摘要
基于有向图对物流网络多层级设施选址-路径规划问题,建立混合整数规划数学模型,提出量子进化算法与遗传算法协同的双智能算法集成求解方案.量子进化算法解决设施选址和设施分配,遗传算法进行路径规划,并提出可达配送区域的搜索策略和路径长度为权重的设施分配优化策略以提高算法效率.实例测试表明,所提出的数学模型和组合智能算法是可行而有效的,可为多层级设施选址-路径规划问题提供理论与方法指导.
Aiming at the multi-echelon location-routing problem（ME-LRP） based on the directed graph theory, a systematic model is built up, and a combination intelligent algorithm of the quantum-inspired evolutionary algorithm（QEA） and genetic algorithm（GA） is applied to solve it. The QEA is applied to solve the facility location problem（FLP） and facility allocation problem（FAP）, and the GA is applied to solve the vehicle routing problem（VRP）.In order to improve the efficiency of the algorithm, the searching strategy based on the reachable distribution region and the facility allocation strategy based on path length are proposed. The results from the testing example shows that, the proposed ME-LRP mathematical model and the combined intelligent algorithm are feasible and effective, which provide the oretical and methodical guidance for the ME-LRP.
作者
黄凯明
卢才武
连民杰
HUANG Kai-ming LU Cai-wu LIAN Min-jie(School of Management, Xi＇an University of Architecture and Technology, Xi＇an 710055, China School of Business Administration, Jimei University, Xiamen 361021, China Sinosteel Mining Co Ltd, Beijing 100080, China)
出处
《控制与决策》
EI
CSCD
北大核心
2017年第10期1803-1809,共7页
Control and Decision
基金
陕西省重点学科建设专项基金项目(E08001)
陕西省自然科学基金项目(2011JQ7016)
陕西省社会科学基金项目(2016R014)
关键词
多层级设施选址-路径规划问题
建模
量子进化算法
遗传算法
multi-echelon location-routing problem
modeling
quantum-inspired evolutionary algorithm
genetic algorithm
