concerning rise in crashes involving these riders, posing a critical challenge for city authorities and policymakers. Promoting safer riding behavior, such as choosing safer routes while delivering food, can potentially reduce crash risks. With this motivation, this paper aims to evaluate the effectiveness of strategies that encourage riders to choose safer routes and estimate the value riders place on reducing the risk of road crashes. The paper presents a stated preference experiment conducted with food delivery riders in Amsterdam and Copenhagen to assess two targeted strategies: ’safety information’ and ’monetary incentives’, designed to encourage riders toward selecting safer routes. The results from the route choice model show that presenting information about safety against crashes on different routes and offering monetary incentives can effectively motivate riders to choose safer routes, even if these are longer. The trade-offs riders make between safer and shorter routes were quantified by calculating the Value of Risk Reduction (VRR) and Willingness to Accept (WTA) indicators, which offer valuable insights into riders’ safety preferences. These indicators highlight how much riders value risk reduction and the compensation required to choose safer routes. Furthermore, the findings reveal that factors related to riders’ working arrangements and socio-demographic profiles significantly influence their route choice decisions. The paper concludes with a discussion about the practical challenges associated with implementing the strategies to enhance rider safety and proposing potential solutions that can be useful for food delivery platforms and policymakers.},
  keywords = {Discrete choice experiment, Food delivery riders, Gig workers, Meal delivery, Route choice, Safety},
}

% VERIFIED; verified 2026-10-11
@article{orbit-afa4804285f227aa,
  title = {Optimizing multi-modal ride-matching with transfers},
  author = {Stokkink, Patrick and de Palma, André and Geroliminis, Nikolas},
  journal = {Transportation Research Part C: Emerging Technologies},
  year = {2025},
  volume = {179},
  pages = {105274},
  eid = {105274},
  doi = {10.1016/j.trc.2025.105274},
  url = {https://doi.org/10.1016/j.trc.2025.105274},
  issn = {0968-090X, 1879-2359},
  publisher = {Elsevier BV},
  abstract = {One of the limitations of ride-sharing is that matched drivers and riders need to have similar itineraries and desired arrival times for ride-sharing to be competitive against other transport modes. By allowing a single transfer at a designated transfer hub, their itineraries need to be only partially similar, and therefore more matching options are created. In this paper, we develop an optimal matching approach that matches riders to drivers, taking into account multi-modal routing options to model competition and collaboration between multiple modes of transport. We allow for transfers between modes and between multiple drivers. We model this as a path-based integer programming problem and we develop a simulated annealing algorithm to efficiently solve realistic large-scale instances of the problem. Our analysis indicates that a single transfer hub can reduce significantly the average generalized cost of riders and the total vehicle hours traveled by creating efficient matches. As opposed to previous studies, our work shows that ride-sharing not only attracts former public transport users but also former private car users. By allowing for intermodal transfers and by choosing the cost parameters such that transfers are favorable, itineraries where commuters use their car first, before sharing a ride on the second part of their journey, becomes an appealing alternative. Multi-modal ride-matching with transfers has the potential to increase ride-sharing, reduce the number of vehicle hours traveled in private cars, and reduce the number of cars that are present in urban areas during peak hours of congestion.},
  keywords = {Integer programming, Multi-modal, Ride-matching, Ride-sharing, Simulated annealing, Transfers},
}

% VERIFIED; verified 2026-10-11
@article{orbit-fa571a0660cd53ee,
  title = {Behavioral impact of range anxiety and unlock fees on shared electric-moped usage},
  author = {Burghardt, Sören Paul and Momen, Sara and Maknoon, Yousef and Azadeh, Shadi Sharif and Kavta, Kuldeep},
  journal = {Transportation Research Part D: Transport and Environment},
  year = {2025},
  volume = {145},
  pages = {104772},
  eid = {104772},
  doi = {10.1016/j.trd.2025.104772},
  url = {https://doi.org/10.1016/j.trd.2025.104772},
  issn = {1361-9209, 1879-2340},
  publisher = {Elsevier BV},
  abstract = {The evolving field of electric moped sharing systems is shaped by various determinants influencing user preferences, including range anxiety, pricing strategies, and regulatory changes. Utilizing a stated preference approach with a hybrid choice model, this research explores how these factors, along with attitudinal constructs, impact user decisions. The findings reveal that remaining driving range plays a critical role, with significant individual variability in its sensitivity, while perceived range anxiety did not significantly influence choices. Recent changes in helmet regulations have shifted preferences towards faster vehicles. Furthermore, dynamic pricing strategies, such as adjusting ride or unlock fees, can incentivize the use of less desirable vehicles with lower battery range or aid in user-based relocation. Nevertheless, low-range vehicles are less likely to be chosen, even with incentives. These insights provide valuable guidance for operators of electric moped sharing system to improve fleet management and optimize user satisfaction through strategic pricing and battery management.},
  keywords = {Electric moped sharing systems, Hybrid choice model, Pricing, Range anxiety, Shared micromobility, Stated preferences},
}

% VERIFIED; verified 2026-10-11
@article{orbit-efe44f12ec753f62,
  title = {Adaptive resilience strategies for supply chain networks against disruptions},
  author = {Hart Nibbrig, Maurice and Sharif Azadeh, Shadi and Maknoon, Yousef},
  journal = {Transportation Research Part E: Logistics and Transportation Review},
  year = {2025},
  volume = {200},
  pages = {104172},
  eid = {104172},
  doi = {10.1016/j.tre.2025.104172},
  url = {https://doi.org/10.1016/j.tre.2025.104172},
  issn = {1366-5545, 1878-5794},
  publisher = {Elsevier BV},
  abstract = {Supply chain networks face the critical challenge of enhancing resilience to disruptions while controlling the costs associated with resilience improvements. In this paper, we introduce an adaptive resilience improvement framework designed to sustain material flow by responding dynamically to emerging network vulnerabilities. Our framework centers on the production chain as a core element in resilience planning, integrating vulnerability assessment and reinforcement strategies through a tri-level optimization model. This model adapts to the network's changing conditions by (i) incorporating disruption scenario generation as an integral part of the decision-making process, allowing for the dynamic identification of vulnerabilities, and (ii) optimizing reinforcement strategies in response to them. We demonstrate the framework's effectiveness through two distinct case studies: a steel supply chain, where production flexibility improves resilience by 30\%, and a pharmaceutical supply chain affected by climate-related disruptions. Our computational results confirm the scalability and effectiveness of this approach in strengthening network-wide resilience as vulnerabilities evolve.},
  keywords = {Adaptive reinforcement, Climate-related disruptions, Mixed-integer optimization, Resilience evaluation, Supply chain resilience},
}

