Route optimization for school bus scheduling problem based on a distributed ant colony system algorithm

In the present work, we were interested in a distributed architecture for solving the School Bus Dispatching Problem (SBDP). Our objective is to create a path planning to minimize the costs of transportation while meeting several constraints such as the distance traveled by each bus and the capacity of each vehicle. The metaheuristics methods, namely ant colony system algorithm are able to solve a combinatorial problems. A distributed method is presented to solve the school bus routing problem based on an improved ant colony optimization by using a multi-agent system for creating intelligent agents that work together to solve our problem. In this paper, we propose a distributed model based on clustering strategy for creating sub-areas that will produce a clustering of students depending on their address and the stops locations. An improved ant colony system algorithm is implemented for finding the shortest path between the school and the set of students using distributed agents. The preparatory setup shows that the proposed model can be applicable to real cases.