A hybrid genetic algorithm to the vehicle routing problem with fuzzy cost coefficients
A hybrid genetic algorithm to the vehicle routing problem with fuzzy cost coefficients
复制标题
具有模糊成本系数的车辆路径问题的混合遗传算法
DOI：
10.1109/fskd.2014.6980823
复制
发表时间：
2014
期刊：
影响因子：
--
通讯作者：
Jun Yu Li
中科院分区：
文献类型：
--
作者：
Jianyong Zhang;Jun Yu Li
随着市场竞争的加剧和科学技术的快速发展，许多企业已经开始认识到不确定性环境下物流配送车辆路径问题的重要性，并开始重视对该问题的研究。在本文中，传统的确定性车辆路径问题(VRP)是近几十年来运筹学领域研究的重点和难点问题之一。但在许多实践中，由于世界上存在的不确定因素和人的模糊性，车辆路径问题的许多参数都是不确定或模糊的。本文将传统的确定性车辆路径问题扩展到车辆路径问题具有模糊性的情况。本文将车辆路径问题的行程时间作为模糊数来处理。在对具有模糊行程时间的车辆路径问题进行简单描述后，建立了该问题的数学模型。然后，将遗传算法和模糊逻辑方法有效地结合起来，提出了一种求解此类车辆调度问题的混合遗传算法。最后给出了一个算例。
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.