基于驴与走私者算法的物流配送车辆路径优化研究  

VEHICLE ROUTING OPTIMIZATION OF LOGISTICS DISTRIBUTION BASED ON DONKEY AND SMUGGLER OPTIMIZATION ALGORITHM

作　　者：王迪 金辉[1] Wang Di;Jin Hui(School of Automotive and Traffic Engineering,Liaoning University of Technology,Jinzhou 121001,Liaoning,China)

机构地区：[1]辽宁工业大学汽车与交通工程学院,辽宁锦州121001

出　　处：《计算机应用与软件》2020年第5期281-286,297,共7页Computer Applications and Software

基　　金：2017年辽宁省教育厅重大科技平台科技项目(JP2017009)。

摘　　要：物流车辆配送路径优化(VRP)是提高物流配送效率和降低物流配送成本的重要途径,作为物流运输系统的核心内容,运用智能算法求解VRP问题可以有效地求出近似最优解。驴和走私者算法(Donkey and Smuggle Optimization Algorithm,DSO)是受驴的搜索行为启发,通过模拟驴的运输行为,建立两种模式来实现算法中的搜索行为和路径选择。走私者通过查找所有可能路径,然后确定最佳路径;求出的最优路径的适应性发生变化的情况下,利用驴的多种行为求解次优解。因此建立基于驴与走私者算法的物流配送车辆路径优化模型,通过实例研究并与蚁群算法(ACO)进行求解比较。结果表明,与ACO相比,DSO可以在更短的时间内提供更多和稳定的选项。Logistics vehicle distribution path optimization(VRP)is an important way to improve the efficiency of logistics distribution and reduce the cost of logistics distribution.As the core content of the logistics transportation system,using intelligent algorithms to solve the VRP problem can effectively obtain approximate optimal solutions.Donkey and smuggler optimization algorithm(DSO)is inspired by the search behavior of the donkey.By simulating the donkey s transportation behavior,two models are established to realize the search behavior and path selection in the algorithm.The smugglers search for all possible paths and then determine the best path.And the various behaviors of the donkey are used to solve the suboptimal solution when the adaptability of the obtained optimal path changes.Therefore,we established a logistics distribution vehicle routing optimization model based on donkey and smuggler optimization algorithm.The case studies were performed and compared with ant colony optimization(ACO).The results show that compared with ACO,DSO can provide more and stable options in a shorter time.

关 键 词：驴和走私者算法 路径优化 VRP ACO算法 驴 走私者 

分 类 号：TP3[自动化与计算机技术—计算机科学与技术]