Challenges in Home to School Transport: Large-Scale School Bus Routing inclusive of Special Needs Students and Heterogeneous Fleets in the North West

Lead Research Organisation: University of Manchester
Department Name: Alliance Manchester Business School

Abstract

Planning the routes of school buses to transport children from/to school is a widely studied
problem in the operations research literature (Park & Kim, 2010) with hundreds of papers written
about it. Transporting children is an understandably sensitive topic and the planning of school bus
routing has implications for school policies such as school budget and bell-times (Bertsimas et al.,
2019) and the inclusivity of special-needs students (Caceres et al., 2019). Another reason for this
vast literature is the broad range of possible variants of the problem.
In its most basic form, the goal is to decide when each stop must be visited by each bus, satisfying
requirements about timetables, bus capacity, etc., while trying to minimise the travel time. Real-
world variants, however, are much more complex than this basic form (Caceres et al., 2019;
Ellegood et al., 2020). For example, bus routes should be inclusive of special needs students,
whose time in the bus should be minimised as much as possible and which may require vehicles
with space for wheelchairs or additional seats for personal assistants. In England, bus fleets tend
to be of relatively small capacity and heterogeneous, i.e., with different configurable seats and
wheelchair capacities. In addition, travel-time of the bus itself may not be the most important
criterion, but rather there are a number of conflicting criteria related to the utilisation of the bus's
capacity, the riding time from the point of view of various types of students, the number of buses
required. etc. A further challenge is that school districts in England tend to be large and include
thousands of students, which is beyond what classical mathematical optimisation methods are
able to handle (Riera-Ledesma & Salazar-González, 2013; Schittekat et al., 2013). By using
metaheuristics, Spada et al., (2005) were able to tackle a school district of about 10,000 children.

Publications

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Studentship Projects

Project Reference Relationship Related To Start End Student Name
ES/P000665/1 01/10/2017 30/09/2027
2669222 Studentship ES/P000665/1 01/10/2021 30/09/2024 Ozioma Paul