Multi-depot and Multi-school Bus Scheduling Problem with School Bell Time Optimization

Abstract

Public school systems are responsible for transporting students to and from schools safely and promptly. For a multi-school system, given all the bus trips of schools, the school bus scheduling problem aims at developing an efficient schedule of operation for buses to serve all the trips at minimum operation cost while satisfying some necessary constraints. As for school buses, they usually operate from multiple depots and are required to return to the same depot as they started from. However, most existing studies have concentrated on the single-depot school bus scheduling problem, which assumes that all the buses start from the same depot.

This research studies the multi-depot and multi-school bus scheduling problem with school bell time optimization (MDBSPBO) with the goal of minimizing the total number of buses and the total deadhead duration. Spreading bell times, which change the bell times within a reasonable time window, makes more trips become compatible and could reduce the total number of buses. We will develop appropriate models and solution algorithms for this very important real-world problem. We will use real-world data supplied by one of the public school systems in the state of Maryland for testing and evaluation of the model.

Universities and Sponsoring Organizations

University of Maryland

Principal Investigators

Dr. Ali Haghani, University of Maryland; haghani@umd.edu

Funding Sources and Amounts

USDOT ($100,000), UMD ($50,000)

Start Date

11/1/2020

Expected Completion Date

12/31/2021

Expected Research Outcomes

Models and algorithms that could be used to develop school bus routes from multiple depots for any school system

Expected Equity Impacts and Benefits of Implementation

Such models and algorithms, when implemented, result in significant operational cost savings for public school systems and as such benefit both the public and the government.

Subject Areas

Applied operations research