Darwin meets computers: new approach to multiple depot capacitated vehicle routing problem

We present a study of using genetic algorithms (GAs) to solve non-fixed destination multiple-depot capacitated vehicle routing problem. The genetic algorithm was developed on the basis of experiences in solving the travelling salesman problem and the single depot capacitated vehicle routing problem. Heuristic improvements in population initialization and crossover operators are made to prevent converging to local optima and to reduce the search space domain. To deal effectively with the constraints of the problem, and to prune the search space of GA in advance, the difficult capacity and supply reliability constraints are embedded in the decimal strings that are coded to represent the vehicle routes between depots. Computational results carried out on several instances indicate that the total distance travelled can be reduced significantly when such method is used.