% VERIFIED; verified 2026-10-11
@article{orbit-2caf7c2d102c189f,
  title = {Designing a robust and cost-efficient electrified bus network with sparse energy consumption data},
  author = {Momen, Sara and Maknoon, Yousef and van Arem, Bart and Azadeh, Shadi Sharif},
  journal = {Transportation Research Part C: Emerging Technologies},
  year = {2025},
  volume = {171},
  pages = {105020},
  eid = {105020},
  doi = {10.1016/j.trc.2025.105020},
  url = {https://doi.org/10.1016/j.trc.2025.105020},
  issn = {0968-090X, 1879-2359},
  publisher = {Elsevier BV},
  abstract = {This paper addresses the challenges of charging infrastructure design (CID) for electrified public transport networks using Battery Electric Buses (BEBs) under conditions of sparse energy consumption data. Accurate energy consumption estimation is critical for cost-effective and reliable electrification but often requires costly field experiments, resulting in limited data. To address this issue, we propose two mathematical models designed to handle uncertainty and data sparsity in energy consumption. The first is a robust optimization model with box uncertainty, addressing variability in energy consumption. The second is a data-driven distributionally robust optimization model that leverages observed data to provide more flexible and informed solutions. To evaluate these models, we apply them to the Rotterdam bus network. Our analysis reveals three key insights: (1) Ignoring variations in energy consumption can result in operational unreliability, with up to 55\% of scenarios leading to infeasible trips. (2) Designing infrastructure based on worst-case energy consumption increases costs by 67\% compared to using average estimates. (3) The data-driven distributionally robust optimization model reduces costs by 28\% compared to the box uncertainty model while maintaining reliability, especially in scenarios where extreme energy consumption values are rare and data exhibit skewness. In addition to cost savings, this approach provides robust protection against uncertainty, ensuring reliable operation under diverse conditions.},
  keywords = {Distributionally robust optimization, Energy consumption variability, Minimum cost deployment, Operational reliability with sparse data, Public transport electrification},
}

% VERIFIED; verified 2026-10-11
@article{orbit-ee16586e0e1c3d14,
  title = {A data-to-value framework for freight ITS: Insights from a living lab},
  author = {Vanga, Ratnaji and Thiyagarajan, Nagasubramanian and Gelper, Sarah and Maknoon, Yousef and Duinkerken, Mark B. and Tavasszy, Lóránt A.},
  journal = {Research in Transportation Business \& Management},
  year = {2024},
  volume = {57},
  pages = {101214},
  eid = {101214},
  doi = {10.1016/j.rtbm.2024.101214},
  url = {https://doi.org/10.1016/j.rtbm.2024.101214},
  issn = {2210-5395, 2210-5409},
  publisher = {Elsevier BV},
  abstract = {The emergence of Intelligent Transportation Systems (ITS) for freight transport in recent times has created interest among practitioners and researchers to extend freight ITS to support broader logistics processes, including dynamic tour scheduling, loading and unloading, warehousing, and even production. However, connecting transport data, ITS and logistics information systems require collaboration between different organizations and new business models to create business value for logistics actors. It is critical for these stakeholders to consider how their business models connect to create meaningful new data-to-information value chains. This study develops a conceptual framework to identify opportunities for logistics value creation with freight transport data. Building on the literature we construct a framework that reconciles multi-firm and firm-level business modelling. The main component is a generalized framework for Data-to-Value (DtV) chains for applications in information and communications technology. In order to support its business validity, we extend this framework with Business Model Canvases (BMCs) of the actors in the value chain. Three real-life use cases from a freight ITS community in the Netherlands are used to evaluate and illustrate the framework.},
  keywords = {Business ecosystems, Business models, Co-design, Data-to-value chains, Freight transportation, Intelligent transport systems},
}

% VERIFIED; verified 2026-10-11
@article{orbit-c7431635f361772d,
  title = {A column and row generation approach to the crowd-shipping problem with transfers},
  author = {Stokkink, Patrick and Cordeau, Jean-François and Geroliminis, Nikolas},
  journal = {Omega},
  year = {2024},
  volume = {128},
  pages = {103134},
  eid = {103134},
  doi = {10.1016/j.omega.2024.103134},
  url = {https://doi.org/10.1016/j.omega.2024.103134},
  issn = {0305-0483, 1873-5274},
  publisher = {Elsevier BV},
  abstract = {Crowd-shipping is a last-mile delivery concept in which commuters pick up and deliver parcels on their pre-existing paths. In urban areas, crowd-shipping circumvents problems that traditional last-mile delivery systems suffer from, such as road congestion and lack of parking spaces, especially if more sustainable modes of transport are utilized, like bikes or e-bikes. Using transfers between crowd-shippers allows for expanding the service area and improving the overall performance. However, as this requires synchronization over space and time, it makes the problem more complex. In this work, we develop a model that can encompass fully heterogeneous crowd-shippers and parcels. Thereby, it allows for both direct time-synchronized transfers as well as intermediate storage at designated parcel lockers. We design a column generation algorithm to solve large-scale realistic instances to optimality. We extend the problem to allow crowd-shippers to carry multiple parcels at the same time and for this, we extend the algorithm to simultaneous column and row generation. We evaluate the performance of our algorithm as well as the potential of crowd-shipping with transfers on a realistic case study of a bike-based crowd-shipping system in Washington DC. Our methods solve realistic instances with 1000 crowd-shippers and 1000 parcels within minutes. The results show that a gain in revenue and service level of 30\% can be obtained by allowing transfers. By letting part of the population of crowd-shippers carry two or three parcels at the same time, the revenue and service level can be further increased by 30 to 50\%. Maximum locker capacities are shown to be reasonable and are the highest in areas where there is a large gap between the moment when parcels are dropped off and when they are picked up from parcel points, which are mainly in the city center.},
  keywords = {Column generation, Crowd-shipping, Last-mile delivery, Row generation, Transfers},
}

% VERIFIED; verified 2026-10-11
@article{orbit-32d4a3e6c5b6933c,
  title = {Ride-sharing with inflexible drivers in the Paris metropolitan area},
  author = {de Palma, André and Javaudin, Lucas and Stokkink, Patrick and Tarpin-Pitre, Léandre},
  journal = {Transportation},
  year = {2024},
  volume = {51},
  number = {3},
  pages = {963--986},
  doi = {10.1007/s11116-022-10361-1},
  url = {https://doi.org/10.1007/s11116-022-10361-1},
  issn = {0049-4488, 1572-9435},
  publisher = {Springer US},
  abstract = {In ride-sharing, commuters with similar itineraries share a vehicle for their trip. Despite its clear benefits in terms of reduced congestion, ride-sharing is not yet widely accepted. We propose a specific ride-sharing variant, where drivers are completely inflexible. This variant can form a competitive alternative against private transportation, due to the limited efforts that need to be made by drivers. However, due to this inflexibility, matching of drivers and riders can be substantially more complicated, compared to the situation where drivers can deviate. In this work, we propose a four-step procedure to identify the effect of such a ride-sharing scheme. We use a dynamic mesoscopic traffic simulator which computes departure-time choices and route choices for each commuter. The optimal matching of potential drivers and riders is obtained outside the simulation framework through an exact formulation of the problem. We evaluate the potential of this ride-sharing scheme on a real network of the Paris metropolitan area for the morning commute. We show that even with inflexible drivers and when only a small share of the population is willing to participate in the ride-sharing scheme, ride-sharing can alleviate congestion. Further improvements can be obtained by increasing the capacity of the vehicles or by providing small monetary incentives, but without jeopardizing the inflexibility of the drivers. Thereby, we show that ride-sharing can lead to fuel savings, CO \$\$\_{2}\$\$ 2 emission reductions and travel time savings on a network level, even with a low participation rate.},
}

