Abstract

Traveling to school is a complex undertaking that refers to students’ daily trips from their residences to their schools and vice versa. The school bus routing problem differs from a conventional vehicle routing problem because it involves a procedure of receiving and delivering transported vulnerable objects (students). In the Greek school transportation system, this procedure is executed in complex transport networks, following a series of routes formulated with an empirical approach; not a mathematical model. Many schools design these routes by using a manual process, taking into account primarily the parents’ requirements. However, the complexities of school bus routing problems, such as local conditions, operating costs, and customer needs, make the whole procedure extremely challenging and render the adoption of a software solution a necessity. Considering this framework, this paper presents a seven-step method developed for optimizing the school bus routes of a private school in Thessaloniki, Greece. The method is based on cluster analysis and genetic algorithms while taking into account the geographic characteristics of the road network as well as the distribution of the student’s travel behavior and requirements. The results derived from the pilot testing verify initial considerations: reducing the distance and travel time by optimizing school bus routing lessens the possibility for students to be involved in road accidents and enhances the air quality through a reduction in fuel emissions.

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