随机与动态环境下物流配送区域划分与配送路径集成优化问题研究

The districting problem and the routing problem are the two core problems in the logistics. To our best knowledge, there exists very limited related works on the integrated optimization on these two problems, called as the "districting-routing" problem, especially under the uncertain environment. This project focusses on the districting-routing problems, considering the stochastic customers and the dynamic customers respectively. It extends the problems by adding the route duration limit and setting the multi-depots, and develops a hyrid algorithm which combines the benders decomposition and the heuristic search for the problem solving. At the end, the models and the algorithms are applied to the planning of the city express logistics and the design of the military maintenance support network system. The target of this project is to provide the decision support for the planning of city logistics system and the design of the military maintenance support network system, through the accurate modelling of the districting-routing problems under uncertain envoirments and the effective solution of the problems. It provides the significance of theoretical investigation and the great value of practical application.

配送区域划分与配送路径优化是物流研究领域里两个关键的研究问题，目前针对这两个问题的集成优化研究比较有限，特别是在不确定环境下。本项目分别考虑随机顾客和动态顾客情况下，对配送区域划分与配送路径集成优化开展研究，并进行工作时间限制以及多配送中心设置的集成优化问题扩展研究。针对集成优化问题设计融合Benders decomposition分解和启发式搜索的混合式算法进行高效求解。最后在城市快递物流系统规划以及军事维修保障网络系统设计上进行应用验证。本项目旨在通过研究，对相关不确定环境下的配送区域划分与配送路径集成优化问题准确建模并高效求解，为城市物流系统规划和军事维修保障网络系统设计提供决策支持，其具有重要的理论探索研究意义及实际应用价值。

物流系统是一个复杂的网络系统，配送路径优化和配送区域划分研究作为其研究的重要组成部分和核心关注点，无论是在国民经济生活中还是在军事战争领域里都有着重要的理论意义和实用价值。.项目研究，首先归纳了在物流配送路径优化和物流配送区域划分领域上的国内外研究现状，并总结了研究所存在的问题；针对存在随机客户情况下的物流配送区域划分与配送路径集成优化问题，建立了数学模型，提出了一种大邻域搜索算法进行求解，并在修改Solomon示例集和修改Gehring & Homberge示例集上进行了实验验证与分析；研究了考虑多周期动态客户与多仓库点情况下的物流配送区域划分与配送路径集成优化问题，设计了一种自适应大邻域启发式搜索算法对问题进行求解，并进行了实验验证分析；针对同时存在动态客户和随机客户情况下的物流配送区域划分与配送路径集成多目标优化问题，定义了相关数学模型，设计了一种考虑约束配对策略的基于偏好的协同多目标进化算法，在随机生成的测试示例集上对提出算法进行了对比与分析，验证了算法的有效性和先进性。