% VERIFIED; verified 2026-10-11
@article{orbit-42c77161fdad46ad,
  title = {A continuum approximation approach to the depot location problem in a crowd-shipping system},
  author = {Stokkink, Patrick and Geroliminis, Nikolas},
  journal = {Transportation Research Part E: Logistics and Transportation Review},
  year = {2023},
  volume = {176},
  pages = {103207},
  eid = {103207},
  doi = {10.1016/j.tre.2023.103207},
  url = {https://doi.org/10.1016/j.tre.2023.103207},
  issn = {1366-5545, 1878-5794},
  publisher = {Elsevier BV},
  abstract = {Last-mile delivery in the logistics chain contributes to congestion in urban networks due to frequent stops. Crowd-shipping is a sustainable and low-cost alternative to traditional delivery but relies heavily on the availability of occasional couriers. In this work, we propose a crowd-shipping system that uses depots to improve accessibility for potential crowd-shippers to serve a large portion of the demand for small parcels. While small-scale versions of this problem have been recently addressed, scaling to larger instances significantly complexifies the problem. A heuristic approach based on continuum approximation is designed to evaluate the quality of a potential set of depots. By combining an efficient and accurate approximation method with a large neighborhood search heuristic, we can efficiently find a good set of depots, even for large-scale networks. The proposed methodology allows for heterogeneity among crowd-shippers and allows identifying the expected number of delivered parcels in every region, which can be used to enhance lower-level assignment decisions. A case study on the Washington DC network shows that depots are built at geographically central locations but most importantly at locations around popular origins for crowd-shippers. The optimal number of depots is mainly dependent on the marginal number of parcels that can be served by crowd-shippers from a specific depot, relative to the costs involved in opening that depot. The operational costs approximated by our continuum approximation approach deviate on average 2\% from the actual operational costs using dynamic assignment strategies. For small instances, our algorithm finds better solutions than solving a discrete formulation using CPLEX, while being almost 200 times faster. For large instances, the discrete formulation cannot be constructed by CPLEX, whereas the CA-based approach finds good solutions within minutes. Finally, the results show that using CA-based strategies in all three layers of decision-making can improve overall performance by 15\% compared to non-predictive strategies.},
}

% VERIFIED; verified 2026-10-11
@article{orbit-3976200fa93ad9da,
  title = {Incentive-based electric vehicle charging for managing bottleneck congestion},
  author = {Cenedese, Carlo and Stokkink, Patrick and Geroliminis, Nikolas and Lygeros, John},
  journal = {European Journal of Control},
  year = {2022},
  volume = {68},
  pages = {100697},
  eid = {100697},
  doi = {10.1016/j.ejcon.2022.100697},
  url = {https://doi.org/10.1016/j.ejcon.2022.100697},
  issn = {0947-3580, 1435-5671},
  publisher = {Elsevier BV},
  abstract = {We propose an incentive-based traffic demand management policy to alleviate traffic congestion on a road stretch that creates a bottleneck for the commuters. The incentive targets electric vehicles owners by proposing a discount on the energy price they use to charge their vehicles if they are flexible in their departure time. We show that, with a sufficient monetary budget, it is possible to completely eliminate the traffic congestion and we compute the optimal discount. We analyse also the case of limited budget, when the congestion cannot be completely eliminated. We compute analytically the policy minimising the congestion and estimate the level of inefficiency for different budgets. We corroborate our theoretical findings with numerical simulations that allow us to highlight the power of the proposed method in providing practical advice for the design of policies.},
  keywords = {Bottleneck model, Dynamic energy price, Electric vehicles, Incentive-based traffic demand management},
}

% VERIFIED; verified 2026-10-11
@article{orbit-6443bba5961d9ab5,
  title = {Electrification of a bus system with fast charging stations: Impact of battery degradation on design decisions},
  author = {Sharif Azadeh, Shadi and Vester, Jeroen and Maknoon, Yousef},
  journal = {Transportation Research Part C: Emerging Technologies},
  year = {2022},
  volume = {142},
  pages = {103807},
  eid = {103807},
  doi = {10.1016/j.trc.2022.103807},
  url = {https://doi.org/10.1016/j.trc.2022.103807},
  issn = {0968-090X, 1879-2359},
  publisher = {Elsevier BV},
  abstract = {In this paper, we evaluate the cost of the electrification of an existing bus network. We propose a family of bi-objective mathematical models to demonstrate the trade-off between strategic (i.e., battery sizing and the locations of charging stations) and operational decisions (i.e., battery degradation). The proposed mathematical models investigate different charging policies and measure their impacts on overall cost. Battery degradation is estimated by a tailored and linearized semi-empirical approach and is explicitly incorporated in the proposed mixed-integer linear models. The impact of different charging policies on reducing the overall costs is evaluated for a bus network in Rotterdam. The results show that allowing for flexibility in the loss of energy levels at each bus cycle results in savings up to 17\% in battery aging.},
  keywords = {Battery degradation, Charging policies, Electrification of bus systems, Mixed-integer linear problem, Network design},
}

% VERIFIED; verified 2026-10-11
@article{orbit-b8d5c1ab011a1d91,
  title = {Choice-driven dial-a-ride problem for demand responsive mobility service},
  author = {Sharif Azadeh, Shadi and Atasoy, Bilge and Ben-Akiva, Moshe E. and Bierlaire, Michel and Maknoon, Yousef},
  journal = {Transportation Research Part B: Methodological},
  year = {2022},
  volume = {161},
  pages = {128--149},
  doi = {10.1016/j.trb.2022.04.008},
  url = {https://doi.org/10.1016/j.trb.2022.04.008},
  issn = {0191-2615, 1879-2367},
  publisher = {Elsevier BV},
  abstract = {Urban mobility services face the challenge of planning their operations efficiently while complying with user preferences. In this paper, we introduce a new mathematical model called a choice-driven dial-a-ride problem (CD-DARP) which is a generalization of the dynamic DARP where passenger behavior is integrated in the operational planning using choice models and assortment optimization. We look at two types of mobility services, private and shared. Our problem extends the dynamic DARP by (i) changing its objective function to profit maximization, where both cost and revenue are variables, and (ii) incorporating assortment optimization with routing decisions in a dynamic setting. We propose a pricing scheme based on a choice model designed to offer service alternatives at the time a customer makes a request. We introduce a tailored algorithm to efficiently solve the dynamic CD-DARP. Computational results indicate that our proposed approach outperforms dynamic DARP in terms of reducing routing costs and improving the number of customers served.},
  keywords = {Assortment optimization, Choice-driven dial-a-ride problem, Demand responsive mobility, Mixed-Integer Linear Problem (MILP)},
}

