第四方物流多目标路径集成优化  

Integrated Optimization of Multi-Objective Routing Problem in Fourth Party Logistics

作　　者：任亮[1,2] 黄敏 王洪峰[1] 王兴伟[1] REN Liang;HUANG Min;WANG Hongfeng;WANG Xingwei(College of Information Science and Engineering,Northeastern University,State Key Laboratory of Synthetical Automation for Process Industries,Shenyang 110819,China;Evergrande School of Management,Wuhan University of Science and Technology,Wuhan,430081,China)

机构地区：[1]东北大学信息科学与工程学院流程工业综合自动化国家重点实验室,沈阳110819 [2]武汉科技大学恒大管理学院,武汉430081

出　　处：《复杂系统与复杂性科学》2018年第1期62-67,共6页Complex Systems and Complexity Science

基　　金：国家杰出青年科学基金(71325002);国家自然科学基金重点国际合作研究项目(71620107003);国家自然科学基金创新研究群体项目(61621004);流程工业综合自动化国家重点实验室基础科研业务费(2013ZCX11);湖北省教育厅科学技术研究项目(Q20171104);武汉科技大学2017年青年科技骨干培养计划资助项目(2017xz031);武汉科技大学服务科学与工程研究中心开放基金(CSSE2017GB01)

摘　　要：路径问题是第四方物流优化中的关键问题。针对第四方物流实践中需求的特点,基于路径选择和供应商选择的综合优化,提出第四方物流多目标路径集成优化问题,并建立以费用最小和时间最短为双目标的数学模型。进而,设计实现基本蚁群算法和动态调整选择策略的改进蚁群算法的求解方法。实验分析表明,在不同的目标偏好情形下,改进算法均能取得较好效果。研究为第四方物流路径集成优化提供了有效的工具。Routing problem is a key issue of the fourth party logistics.According to characteristics of practice and integrated optimization of routes selection and suppliers selection,integrated optimization of multi-objective routing problem in fourth party logistics is proposed.Double-objective model is established to minimize the total cost and time.Then,a basic ant colony algorithm and an improved ant colony algorithm with dynamic transition probability are used to solve the model.Experimental analysis shows that the improved algorithm can always obtain good solutions in case of different target preferences.The study provides an effective tool for the integrated optimization of fourth party logistics routing problems.

关 键 词：第四方物流 多目标问题 路径问题 蚁群算法 

分 类 号：TP29[自动化与计算机技术—检测技术与自动化装置]