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作 者:罗浩 李想 吉敏全[1] LUO Hao;LI Xiang;JI Minquan(Qinghai University,Xining 810016,China)
机构地区:[1]青海大学
出 处:《物流科技》2019年第10期45-48,56,共5页Logistics Sci-Tech
基 金:国家自然科学基金项目“基于生态安全的青海三江源地区低碳交通体系构建研究”(71463048)
摘 要:逆向物流的路径优化对降低回收成本具有重要意义,而回收成本直接影响着逆向物流行业的发展。本文针对逆向物流多中心的回收问题,基于共享订单协同回收的回收网络模式,在考虑逆向物流过程中的运输成本以及客户满意度的基础上以油耗和时间惩罚成本最小化为目标建立了车辆回收路径规划模型,并利用量子粒子群算法精度较高和收敛速度较快的优势对模型进行求解。最后通过算例分析证明了模型和算法的可行性和有效性,以期对多回收中心的逆向物流路径规划问题提供理论参考和实践指导。The path optimization of reverse logistics is of great significance to reduce the cost of recycling,and the cost of recycling directly affects the development of the reverse logistics industry.This paper aims at the multi-center recycling of reverse logistics.Based on the recycling network model of shared order collaborative recycling,based on the transportation cost and customer satisfaction in the process of reverse logistics,the vehicle recovery is established with the goal of minimizing fuel consumption and time penalty cost.The path planning model is solved by using the advantages of high precision and fast convergence of quantum particle swarm optimization.Finally,the feasibility and effectiveness of the model and algorithm are proved by a case study,in order to provide theoretical reference and practical guidance for the reverse logistics path planning problem of multiple recycling centers.
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