模糊信息条件下车辆路径问题研究
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摘要
随着市场竞争的日益加剧、世界经济一体化进程的加快和科学技术的飞速发展，许多企业已经把物流作为提高市场竞争能力和提升核心竞争能力的重要手段，将先进的物流理论和物流技术引入企业的生产和经营管理中。作为实现物流合理化的重要内容和手段，研究车辆路径有助于企业降低物流成本，提高运作效率，全面提高顾客满意度。由于车辆路径问题将运筹学理论与生产实践紧密地结合在一起，近几十年取得了很多成果，因此被称为“最近几十年运筹学领域最成功的研究之一”。以往对车辆路径问题的研究多是基于确定性信息，而在实际中出现在路径制定者面前的往往是一些非确定性信息，如模糊信息等，研究确定性车辆路径问题的有效方法不一定能有效解决模糊车辆路径问题，因此有必要研究模糊车辆路径问题的特征，构造有效的模型和算法。但到目前为止，对模糊性信息条件下车辆路径问题的研究仍然很少，许多不尽人意的地方有待于进一步完善和改进。本文较深入地研究了模糊性信息条件下的一系列车辆路径问题。
论文的主要研究内容如下：
第1章在对大量相关文献进行总结提炼的基础上，分别回顾了国内、外对车辆路径问题的研究成果，并指出了目前车辆路径问题研究中存在的不足和潜在的研究领域。
第2章，研究了模糊需求信息条件下的VRP(VRPFD)。通过引入决策者主观偏好的概念，建立了VRPFD的模糊机会约束规划模型，结合传统VRP的启发式、亚启发式算法，分别给出了VRPFD的两种计算方法。同时，由于决策者主观偏好值的选取对最终决策结果有巨大影响，通过随机试验方法研究了决策者主观偏好值对最终决策目标的影响，给出了决策者主观偏好值选取的合理范围。
第3章，在对具有模糊旅行时间的VRP进行描述的基础上，通过对传统VRP的C-W节约算法进行修正和引入模糊数学中模糊推理的概念，提出求解VRPFT的两种启发式算法——修正的C-W节约算法和基于模糊逻辑的混合遗传算法。
第4章，具有模糊预约时间的VRP研究。对传统带有时间窗的VRP进行拓展，运用模糊预约时间的概念代替传统的时间窗概念，研究了具有模糊预约时间的多对多货物收发情况下的车辆路径问题，并提出解决该问
第11页西南交通大学博士研究生学位论文
题的一种混合遗传算法。
第5章，研究了模糊需求信息条件下的单车场单车辆动态VRP，通过
对前面VRPFD研究的进一步扩展，研究了在车辆运行过程中信息会实时
变化的动态VRPFD(DVRPFD)，提出了决策者主观偏好值P’给定条件下
求解该问题的一种基于模糊可能性的动态启发式算法。并同样运用随机模
拟方法研究了决策者主观偏好值的选取对最终车辆路径安排的影响，给出
了其最佳取值范围。
第6章，研究了具有模糊预约时间的动态VRP。设计了用来处理该问
题的模糊特征，以及用来确定车辆的最适宜服务时间的双向推一碰过程，
并在此基础上提出了解决该问题的一种插入启发式算法。
结论部分指出论文的主要创新之处，并对未来研究加以展望。
关键词:车辆路径问题;模糊性;启发式算法;遗传算法;动态
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 influence
on 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
论文的主要研究内容如下：
第1章在对大量相关文献进行总结提炼的基础上，分别回顾了国内、外对车辆路径问题的研究成果，并指出了目前车辆路径问题研究中存在的不足和潜在的研究领域。
第2章，研究了模糊需求信息条件下的VRP(VRPFD)。通过引入决策者主观偏好的概念，建立了VRPFD的模糊机会约束规划模型，结合传统VRP的启发式、亚启发式算法，分别给出了VRPFD的两种计算方法。同时，由于决策者主观偏好值的选取对最终决策结果有巨大影响，通过随机试验方法研究了决策者主观偏好值对最终决策目标的影响，给出了决策者主观偏好值选取的合理范围。
第3章，在对具有模糊旅行时间的VRP进行描述的基础上，通过对传统VRP的C-W节约算法进行修正和引入模糊数学中模糊推理的概念，提出求解VRPFT的两种启发式算法——修正的C-W节约算法和基于模糊逻辑的混合遗传算法。
第4章，具有模糊预约时间的VRP研究。对传统带有时间窗的VRP进行拓展，运用模糊预约时间的概念代替传统的时间窗概念，研究了具有模糊预约时间的多对多货物收发情况下的车辆路径问题，并提出解决该问
第11页西南交通大学博士研究生学位论文
题的一种混合遗传算法。
第5章，研究了模糊需求信息条件下的单车场单车辆动态VRP，通过
对前面VRPFD研究的进一步扩展，研究了在车辆运行过程中信息会实时
变化的动态VRPFD(DVRPFD)，提出了决策者主观偏好值P’给定条件下
求解该问题的一种基于模糊可能性的动态启发式算法。并同样运用随机模
拟方法研究了决策者主观偏好值的选取对最终车辆路径安排的影响，给出
了其最佳取值范围。
第6章，研究了具有模糊预约时间的动态VRP。设计了用来处理该问
题的模糊特征，以及用来确定车辆的最适宜服务时间的双向推一碰过程，
并在此基础上提出了解决该问题的一种插入启发式算法。
结论部分指出论文的主要创新之处，并对未来研究加以展望。
关键词:车辆路径问题;模糊性;启发式算法;遗传算法;动态
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 influence
on 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
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