% VERIFIED; verified 2026-10-11
@article{orbit-e3881cc9067f2ae2,
  title = {A Predictive–Proactive Approach for Slot Management of a Loading Facility With Truck ETA Information},
  author = {Prakoso, Emanuel Febrianto and Maknoon, Yousef and Pel, Adam and Tavasszy, Lóránt A. and Vanga, Ratnaji},
  journal = {Frontiers in Future Transportation},
  year = {2022},
  volume = {3},
  eid = {815267},
  doi = {10.3389/ffutr.2022.815267},
  url = {https://doi.org/10.3389/ffutr.2022.815267},
  issn = {2673-5210},
  publisher = {Frontiers},
  abstract = {Due to the uncertain and dynamic environment around scheduling systems, timely revisions or reschedules of the master plans are essential for achieving optimal utilization. With the recent development of Industry 4.0 technologies, many researchers perceive the creation of cyber-physical systems as a solution for managing systems under uncertainty. This article focuses on a loading facility under uncertain truck arrivals due to road congestion and proposes utilizing real-time truck location information to improve performance. We do this by developing an integrated system consisting of a predictive model using machine learning (MC) classifiers and a mathematical model for real-time slot rescheduling. The ML classifier is used to predict the presence probabilities of all the incoming trucks at a particular slot based on the historical traffic data and the real-time truck location. Subsequently, a Mixed-Integer Quadratic Programming (MIQP) model is developed to solve a Probabilistic Slot Rescheduling Problem (P-SRP), which uses the estimated truck presence probabilities and minimizes the total expected cost of rescheduling. We implemented this by first testing multiple ML classifiers and selected the ANN classifier for prediction as it outperformed others. Our limited experiments showed that the proposed method reduced the total rescheduling cost by 42 \% . Furthermore, our sensitivity analysis with different congestion levels, complexity, and rescheduling strategy also showed the practicality of the proposed approach.},
  keywords = {Real-time information, Proactive rescheduling, Truck visibility, Probabilistic optimization, machine learning, Uncertain arrivals},
}

% VERIFIED; verified 2026-10-11
@article{orbit-c1e3b2228ed5ef6f,
  title = {Influence of dynamic congestion with scheduling preferences on carpooling matching with heterogeneous users},
  author = {de Palma, André and Stokkink, Patrick and Geroliminis, Nikolas},
  journal = {Transportation Research Part B: Methodological},
  year = {2022},
  volume = {155},
  pages = {479--498},
  doi = {10.1016/j.trb.2021.11.005},
  url = {https://doi.org/10.1016/j.trb.2021.11.005},
  issn = {0191-2615, 1879-2367},
  publisher = {Elsevier BV},
  abstract = {Carpooling is an efficient measure to fight car ownership and reduce vehicle kilometres travelled. By individuals sharing their commutes, vehicle occupancy increases and congestion is reduced. We develop a dynamic ADL (Arnott, de Palma, Lindsey)–Vickrey approach for a corridor monocentric city à la Hotelling. First, we formulate the matching problem of heterogeneous users in carpooling as an MILP problem and we discuss its analytical properties when there is no congestion. Next, we construct a bi-level optimization problem involving matching (first stage) and dynamic traffic congestion with scheduling preferences (second stage) when congestion is endogenous. We provide a heuristic to attain an optimal matching for a dynamic traffic equilibrium with congestion. Such a template allows studying the two-way causality between dynamic congestion and carpooling matching.},
  keywords = {Economics, Engineering, Civil, Operations Research \& Management Science, Transportation, Transportation Science \& Technology, Business \& Economics, Engineering, Operations Research \& Management Science, Transportation, carpooling, ride-sharing, matching, scheduling delay, dynamic congestion, bi-level optimization, morning commute, traffic flows, model, bottleneck, benefits, optimization, service, design, scheme},
}

% VERIFIED; verified 2026-10-11
@article{orbit-95322d95f27c0721,
  title = {Passenger-centric timetable rescheduling: A user equilibrium approach},
  author = {Binder, Stefan and Maknoon, Yousef and Sharif Azadeh, Shadi and Bierlaire, Michel},
  journal = {Transportation Research Part C: Emerging Technologies},
  year = {2021},
  volume = {132},
  pages = {103368},
  eid = {103368},
  doi = {10.1016/j.trc.2021.103368},
  url = {https://doi.org/10.1016/j.trc.2021.103368},
  issn = {0968-090X, 1879-2359},
  publisher = {Elsevier BV},
  abstract = {Unexpected disruptions commonly occur in the railway network, causing delays, and extra cost for operators and inconvenience for passengers by missing their connection and facing overcrowded trains. This paper presents a passenger-centric approach for timetable rescheduling in case of disruption. We study a railway system in which passengers are free to choose their itinerary and compete over limited train capacity. We explicitly model the passengers’ decisions using a choice model. We propose a multi-objective algorithmic approach to solve the problem. Service punctuality, operating cost, and passengers’ inconvenience are selected as objectives. Computational experiments are performed on the Swiss and Dutch railway networks. The results demonstrate the performance of the algorithm in finding high-quality solutions in a computationally efficient manner.},
  keywords = {Heuristic algorithm, Pareto frontier, Passenger assignment, Passenger satisfaction, Railway timetabling rescheduling},
}

% VERIFIED; verified 2026-10-11
@article{orbit-b9fa1c9081fc950c,
  title = {An Integrated Territory Planning and Vehicle Routing Approach for a Multi-Objective Residential Waste Collection Problem},
  author = {Hurkmans, Sarah and Maknoon, Yousef and Negenborn, Rudy R. and Atasoy, Bilge},
  journal = {Transportation Research Record: Journal of the Transportation Research Board},
  year = {2021},
  volume = {2675},
  number = {7},
  pages = {616--628},
  doi = {10.1177/03611981211030262},
  url = {https://doi.org/10.1177/03611981211030262},
  issn = {0361-1981, 2169-4052},
  publisher = {SAGE Publications},
  abstract = {In this paper, we address a multi-objective residential waste collection problem with an integrated territory planning and vehicle routing approach. Dividing the problem into territories enables drivers to carry out the same route every week so they get familiar with it and residents put out their bins at the appropriate time. Another benefit is to reduce the computation time for large problems, since the complex characteristics of the involved vehicle routing problem make it otherwise difficult to solve. There are three characteristics that are important for good territory planning: minimum overlap, minimum travel time, and balanced workload. The purpose of this paper is to investigate the influence these three objectives have on each other, since they might be contradictory. Moreover, an Adaptive Large Neighborhood Search (ALNS) algorithm is developed for this specific problem which uses a K-means algorithm to generate the initial solution for territories. The results with the three objectives are shown to be useful for planners seeking to make informed decisions through the trade-off across different solutions with the Pareto frontiers provided. Moreover, the ALNS algorithm is shown to find good quality solutions in a reasonable computational time.},
}

