用进化变邻域搜索算法求解闭合供应链选址问题

针对逆向物流依赖于物流网络的合理规划与设计，提出选址问题，通过分析闭合供应链规划设计中的选址定位，建立了相应的数学模犁。模型中正向物流和逆向物流共享运输网络，把需求量作为随机变量处理，以供应链的总运营成本作为优化目标，为解决闭合供应链选址这个NP难题，提出了种基于进化策略的变邻域搜索算法。通过设计基于多个算例的仿真试验表明：所建立数学模型和所提出算法是有效的。

Application of evolutionary variable neighborhood search algorithm to location-allocation problem in close-loop supply chain

Location-allocation problem is one of the important decision problems in designing logistic network. The complexity of reverse logistic makes the operation of close-loop supply chain more dependent on logistic network, so the location-allocation problem is the most important problem in the close-loop supply chain management. The Location-allocation problem in designing close-loop supply chain is analyzed in this paper at first, and then the mathematical model of location-allocation problem in close-loop supply chain is formulated. In the model the logistic network is shared by normal logistic and reverse logistic, and the requirement is considered as stochastic variable. The objective of the model is to optimize the total cost of supply chain. Because the formulated model is NP-hard, variable neighborhood search algorithm with the feature of population-based evolution is designed to solve the problem. Simulation based on several numerical examples shows that the proposed mathematical model and the algorithm are effective.