The school bus routing problem (SBRP) is a central issue in
transportation planning and optimization systems. SBRP seeks to
plan an efficient schedule for a fleet of school buses where each
bus picks up students from various bus stops and delivers them to
their designated schools while satisfying various constraints such
as the bus capacity. Due to its complexity, many heuristics have
been proposed to solve this combinatorial problem in an effective
way. In this book, geographic information systems (GIS)-based
decision-making framework that combines GIS, clustering techniques,
network cutting techniques, and a hybrid ant colony optimization
metaheuristic with the iterated Lin-Kernighan local improvement
heuristic is proposed for solving the SBRP as a split delivery
vehicle routing problem (SDVRP). Experiments were conducted for
evaluating the proposed framework by comparing the results from it
and Arc-GIS 9.2 Network Analyst which uses the greedy Dijkstra's
algorithm. The reported results of the proposed framework generally
outperform that of the ArcGIS. IIn addition, the proposed
decision-making framework was applied to solve a real life SBRP to
demonstrate its application.
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