A hybrid GA approach for solving the Dynamic Vehicle Routing Problem with Time Windows

The dynamic vehicle routing problem is an extension of conventional routing problems whose particularities are that information can change after initial routes have been constructed or that not all the information is known when the routing process takes place. The main interest of this type of problem is that it corresponds to many real word applications (repair services, courier mail services, taxi cab services). In this paper, we study the particular case of the dynamic vehicle routing problem with time windows (DVRPTW) in which occurrences of new customers appear over time. We propose an original resolution approach based on a genetic algorithm adapted to this dynamic optimisation context. Taguchi´s tables have been used in order to adjust the parameters of our genetic algorithm. Experimental results based on the modified Solomon benchmarks show the efficacy of our approach as compared to other meta-heuristic approaches