Fairness in hazmat routing-scheduling: A bi-objective Stackelberg game

Seyed Sina Mohri; Nasrin Asgari; Reza Zanjirani Farahani; Michael Bourlakis; Benjamin Laker

doi:10.1016/j.tre.2020.102006

Fairness in hazmat routing-scheduling: A bi-objective Stackelberg game

Seyed Sina Mohri, Nasrin Asgari, Reza Zanjirani Farahani, Michael Bourlakis, Benjamin Laker

Centre for Sustainability and Responsible Management

Research output: Contribution to journal › Article › peer-review

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Abstract

We investigate a hazmat routing-scheduling problem. To minimize the overall expected risk, various vehicles may take different routes/schedules to avoid multiple accidents on the same link.
Therefore, the company envisages two issues: (1) unfairly, a vehicle departing earlier from its origin may arrive earlier at its destination than the others leaving later; (2) focusing only on the minimization of risk may increase travel time/cost incurred by the company. We suggest a bi-objective game-theoretic formulation and solve it by a modified Adaptive Large Neighborhood Search and Simulated Annealing. We test the solution on a real-life case and extract practical insights.

© 2020, Elsevier. The attached document (embargoed until 25/06/2023) is an author produced version of a paper published in TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW uploaded in accordance with the publisher’s self-archiving policy. The final published version (version of record) is available online at the link. Some minor differences between this version and the final published version may remain. We suggest you refer to the final published version should you wish to cite from it.

Original language	English
Journal	TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW
DOIs	https://doi.org/10.1016/j.tre.2020.102006
Publication status	Published - 25 Jun 2020

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Cite this

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title = "Fairness in hazmat routing-scheduling: A bi-objective Stackelberg game",

abstract = "We investigate a hazmat routing-scheduling problem. To minimize the overall expected risk, various vehicles may take different routes/schedules to avoid multiple accidents on the same link.Therefore, the company envisages two issues: (1) unfairly, a vehicle departing earlier from its origin may arrive earlier at its destination than the others leaving later; (2) focusing only on the minimization of risk may increase travel time/cost incurred by the company. We suggest a bi-objective game-theoretic formulation and solve it by a modified Adaptive Large Neighborhood Search and Simulated Annealing. We test the solution on a real-life case and extract practical insights.{\textcopyright} 2020, Elsevier. The attached document (embargoed until 25/06/2023) is an author produced version of a paper published in TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW uploaded in accordance with the publisher{\textquoteright}s self-archiving policy. The final published version (version of record) is available online at the link. Some minor differences between this version and the final published version may remain. We suggest you refer to the final published version should you wish to cite from it.",

author = "Mohri, {Seyed Sina} and Nasrin Asgari and Farahani, {Reza Zanjirani} and Michael Bourlakis and Benjamin Laker",

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AU - Asgari, Nasrin

AU - Farahani, Reza Zanjirani

AU - Bourlakis, Michael

AU - Laker, Benjamin

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N2 - We investigate a hazmat routing-scheduling problem. To minimize the overall expected risk, various vehicles may take different routes/schedules to avoid multiple accidents on the same link.Therefore, the company envisages two issues: (1) unfairly, a vehicle departing earlier from its origin may arrive earlier at its destination than the others leaving later; (2) focusing only on the minimization of risk may increase travel time/cost incurred by the company. We suggest a bi-objective game-theoretic formulation and solve it by a modified Adaptive Large Neighborhood Search and Simulated Annealing. We test the solution on a real-life case and extract practical insights.© 2020, Elsevier. The attached document (embargoed until 25/06/2023) is an author produced version of a paper published in TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW uploaded in accordance with the publisher’s self-archiving policy. The final published version (version of record) is available online at the link. Some minor differences between this version and the final published version may remain. We suggest you refer to the final published version should you wish to cite from it.

AB - We investigate a hazmat routing-scheduling problem. To minimize the overall expected risk, various vehicles may take different routes/schedules to avoid multiple accidents on the same link.Therefore, the company envisages two issues: (1) unfairly, a vehicle departing earlier from its origin may arrive earlier at its destination than the others leaving later; (2) focusing only on the minimization of risk may increase travel time/cost incurred by the company. We suggest a bi-objective game-theoretic formulation and solve it by a modified Adaptive Large Neighborhood Search and Simulated Annealing. We test the solution on a real-life case and extract practical insights.© 2020, Elsevier. The attached document (embargoed until 25/06/2023) is an author produced version of a paper published in TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW uploaded in accordance with the publisher’s self-archiving policy. The final published version (version of record) is available online at the link. Some minor differences between this version and the final published version may remain. We suggest you refer to the final published version should you wish to cite from it.

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