A Hybrid Metaheuristic Algorithm for the School Bus Routing Problem with Multi-School Planning Scenarios

In the practice of multi-school bus route planning, the characteristics of the bus fleet and the operation modes of buses have produced a variety of bus planning scenarios. In recent years, many methods have been used to arrange the routes of school buses for the school bus routing problem (SBRP) with a specific planning scenario. However, it is still a challenging task to develop a general-purpose algorithm that can effectively apply to the bus route planning for a variety of bus planning scenarios. This paper tries to develop a hybrid iterated local search (ILS) metaheuristic algorithm for SBRP with multiple planning scenarios, which including homogenous or heterogeneous fleets, single load or mixed load operation modes. Within the framework of ILS, a variety of neighborhood structures are used to improve the initial solution as well as the routes generated in the process of local search are recorded. For heterogeneous SBRP, the fleet adjustment strategy based on route segments is also applied. In addition, the perturbation mechanism and the acceptance of worse solutions within a certain deviation range are adopted to enhance the diversity of solutions. Finally, the local best solution is further promoted by the set partitioning procedure (SP), which is modeled by the history routes in the local search process. The experiment results prove that the proposed algorithm is effective and it also outperforms the existing algorithms for multi-school SBRP.