A novel GIS-based decision-making framework for the school bus routing problem

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 maximum capacity of a bus, and the time window of a school. Due to its inherent complexity, many heuristics have been proposed to solve this combinatorial problem in an effective way. In this paper, a novel 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 for solving 11 routing problems using both the proposed decision-making framework and ArcGIS 9.2 Network Analyst which uses the greedy Dijkstra’s algorithm. The reported results of the proposed framework generally outperform that of the ArcGIS Network Analyst. In addition, the proposed decision-making framework was applied to solve a real life SBRP to demonstrate its application.