Sushil J. Louis, Xiangying Yin, Zhen Ya Yuan
Genetic Adaptive Systems LAB
Department Of Computer Science/171
University Of Nevada, Reno - 89557
sushil@cs.unr.edu
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. In this paper 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.
Keywords: Genetic Algorithms, merge crossover, vehicle routing problem with time windows