An improved evolutionary algorithm for dynamic vehicle routing problem with time windows

The dynamic vehicle routing problem is one of the most challenging combinatorial optimization tasks. The interest in this problem is motivated by its practical relevance as well as by its considerable difficulty. We present an approach to search for best routes in dynamic network. We propose a dynamic route evaluation model for modeling the responses of vehicles to changing traffic information, a modified Dijkstra's double bucket algorithm for finding the real-time shortest paths, and an improved evolutionary algorithm for searching the best vehicle routes in dynamic network. The proposed approach has been evaluated by simulation experiment using DVRPSIM. It has been found that the proposed approach quite efficient in finding real-time best vehicle routes where the customer nodes and network information changes dynamically.