% VERIFIED; verified 2026-10-11
@article{orbit-0aacb503839ea34f,
  title = {Predictive user-based relocation through incentives in one-way car-sharing systems},
  author = {Stokkink, Patrick and Geroliminis, Nikolas},
  journal = {Transportation Research Part B: Methodological},
  year = {2021},
  volume = {149},
  pages = {230--249},
  doi = {10.1016/j.trb.2021.05.008},
  url = {https://doi.org/10.1016/j.trb.2021.05.008},
  issn = {0191-2615, 1879-2367},
  publisher = {Elsevier BV},
  abstract = {Car-sharing systems are an attractive alternative to private vehicles due to their benefits in terms of mobility and sustainability. However, the distribution of vehicles throughout the network in one-way systems is disturbed due to asymmetry and stochasticity in demand. As a consequence, vehicles need to be relocated to maintain an adequate service level. In this paper, we develop a user-based vehicle relocation approach through the incentivization of customers and a predictive model for the state of the system based on Markov chains. Our methods determine the optimal incentive as a trade-off between the cost of an incentive and the expected omitted demand loss while taking into account the value of time of customers. We introduce a learning algorithm that allows the operator to estimate unknown customer preferences to find the optimal incentive. Experimental results in an event-based simulation of a real system show that the use of incentives can significantly increase the service level and profitability of a car-sharing system and decrease the number of staff members needed to balance the vehicles in the system. Thereby, incentives are a more sustainable alternative to staff-based relocations. Extensive sensitivity analyses show the prospective benefits in terms of customer flexibility and the robustness of our results to varying customer preferences.},
  keywords = {One-way car-sharing system, Prediction, User-based vehicle relocations, Incentivization},
}

% VERIFIED; verified 2026-10-11
@article{orbit-228898cb313905e6,
  title = {Storage assignment in the steel manufacturing industry: Mathematical modeling and a priority-based heuristic approach},
  author = {Ahmed, Mehwish R. and Beelaerts van Blokland, Wouter W.A. and Maknoon, M. Youssef},
  journal = {Journal of Supply Chain Management Science},
  year = {2021},
  volume = {2},
  number = {1-2},
  pages = {33--46},
  doi = {10.18757/jscms.2021.5899},
  url = {https://doi.org/10.18757/jscms.2021.5899},
  issn = {2451-9901},
  publisher = {TU Delft OPEN Publishing},
  abstract = {This paper presents a multi-criteria storage assignment model for the manufacturing system of the steel industry. The manufacturing system involves several plants, dozen of the production line, and thousands of different products. The products have to be routed and stored in various stages till it is dispatched to the end customer. Due to the size and weight of produced items, material handling is a costly operation. The handling cost is related to the number of handling, product storage time, and meeting the due date. This paper presents several storage assignment algorithms to reduce material handling costs. We have tested our algorithms with the data provided by a large steel company in Europe. The results indicate that considering product features in the storage assignment offers better performance on handling, storage time, and meeting the due date.},
}

% VERIFIED; verified 2026-10-11
@article{orbit-aaeb70c8010cb8bb,
  title = {Waste collection inventory routing with non-stationary stochastic demands},
  author = {Markov, Iliya and Bierlaire, Michel and Cordeau, Jean-François and Maknoon, Yousef and Varone, Sacha},
  journal = {Computers \& Operations Research},
  year = {2020},
  volume = {113},
  pages = {104798},
  eid = {104798},
  doi = {10.1016/j.cor.2019.104798},
  url = {https://doi.org/10.1016/j.cor.2019.104798},
  issn = {0305-0548, 1873-765X},
  publisher = {Elsevier BV},
  abstract = {We solve a rich routing problem inspired from practice, in which a heterogeneous fixed fleet is used for collecting recyclable waste from large containers over a finite planning horizon. Each container is equipped with a sensor that communicates its level at the start of the day. Given a history of observations, a forecasting model is used to estimate the expected demands and a forecasting error representing the level of uncertainty. The problem falls under the framework of the stochastic inventory routing problem and our main contribution is the modeling of the dynamic probability-based cost of container overflows and route failures over the planning horizon. We cast the problem as a mixed integer non-linear program and, to solve it, we develop an adaptive large neighborhood search algorithm that integrates a purpose-designed forecasting model, tested and validated on real data. We demonstrate the strength of our modeling approach on a set of rich inventory routing instances derived from real data coming from the canton of Geneva, Switzerland. Our approach significantly outperforms alternative deterministic policies in its ability to limit the occurrence of container overflows for the same routing cost. Finally, we show the benefit of a rolling horizon solution and derive lower and upper bounds on its cost.},
  keywords = {Demand forecasting, Overflows, Route failures, Stochastic inventory routing problem, Uncertainty, Waste collection},
}

% VERIFIED; verified 2026-10-11
@article{orbit-c94bf03ae9e90cd7,
  title = {Hinterland freight transportation replanning model under the framework of synchromodality},
  author = {Qu, Wenhua and Rezaei, Jafar and Maknoon, Yousef and Tavasszy, Lóránt},
  journal = {Transportation Research Part E: Logistics and Transportation Review},
  year = {2019},
  volume = {131},
  pages = {308--328},
  doi = {10.1016/j.tre.2019.09.014},
  url = {https://doi.org/10.1016/j.tre.2019.09.014},
  issn = {1366-5545, 1878-5794},
  publisher = {Elsevier BV},
  abstract = {Hinterland freight transportation is managed according to a pre-designed schedule. In daily operations, unexpected uncertainties cause deviation from the original plan. Thus replanning is needed to deal with the perturbations and complete the transportation tasks. This paper proposes a mixed-integer programming model to re-plan hinterland freight transportation, based on the framework of synchromodality. It is a holistic resolution of shipment flow rerouting, consequence transshipment organization in the intermediate terminals, and corresponding service rescheduling. The replanning benefits from a high operational flexibility and coordination via a split of shipment and aligning the departure time of service flows with the shipment flows.},
  keywords = {Freight transportation replanning, Shipment split, Synchromodality, Synchronization of shipment and services, Uncertainty management},
}

% VERIFIED; verified 2026-10-11
@article{orbit-f116dd68f1fddf08,
  title = {A two-stage route optimization algorithm for light aircraft transport systems},
  author = {Sharif Azadeh, Shadi and Bierlaire, Michel and Maknoon, Yousef},
  journal = {Transportation Research Part C: Emerging Technologies},
  year = {2019},
  volume = {100},
  pages = {259--273},
  doi = {10.1016/j.trc.2019.01.028},
  url = {https://doi.org/10.1016/j.trc.2019.01.028},
  issn = {0968-090X, 1879-2359},
  publisher = {Elsevier BV},
  abstract = {This paper presents a route optimization algorithm for light aircraft operating under visual flight rules. The problem aims at finding a minimum-duration, collision-free route in three spatial dimensions with possible aircraft maneuvers. The optimal route takes into account the aircraft kinodynamic characteristics and its interaction with external wind. A data processing approach is presented to recast the flying environment as a series of polyhedrons based on which a mixed-integer linear model is formulated. A two-stage route optimization model is then introduced to solve real-life instances. Computational experiments depict the efficiency of this approach.},
  keywords = {Heuristic, Light aircraft, MILP, Obstacle avoidance, Route optimization},
}

