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Optimizing schools’ start time and bus routes

Author

Listed:
  • Dimitris Bertsimas

    (Operations Research Center, Massachusetts Institute of Technology, Cambridge, MA 02139)

  • Arthur Delarue

    (Operations Research Center, Massachusetts Institute of Technology, Cambridge, MA 02139)

  • Sebastien Martin

    (Operations Research Center, Massachusetts Institute of Technology, Cambridge, MA 02139)

Abstract

Maintaining a fleet of buses to transport students to school is a major expense for school districts. To reduce costs by reusing buses between schools, many districts spread start times across the morning. However, assigning each school a time involves estimating the impact on transportation costs and reconciling additional competing objectives. Facing this intricate optimization problem, school districts must resort to ad hoc approaches, which can be expensive, inequitable, and even detrimental to student health. For example, there is medical evidence that early high school starts are impacting the development of an entire generation of students and constitute a major public health crisis. We present an optimization model for the school time selection problem (STSP), which relies on a school bus routing algorithm that we call biobjective routing decomposition (BiRD). BiRD leverages a natural decomposition of the routing problem, computing and combining subproblem solutions via mixed integer optimization. It significantly outperforms state-of-the-art routing methods, and its implementation in Boston has led to $5 million in yearly savings, maintaining service quality for students despite a 50-bus fleet reduction. Using BiRD, we construct a tractable proxy to transportation costs, allowing the formulation of the STSP as a multiobjective generalized quadratic assignment problem. Local search methods provide high-quality solutions, allowing school districts to explore tradeoffs between competing priorities and choose times that best fulfill community needs. In December 2017, the development of this method led the Boston School Committee to unanimously approve the first school start time reform in 30 years.

Suggested Citation

  • Dimitris Bertsimas & Arthur Delarue & Sebastien Martin, 2019. "Optimizing schools’ start time and bus routes," Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 116(13), pages 5943-5948, March.
  • Handle: RePEc:nas:journl:v:116:y:2019:p:5943-5948
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    Citations

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    Cited by:

    1. Amanda Chu & Pinar Keskinocak & Monica C. Villarreal, 2020. "Introduction: Empowering Denver Public Schools to Optimize School Bus Operations," Interfaces, INFORMS, vol. 50(5), pages 298-312, September.
    2. König, Pascal D. & Wenzelburger, Georg, 2021. "The legitimacy gap of algorithmic decision-making in the public sector: Why it arises and how to address it," Technology in Society, Elsevier, vol. 67(C).
    3. Dimitris Bertsimas & Arthur Delarue & William Eger & John Hanlon & Sebastien Martin, 2020. "Bus Routing Optimization Helps Boston Public Schools Design Better Policies," Interfaces, INFORMS, vol. 50(1), pages 37-49, January.
    4. Erica L. Plambeck & Kamalini Ramdas, 2020. "Alleviating Poverty by Empowering Women Through Business Model Innovation: Manufacturing & Service Operations Management Insights and Opportunities," Manufacturing & Service Operations Management, INFORMS, vol. 22(1), pages 123-134, January.
    5. Kuo, Yong-Hong & Leung, Janny M.Y. & Yan, Yimo, 2023. "Public transport for smart cities: Recent innovations and future challenges," European Journal of Operational Research, Elsevier, vol. 306(3), pages 1001-1026.

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