Genetic algorithm with pareto front selection for multi-criteria optimization of multi-depots and multi- vehicle pickup and delivery problems with time windows

In this paper, multi-vehicle and multi-depots pickup and delivery problem with time windows (m-MDPDPTW) is presented as a multi-objective problem. The main contribution is to develop a new encoding and structure algorithm for multicriteria optimization approach using genetic algorithm with Pareto dominance method and elitist selection strategy for replacement. In our problem each request has to be transported by one of the vehicles between paired pickup and delivery locations. Such that, the depot does not contain the goods. We has assumed that all vehicles have the same capacity and each one start and finish route at the same depot. A set of satisfying solutions is given representing the shortest, quickest or cheapest set of routes assigned to a fleet of vehicles which satisfies all customer demand without contravening any of the instance specific constraints (precedence, capacity and time window constraints). These optimal solutions minimize total travel distance, total tardiness time and vehicles number.