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Collecting Sleep, Circadian, Fatigue, and Performance Data in Complex Operational Environments
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Published on: August 8, 2019

Optimizing schools' start time and bus routes.

Dimitris Bertsimas1, Arthur Delarue1, Sebastien Martin2

  • 1Operations Research Center, Massachusetts Institute of Technology, Cambridge, MA 02139.

Proceedings of the National Academy of Sciences of the United States of America
|March 14, 2019
PubMed
Summary
This summary is machine-generated.

Optimizing school bus routes with the biobjective routing decomposition (BiRD) algorithm saves millions for school districts. This approach balances transportation costs and student needs, improving efficiency and equity in school start times.

Keywords:
educationfairnessoptimizationpublic policytransportation

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Area of Science:

  • Operations Research
  • Public Health
  • Education Policy

Background:

  • School districts face significant transportation costs, often managing bus fleets to serve multiple schools.
  • Reconciling competing objectives like cost reduction and equitable service is challenging with current ad hoc approaches.
  • Early high school start times are linked to negative health and developmental impacts on students.

Purpose of the Study:

  • To develop an optimization model for the school time selection problem (STSP).
  • To introduce a novel school bus routing algorithm, biobjective routing decomposition (BiRD).
  • To enable school districts to make informed decisions balancing transportation costs and student well-being.

Main Methods:

  • Developed the biobjective routing decomposition (BiRD) algorithm, a novel approach to school bus routing.
  • Leveraged mixed integer optimization to combine subproblem solutions within BiRD.
  • Formulated the STSP as a multiobjective generalized quadratic assignment problem using a cost proxy.

Main Results:

  • BiRD significantly outperforms existing state-of-the-art routing methods.
  • Implementation in Boston resulted in $5 million in annual savings with a reduced bus fleet.
  • Enabled a 50-bus fleet reduction while maintaining service quality.

Conclusions:

  • The BiRD algorithm provides a tractable and effective solution for the STSP.
  • The optimization model allows exploration of tradeoffs between cost, equity, and student health.
  • This research supported Boston's first school start time reform in 30 years, demonstrating practical impact.