基于改进蚁群算法的物流配送问题研究

Yimin Xiao, Li-min Xiao, F. Yu, Xiaoping Xu
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引用次数: 0

摘要

本文描述了带时间窗口的物流配送车辆路线优化调度问题,并给出了数学模型。在极大极小蚁群算法的基础上,提出了一种改进的蚁群算法。通过引入信息水分的概念,在构建物流配送路线优化问题的初始解、路线优化、传递规则、信息素更新方式、算法终止判断等方面进行了改进,用与算法运行过程相关的信息水分值来表示选择过程中的不确定性;从而控制路径选择的概率和局部随机变异干扰,从而实现算法的自适应调整。同时,结合局部优化方法对解进行了两次优化。通过这些改进,提高了算法的搜索效率,实验仿真表明了改进算法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research on Logistics Distribution Problem Based on Improved Ant Colony Algorithm
This paper describes the logistics distribution vehicle routing optimization scheduling problem with time window, and gives the mathematical model. Based on the maximum minimum ant colony algorithm, an improved ant colony algorithm is proposed. It is improved in the construction of the initial solution of the logistics distribution routing optimization problem, routing optimization, transfer rules, pheromone update mode, algorithm termination judgment, etc. by introducing the concept of information moisture, The value of information moisture related to the operation process of the algorithm is used to represent the uncertainty in the selection process, so as to control the probability of path selection and local random variation disturbance, so as to realize the adaptive adjustment of the algorithm. At the same time, the solution is optimized twice in combination with the local optimization method. Through these improvements, the search efficiency of the algorithm is improved, and the experimental simulation shows the effectiveness of the improved algorithm.
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