基于混合算法的不确定环境下逆向物流网络设计研究

Research on Reverse Logistics Network Design in Uncertain Environment Based on Hybrid Algorithm

针对不确定环境下的逆向物流网络容易产生较高成本的问题，结合当前已有的物流设施节点，提出充分考虑固定投资、物流成本、库存成本和回收量不确定的设施选址规划模型，利用遗传算法和贪婪算法相结合的混合算法对设施选址、回收区域划分和回收间隔期进行求解。以某汽车零部件企业为实际案例，验证了模型和混合算法的可行性和正确性。

A facility planning model that takes into account the fixed investment, logistics cost, inventory cost and recycling uncertainty was proposed. Combined with the current logistics facilities node, a facility site selection planning mode was proposed taking fixed investment, logistics costs,inventory cost and uncertain recycling quantity into full considerattion to solve the problem that reverse logistics network easily results in higher cost under uncertain conditions. A hybrid algorithm integrating genetic algorithm with greedy algorithm was put forward to select facility sites, divide recycling area and to calculate the recovery interval. The feasibility and correctness of the model and the algorithm were verified by a case study of an auto parts enterprise.