Study Of Vehicle Routing Problem Under Fuzzy Information

With the increasing intensification of market competition, acceleration of global integration, and fast development of science and technology, many enterprises realize that logistic is an important measure to improve the ability of market competition and the ability of coral competition, and introduce advanced logistical theory and logistical technique to manufacture and operation management of enterprise. As an important approach to realize logistic rationalization, research on vehicle routing problems will help enterprises to reduce logistical cost, improve operation efficiency, and enhance customer satisfaction comprehensively. Since vehicle routing problems tightly connect theory of Operations Research with practice of production, which was named as one of the most successful areas in Operations Research in the past decades. In the classical vehicle routing problems, all kinds of information are assumed to be determinated, but in practice, planner of routes always meet with uncertain information, such as fuzzy information. Consequently, effective methods for solving determinated vehicle routing problems cann't solving fuzzy vehicle routing problems effectively. It is necessary to do some research on characteristics of fuzzy vehicle routing problems and to design effective models and algorithms for it. Until now, few researchs have been made on fuzzy vehicle routing problems, and many dissatisfactory items await amelioration and modification. In this dissertation, a series of vehicle routing problems under fuzzy information are analyzed thoroughly.The main contents of this dissertation are as follows:In chapter 1, based on summarizing relative reference, we retrospecte domestic and foreign researchs on vehicle routing problem, point out shortcomings of research on this problem and find some potential areas of research.In chapter 2, analyze models and algorithms of a vehicle routing problem with fuzzy demand (VRPFD). Through introducing the concept of decisionmaker's preference, we set up the fuzzy chance constrain programming model of VRPFD, and put forward two types of computing methods of this problem combined with the traditional heuristics or meta-heuristics. Besides, since decisionmaker's preference has great influenceon the final decision, this chapter analyzes the relationship between the final goals and the preference numbers using stochastic simulated method. Finally, offer the rational range of the preference number.In chapter 3, we research models and algorithms of vehicle routing problems with fuzzy traveling time (VRPFT). On the basis of describing of VRPFT, we propose two methods to solve this problem, they are the modified C-W algorithms and fuzzy reasoning based hybrid genetic algorithm.In chapter 4, vehicle routing problem with fuzzy due time is studied. The traditional vehicle routing problem with time windows (VRPTW) is expanded to the situation that the time window is replaced by fuzzy due time which can represent the preferences of the customers. After a simple description of the fuzzy dial-a-ride problem, a multi-objective mathematical model for the problem is built. Then, an insertion heuristic-based hybrid genetic algorithm is proposed for solving this kind of problem. In this algorithm, the modified push-bump-throw procedure is employed to handle the fuzzy nature of the problem. Finally, an example is presented; the relationship between the different objectives is discussed.In chapter 5, the dynamic vehicle routing problem with one depot from which vehicles depart and to which they return after completing their service is considered. The quantities to be picked up at the nodes are assumed to be only approximately known. This thesis develop a model to design vehicle routing when demand at the nodes is uncertain. The model is based on the heuristic algorithm and the rules of fuzzy arithmetic. Finally, the influence of the decisionmaker's preference on the final objective of the problem is discussed using the method of...