% VERIFIED; verified 2026-10-11
@article{orbit-38c86d4c7953e9fc,
  title = {A unified framework for rich routing problems with stochastic demands},
  author = {Markov, Iliya and Bierlaire, Michel and Cordeau, Jean-François and Maknoon, Yousef and Varone, Sacha},
  journal = {Transportation Research Part B: Methodological},
  year = {2018},
  volume = {114},
  pages = {213--240},
  doi = {10.1016/j.trb.2018.05.015},
  url = {https://doi.org/10.1016/j.trb.2018.05.015},
  issn = {0191-2615, 1879-2367},
  publisher = {Elsevier BV},
  abstract = {We introduce a unified framework for rich vehicle and inventory routing problems with complex physical and temporal constraints. Demands are stochastic, can be non-stationary, and are forecast using any model that provides the expected demands and their error term distribution, which can be any theoretical or empirical distribution. We offer a detailed discussion on the modeling of demand stochasticity, focusing on the probabilities and cost effects of undesirable events, such as stock-outs, breakdowns and route failures, and their associated recourse actions. Tractability is achieved through the ability to pre-compute or at least partially pre-process the stochastic information, which is possible under mild assumptions for a general inventory policy. We integrate the stochastic aspect into a mixed integer non-linear program, illustrate applications to various problem classes, and show how to model specific problems through the lens of inventory routing. The case study is based on two sets of realistic instances, representing a waste collection inventory routing problem and a facility maintenance problem, respectively. We analyze the effects of our assumptions on modeling realism and tractability, and demonstrate that our framework significantly outperforms deterministic policies in its ability to limit the number of undesirable events for the same routing cost.},
  keywords = {Forecasting, Recourse, Rich routing problem, Stochastic demand, Tractability, Unified framework},
}

% VERIFIED; verified 2026-10-11
@article{orbit-8fe2b69b17ab61ce,
  title = {A Time-use Model for the Automated Vehicle-era},
  author = {Pudāne, Baiba and Molin, Eric J.E. and Arentze, Theo A. and Maknoon, Yousef and Chorus, Caspar G.},
  journal = {Transportation Research Part C: Emerging Technologies},
  year = {2018},
  volume = {93},
  pages = {102--114},
  doi = {10.1016/j.trc.2018.05.022},
  url = {https://doi.org/10.1016/j.trc.2018.05.022},
  issn = {0968-090X, 1879-2359},
  publisher = {Elsevier BV},
  abstract = {Automated Vehicles (AVs) offer their users a possibility to perform new non-driving activities while being on the way. The effects of this opportunity on travel choices and travel demand have mostly been conceptualised and modelled via a reduced penalty associated with (in-vehicle) travel time. This approach invariably leads to a prediction of more car-travel. However, we argue that reductions in the size of the travel time penalty are only a crude proxy for the variety of changes in time-use and travel patterns that are likely to occur at the advent of AVs. For example, performing activities in an AV can save time and in this way enable the execution of other activities within a day. Activities in an AV may also eliminate or generate a need for some other activities and travel. This may lead to an increase, or decrease in travel time, depending on the traveller’s preferences, schedule, and local accessibility. Neglecting these dynamics is likely to bias forecasts of travel demand and travel behaviour in the AV-era. In this paper, we present an optimisation model which rigorously captures the time-use effects of travellers’ ability to perform on-board activities. Using a series of worked out examples, we test the face validity of the model and demonstrate how it can be used to predict travel choices in the AV-era. },
  keywords = {Automated vehicles, Time-use model, On-board activities, Travel behaviour, Travel demand, Multitasking},
}

% VERIFIED; verified 2026-10-11
@article{orbit-0b3819af5a2df81b,
  title = {Train timetable design under elastic passenger demand},
  author = {Robenek, Tomáš and Azadeh, Shadi Sharif and Maknoon, Yousef and de Lapparent, Matthieu and Bierlaire, Michel},
  journal = {Transportation Research Part B: Methodological},
  year = {2018},
  volume = {111},
  pages = {19--38},
  doi = {10.1016/j.trb.2018.03.002},
  url = {https://doi.org/10.1016/j.trb.2018.03.002},
  issn = {0191-2615, 1879-2367},
  publisher = {Elsevier BV},
  abstract = {A passenger centric timetable is such a timetable that the satisfaction of the passengers is maximized. However, these timetables only maximize the probability of a passenger to take the train, but provide no insight on the actual choices of the passengers. Therefore, in this manuscript we replace the deterministic passenger satisfaction function with a probabilistic demand forecasting model inside of the passenger centric train timetable design. The actual forecasts lead to a realistic train occupation. Knowing the train occupation, we can estimate the revenue and to use pricing as a mobility management to further improve the level-of-service. We use a logit model that we calibrate to reflect the known demand elasticities. We further include a competing operator as an opt-out option for the passengers. Subsequently, we integrate the passenger centric train timetabling problem with a ticket pricing problem. We solve the elastic passenger centric train timetabling problem for various types of timetables using a simulated annealing heuristic on a case study of Israeli Railways. The results of our case study show that the generated revenues can be increased by up to 15\% when taking into account the passengers’ behavior along with a specific pricing scheme. This study further confirms the advantages of hybrid cyclicity.},
  keywords = {Hybrid cyclicity, Passenger centric train timetabling problem, Railway demand forecasting, Revenue, Ticket pricing},
}

% VERIFIED; verified 2026-10-11
@article{orbit-974bb7dd6afe82da,
  title = {Exogenous priority rules for the capacitated passenger assignment problem},
  author = {Binder, Stefan and Maknoon, Yousef and Bierlaire, Michel},
  journal = {Transportation Research Part B: Methodological},
  year = {2017},
  volume = {105},
  pages = {19--42},
  doi = {10.1016/j.trb.2017.08.022},
  url = {https://doi.org/10.1016/j.trb.2017.08.022},
  issn = {0191-2615, 1879-2367},
  publisher = {Elsevier BV},
  abstract = {We propose a novel algorithm for the capacitated passenger assignment problem in public transportation where exogenous priority lists define the order in which passengers are assigned. Separating explicitly theses rules from the assignment procedure allows for a great deal of flexibility to model various priority rules. When the actual rules are endogenous, the framework can easily be embedded in a fixed-point specification. Computational experiments are performed on a realistic case study based on the morning rush hours of the timetable of Canton Vaud, Switzerland. The algorithm is able to assign the demand in very low computational times. The results provide evidences that the ordering of the passengers does not have a significant impact on aggregate performance indicators (such as average delay and level of unsatisfied demand), but that the variability at the individual passenger level is substantial. Thanks to its flexibility, our framework can easily be implemented by a railway operator who wishes to evaluate the effects of different policies in terms of passenger priorities.},
  keywords = {Capacitated passenger assignment, Public transportation, Passenger priority list},
}

