Multiple vehicle routing with time windows using genetic algorithms

Abstract

We use genetic algorithm to attack the vehicle routing problem with time windows. Previous work has shown that although merge crossover works better than traditional cross operators for this problem, it does poorly on problems with non-random customer locations. We modify the merge crossover operator to achieve better performance on problems with clustered customer locations. Our algorithm optimally solved three out of six benchmark problems and came within 0.23% of the optimal on the rest.