Incorporating Service Reliability in Multi-depot Vehicle Scheduling
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arXiv
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| Format: | Preprint |
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2024
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| _version_ | 1866929404585705472 |
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| author | Castro, Margarita P. Bodur, Merve Shalaby, Amer |
| author_facet | Castro, Margarita P. Bodur, Merve Shalaby, Amer |
| contents | The multi-depot vehicle scheduling problem (MDVSP) is a critical planning challenge for transit agencies. We introduce a novel approach to MDVSP by incorporating service reliability through chance-constrained programming (CCP), targeting the pivotal issue of travel time uncertainty and its impact on transit service quality. Our model guarantees service reliability measured by on-time performance (OTP), a primary metric for transit agencies, and fairness across different service areas.We propose an exact branch-and-cut (B&C) scheme to solve our CCP model. We present several cut-generation procedures that exploit the underlying problem structure and analyze the relationship between the obtained cut families. Additionally, we design a Lagrangian-based heuristic to handle large-scale instances reflective of real-world transit operations. Our approach partitions the set of trips, each subset leading to a subproblem that can be efficiently solved with our B&C algorithm, and then employs a procedure to combine the subproblem solutions to create a vehicle schedule that satisfies all the planning constraints of the MDVSP. Our empirical evaluation demonstrates the superiority of our stochastic variant in achieving cost-effective schedules with reliable OTP guarantees compared to alternatives commonly used by practitioners, as well as the computational benefits of our methodologies. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2407_00836 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Incorporating Service Reliability in Multi-depot Vehicle Scheduling Castro, Margarita P. Bodur, Merve Shalaby, Amer Optimization and Control The multi-depot vehicle scheduling problem (MDVSP) is a critical planning challenge for transit agencies. We introduce a novel approach to MDVSP by incorporating service reliability through chance-constrained programming (CCP), targeting the pivotal issue of travel time uncertainty and its impact on transit service quality. Our model guarantees service reliability measured by on-time performance (OTP), a primary metric for transit agencies, and fairness across different service areas.We propose an exact branch-and-cut (B&C) scheme to solve our CCP model. We present several cut-generation procedures that exploit the underlying problem structure and analyze the relationship between the obtained cut families. Additionally, we design a Lagrangian-based heuristic to handle large-scale instances reflective of real-world transit operations. Our approach partitions the set of trips, each subset leading to a subproblem that can be efficiently solved with our B&C algorithm, and then employs a procedure to combine the subproblem solutions to create a vehicle schedule that satisfies all the planning constraints of the MDVSP. Our empirical evaluation demonstrates the superiority of our stochastic variant in achieving cost-effective schedules with reliable OTP guarantees compared to alternatives commonly used by practitioners, as well as the computational benefits of our methodologies. |
| title | Incorporating Service Reliability in Multi-depot Vehicle Scheduling |
| topic | Optimization and Control |
| url | https://arxiv.org/abs/2407.00836 |