Application of Genetic Algorithm in Vehicle Routing Problem with Stochastic Demands

The paper considered a version of vehicle routing problem where customers´ demands were stochastic, and was applied in traffic and communication, manufacture and control, integrated circuit design extensively. Assuming that actual demand was revealed only upon arrival of a vehicle at the location of each customer, and the demand could not be partitioned, the goal consisted of minimizing the expected distance traveled in order to meet all customers´ demands. Firstly, two prior policies, tour policy and multi-tour policy were provided, and their asymptotic properties were analyzed. To find the prior solution of tour policy and multi-tour policy, genetic algorithms with different neighborhood structures were designed. Experiments demonstrated validity of tour policy and multi-tour policy, and showed superiority of genetic algorithm with combined neighborhood