Bus Routing Optimization Helps Boston Public Schools Design Better Policies

Dimitris Bertsimas (), Arthur Delarue (), William Eger (), John Hanlon () and Sebastien Martin ()
Additional contact information
Dimitris Bertsimas: Operations Research Center, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139;
Arthur Delarue: Operations Research Center, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139;
William Eger: Boston Public Schools, Roxbury, Massachusetts 02119
John Hanlon: Boston Public Schools, Roxbury, Massachusetts 02119
Sebastien Martin: Operations Research Center, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139;

Interfaces, 2020, vol. 50, issue 1, 37-49

Abstract: In the winter of 2016, Boston Public Schools (BPS) launched a crowdsourcing national competition to create a better way to construct bus routes to improve efficiency, deepen the ability to model policy changes, and realign school start times. The winning team came from the Massachusetts Institute of Technology (MIT). The team developed an algorithm to construct school bus routes by assigning students to stops, combining stops into routes, and optimally assigning vehicles to routes. BPS has used this algorithm for two years running; in the summer of 2017, its use led to a 7% reduction in the BPS bus fleet. Bus routing optimization also gives BPS the unprecedented ability to understand the financial impact of new policies that affect transportation. In particular, the MIT research team developed a new mathematical model to select start times for all schools in the district in a way that considers transportation. Using this methodology, BPS proposed a solution that would have saved an additional $12 million annually and also shifted students to more developmentally appropriate school start times (e.g., by reducing the number of high school students starting before 8:00 a.m. from 74% to 6% and the average number of elementary school students dismissed after 4:00 p.m. from 33% to 15%). However, 85% of the schools’ start times would have been changed, with a median change of one hour. This magnitude of change led to strong vocal opposition from some school communities that would have been affected negatively; therefore, BPS did not implement the plan.

Keywords: optimization; transportation; routing; scheduling; education; public policy (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

Downloads: (external link)
https://doi.org/10.1287/inte.2019.1015 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:inm:orinte:v:50:y:2020:i:1:p:37-49

Access Statistics for this article

More articles in Interfaces from INFORMS Contact information at EDIRC.
Bibliographic data for series maintained by Chris Asher ().