% VERIFIED; verified 2026-10-11
@article{orbit-12ab8424be68b4fc,
  title = {An integer programming approach to scheduling the transshipment of products at cross-docks in less-than-truckload industries},
  author = {Maknoon, Yousef and Soumis, François and Baptiste, Pierre},
  journal = {Computers \& Operations Research},
  year = {2017},
  volume = {82},
  pages = {167--179},
  doi = {10.1016/j.cor.2017.01.018},
  url = {https://doi.org/10.1016/j.cor.2017.01.018},
  issn = {0305-0548, 1873-765X},
  publisher = {Elsevier BV},
  abstract = {This paper introduces an exact method to schedule the internal transshipment process at cross-docks in less-than-truckload industries. An integer programming formulation is presented to minimize the cost of double handling by synchronizing two types of decisions: (1) products’ internal transferring route, and (2) the order of processing trucks at the terminal doors. Several valid inequalities are introduced to strengthen the formulation and to increase the efficiency of the proposed algorithm. A tailored branch and bound algorithm is developed. Several structural properties and a heuristic method are implemented to enhance the algorithm. Computational experiments of up to 40 trucks demonstrate the efficiency of the proposed approach.},
  keywords = {Exact methods, Material handling, MILP, Scheduling},
}

% VERIFIED; verified 2026-10-11
@article{orbit-3153afda4c966e49,
  title = {The multi-objective railway timetable rescheduling problem},
  author = {Binder, Stefan and Maknoon, Yousef and Bierlaire, Michel},
  journal = {Transportation Research Part C: Emerging Technologies},
  year = {2017},
  volume = {78},
  pages = {78--94},
  doi = {10.1016/j.trc.2017.02.001},
  url = {https://doi.org/10.1016/j.trc.2017.02.001},
  issn = {0968-090X, 1879-2359},
  publisher = {Elsevier BV},
  abstract = {Unexpected disruptions occur for many reasons in railway networks and cause delays, cancelations, and, eventually, passenger inconvenience. This research focuses on the railway timetable rescheduling problem from a macroscopic point of view in case of large disruptions. The originality of our approach is to integrate three objectives to generate a disposition timetable: the passenger satisfaction, the operational costs and the deviation from the undisrupted timetable. We formulate the problem as an Integer Linear Program that optimizes the first objective and includes ε-constraints for the two other ones. By solving the problem for different values of ε, the three-dimensional Pareto frontier can be explored to understand the trade-offs among the three objectives. The model includes measures such as canceling, delaying or rerouting the trains of the undisrupted timetable, as well as scheduling emergency trains. Furthermore, passenger flows are adapted dynamically to the new timetable. Computational experiments are performed on a realistic case study based on a heavily used part of the Dutch railway network. The model is able to find optimal solutions in reasonable computational times. The results provide evidence that adopting a demand-oriented approach for the management of disruptions not only is possible, but may lead to significant improvement in passenger satisfaction, associated with a low operational cost of the disposition timetable.},
  keywords = {Integer linear program, Multi-objective, Pareto frontier, Passenger satisfaction, Railway timetable rescheduling},
}

% VERIFIED; verified 2026-10-11
@article{orbit-5aac035461d5b2ef,
  title = {Hybrid cyclicity: Combining the benefits of cyclic and non-cyclic timetables},
  author = {Robenek, Tomáš and Sharif Azadeh, Shadi and Maknoon, Yousef and Bierlaire, Michel},
  journal = {Transportation Research Part C: Emerging Technologies},
  year = {2017},
  volume = {75},
  pages = {228--253},
  doi = {10.1016/j.trc.2016.12.015},
  url = {https://doi.org/10.1016/j.trc.2016.12.015},
  issn = {0968-090X, 1879-2359},
  publisher = {Elsevier BV},
  abstract = {We propose a new type of timetable that would combine both the regularity of the cyclic timetables and the flexibility of the non-cyclic ones. In order to do so, several combinations of the two timetables are considered. The regularity is incorporated in their design and the flexibility is evaluated using the passenger satisfaction (in monetary units). Each of the tested timetables is constructed using the Passenger Centric Train Timetabling Problem (PCTTP), that is solved using a simulated annealing heuristic. Note that the PCTTP, unlike the traditional Train Timetabling Problem (TTP), does not take into account the conflicts among trains. The aim of the PCTTP is to design such timetables that the passengers’ satisfaction is maximized and it remains the aim of the TTP to remove any potential conflicts. The performance of each of the considered timetables is assessed on the real network of Israeli Railways. The results of the case study show that our proposed hybrid cyclic timetable can provide the benefits of the cyclic and the non-cyclic timetable simultaneously. This timetable consists of 75\% of cyclic trains (securing the regularity of the service) and of 25\% of non-cyclic trains (deployed as supplementary trains during the peak hours and capturing the demand fluctuation). The level of the passenger satisfaction of the hybrid cyclic timetable is similar to the level of the non-cyclic one, which has about 18.5\% of improvement as compared to the purely cyclic one.},
  keywords = {Cyclicity, Passenger centric train timetabling problem, Passenger satisfaction, Railway timetable, Simulated annealing},
}

% VERIFIED; verified 2026-10-11
@article{orbit-9d79235ada6f5f6e,
  title = {Vehicle routing with cross-dock selection},
  author = {Maknoon, Yousef and Laporte, Gilbert},
  journal = {Computers \& Operations Research},
  year = {2017},
  volume = {77},
  pages = {254--266},
  doi = {10.1016/j.cor.2016.08.007},
  url = {https://doi.org/10.1016/j.cor.2016.08.007},
  issn = {0305-0548, 1873-765X},
  publisher = {Elsevier BV},
  abstract = {The vehicle routing problem with cross-dock selection is a variant of the vehicle routing problem containing spatial and load synchronization constraints by which products are transferred and processed via at least one cross-dock. This paper presents a mathematical formulation of the problem and an adaptive large neighborhood search heuristic. Computational experiments on a set of benchmark instances demonstrate the efficiency of the proposed methodology. (C) 2016 Elsevier Ltd. All rights reserved.},
  keywords = {Vehicle routing, Cross-docking, Adaptive Large Neighborhood Search (ALNS)},
}

% VERIFIED; verified 2026-10-11
@article{orbit-7bf560d75b6df0b8,
  title = {Optimizing transshipment workloads in less-than-truckload cross-docks},
  author = {Maknoon, Yousef and Soumis, François and Baptiste, Pierre},
  journal = {International Journal of Production Economics},
  year = {2016},
  volume = {179},
  pages = {90--100},
  doi = {10.1016/j.ijpe.2016.05.015},
  url = {https://doi.org/10.1016/j.ijpe.2016.05.015},
  issn = {0925-5273, 1873-7579},
  publisher = {Elsevier BV},
  abstract = {This paper presents a scheduling model to enhance cross-docking operations. It attempts to reduce the transshipment workload by minimizing the total number of products that require double-handling. We formalize the problem and represent its mathematical form. Moreover, we develop a variable neighborhood search heuristic to tackle large problems. Computational results depict the effectiveness of our algorithm. Finally, we examine the influence of terminal design and truck scheduling on transshipment workload and provide recommendations to manage cross-docking process. (C) 2016 Elsevier B.V. All rights reserved.},
  keywords = {Cross-docking, Material handling, Scheduling, Integer programming, Variable neighborhood search},
}

