动态车辆路径问题实时优化策略构建的一般方法

Hao Xiong, Huili Yan
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引用次数: 0

摘要

目前,针对动态需求车辆路径问题的策略大多是基于静态问题的传统方法,没有针对动态需求情况构建实时优化策略的通用方法。在此基础上,提出了一种基于静态子问题规则组合构建实时优化策略的新方法。实时优化策略是将动态问题沿时间轴分解为一系列静态子问题,然后求解静态子问题。静态子问题的转换和求解规则包括:划分规则、批处理规则、目标规则、动作规则和算法规则等。这些规则的不同组合可能构成各种实时优化策略。在此基础上,提出了柔性G/G/m政策和柔性D/G/m政策。对这两种政策的竞争分析和仿真结果证明,这两种政策都是对现有最佳政策的改进。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
General Method of Building a Real-Time Optimization Policy for Dynamic Vehicle Routing Problem
Abstract Currently, most of the policies for the dynamic demand vehicle routing problem are based on the traditional method for static problems as there is no general method for constructing a real-time optimization policy for the case of dynamic demand. Here, a new approach based on a combination of the rules from the static sub-problem to building real-time optimization policy is proposed. Real-time optimization policy is dividing the dynamic problem into a series of static sub-problems along the time axis and then solving the static ones. The static sub-problems’ transformation and solution rules include: Division rule, batch rule, objective rule, action rule and algorithm rule, and so on. Different combinations of these rules may constitute a variety of real-time optimization policy. According to this general method, two new policies called flexible G/G/m and flexible D/G/m were developed. The competitive analysis and the simulation results of these two policies proved that both are improvements upon the best existing policy.
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