AN ANT COLONY OPTIMIZATION METHOD FOR FUZZY VEHILCLE ROUTING PROBLEM

摘要

This paper deals with the vehicle routing problem involved with fuzzy/imprecise vehicle travel times and customer service times, these fuzzy/imprecise times are represented as fuzzy numbers and interpreted as possibility distributions. According to the same consideration as the stochastic programming with recourse, the influence of the fuzziness of travel times and service times is treated as recourse cost through two-stage decisions and a two-stage possibilistic programming model is formulated. By choosing an appropriate definition of Fuzzy Mean, it can be showed that the proposed model is equivalent to an ordinary programming problem and then a solution method based on Ant Colony System (ACS) is proposed to give the best solution of the problem. Finally, some examples are given to illustrate the twostage model and the solution algorithm.