% VERIFIED; verified 2026-10-11
@article{orbit-b8451e9dea3a8a43,
  title = {Passenger centric train timetabling problem},
  author = {Robenek, Tomáš and Maknoon, Yousef and Azadeh, Shadi Sharif and Chen, Jianghang and Bierlaire, Michel},
  journal = {Transportation Research Part B: Methodological},
  year = {2016},
  volume = {89},
  pages = {107--126},
  doi = {10.1016/j.trb.2016.04.003},
  url = {https://doi.org/10.1016/j.trb.2016.04.003},
  issn = {0191-2615, 1879-2367},
  publisher = {Elsevier BV},
  abstract = {The aim of this paper is to analyze and to improve the current planning process of the passenger railway service in light of the recent railway market changes. In order to do so, we introduce the Passenger Centric Train Timetabling Problem. The originality of our approach is that we account for the passenger satisfaction in the design of the timetable. We consider both types of timetable(s): cyclic and non-cyclic. The problem is modeled as a Mixed Integer Linear Programming (MILP) problem with an objective of maximizing the train operating company's profit while maintaining epsilon level of passenger satisfaction. The model does not take into account conflicts between trains and does not adjust dwell times at stopping stations among the lines. By solving the model for various values of epsilon, the approximated Pareto frontier is constructed. The analysis, based on an experiment using realistic data, shows that an improvement of passenger satisfaction while maintaining a low profit loss for the railway company can be achieved. A sensitivity analysis on passenger congestion illustrates a quantitative evidence that the non-cyclic timetables can account better for high density demand in comparison to cyclic timetables. (C) 2016 Elsevier Ltd. All rights reserved.},
  keywords = {Railway timetable, Passenger satisfaction, Profit, Cyclic, Non-cyclic, MILP},
}

% VERIFIED; verified 2026-10-11
@article{orbit-42d0287f7d578332,
  title = {A sequential priority-based heuristic for scheduling material handling in a satellite cross-dock},
  author = {Maknoon, Yousef and Kone, Oumar and Baptiste, Pierre},
  journal = {Computers \& Industrial Engineering},
  year = {2014},
  volume = {72},
  pages = {43--49},
  doi = {10.1016/j.cie.2014.03.002},
  url = {https://doi.org/10.1016/j.cie.2014.03.002},
  issn = {0360-8352, 1879-0550},
  publisher = {Elsevier BV},
  abstract = {In a less-than-truckload logistic network, the satellite cross-dock is in charge of local deliveries. These terminals operate in two separate shifts: consolidating pickup freight for overnight shipments and processing received products for early morning deliveries. Satellite cross-docks are flexible when scheduling trucks and where the priority is to minimize handling cost. In this paper, we formalize cross-docking process by presenting a mathematical model. We develop a sequential priority-based heuristic algorithm to deal with practical problems. Numerical results show the stability of the heuristic method for fairly large size problems.},
}

% VERIFIED; verified 2026-10-11
@article{orbit-accadc361c14c858,
  title = {An assessment of the integration of nurse timetable changes with operating room planning and scheduling},
  author = {Di Martinelly, Christine and Baptiste, Pierre and Maknoon, Yousef},
  journal = {International Journal of Production Research},
  year = {2014},
  volume = {52},
  number = {24},
  pages = {7239--7250},
  doi = {10.1080/00207543.2014.916827},
  url = {https://doi.org/10.1080/00207543.2014.916827},
  issn = {0020-7543, 1366-588X},
  publisher = {Informa UK Limited},
  abstract = {The objective of this paper is to understand the links between the management of operating rooms and nurses, and to investigate the trade-offs between the number of operating rooms used, nurses used and overtime work. To do so, we proposed a model that plans and schedules surgical interventions in the operating rooms while considering the availabilities of surgeons and anesthesiologists; the model also includes or discards nurse scheduling. The flexible modeling approach allows us to compare different alternatives, each one representing a different scenario of managing the operating rooms at an operational level. The scenarios were applied to two data-sets and compared on the basis of performance indicators, which include operating costs, utilisation rates of nurses and number of overtime hours done. The important findings were that there is no relationship between the number of nurses required and the number of operating rooms used; the simultaneous scheduling of nurses and surgical interventions provided a better resource usage, a higher occupation rate of nurses, less overtime and furthermore, operating costs were lowered by at least 10\% on average.},
}

% VERIFIED; verified 2026-10-11
@article{orbit-52f2dba4999c0de8,
  title = {Cross-docking: increasing platform efficiency by sequencing incoming and outgoing semi-trailers},
  author = {Maknoon, Mohammad Yousef and Baptiste, Pierre},
  journal = {International Journal of Logistics Research and Applications},
  year = {2009},
  volume = {12},
  number = {4},
  pages = {249--261},
  doi = {10.1080/13675560903076081},
  url = {https://doi.org/10.1080/13675560903076081},
  issn = {1367-5567, 1469-848X},
  publisher = {Informa UK Limited},
  abstract = {Cross-docking involves use of a transhipment platform to consolidate incoming products for outgoing destinations. Research in cross-docking mostly studies the cross-dock network (platform location) and the platform design (door locations). In this study, we consider a platform's internal operation and we focus on the direct flow of products from receiving to shipping doors. This flow can be improved by the synchronisation of incoming and outgoing semi-trailers. Two methods – dynamic programming and a heuristic approach integrated with a stochastic evolutionary algorithm – are proposed as a resolution approach for this problem.},
}

% INCOMPLETE; verified 2026-10-11
@article{orbit-5b332625277027e1,
  title = {Scheduling of two and three machine robotic cells with fuzzy methodology},
  author = {Zarandi, M. Hossein Fazel and Zarandi, M. Mehdi Fazel and Maknoon, M. Yousef and Masoumi, J.},
  journal = {International Journal of Management Science and Engineering Management},
  year = {2007},
  volume = {2},
  number = {4},
  pages = {243--256},
  doi = {10.1080/17509653.2007.10671024},
  url = {https://doi.org/10.1080/17509653.2007.10671024},
  issn = {1750-9653, 1750-9661},
  publisher = {Informa UK Limited},
  abstract = {This paper addresses the scheduling of robotic cells with two and three machines with fuzzy methodology. Some of the scheduling problems of these categories are transferred into a solvable traveling salesman problem that can be solved in a polynomial time. For generating the optimal part sequencing in the cells, the Gilmore and Gomory algorithm is modified and instead, a fuzzy Gilmore and Gomory algorithm is developed. Then, the proposed algorithm is tested and verified in a supplier company that produces part for an automobile industry. In any case, we compare the results of the proposed fuzzy method with those of crisp ones. The results show the superiority of the proposed algorithm in terms of flexibility, robustness, and reduction of cycle times.},
}