A hybrid genetic algorithm to the vehicle routing problem with fuzzy cost coefficients

With the intensification of market competition and fast development of science and technology, many enterprises have begun to realize the importance of logistic distribution vehicle routing problem under uncertainty environment, and begin to pay more attention to the research of this problem. In this paper, the traditional deterministic vehicle routing problem (VRP) is one of the most important and difficult problems in operational research filed in the past many decades. But in many practices, due to the uncertain factors existed in the world and the fuzziness of human being; many parameters of VRP are uncertain or fuzzy. In this paper, the traditional deterministic VRP is expanded to the situation that the VRP has fuzzy features. The traveling time of the VRP are treated as fuzzy numbers in this paper. After a simple description of the VRP with fuzzy traveling time, a mathematical model for the problem is built. Then, a hybrid genetic algorithm to this kind of vehicle scheduling problem is developed based on the effective combination of the genetic algorithm and fuzzy logistic method. Finally, an example is presented.