摘要： 针对某些特殊物资的物流网络设计问题,以系统总成本最小与系统实时性程度最高为目标,建立一个考虑 随机需求、设施容量约束、客户时限约束、带提前期的选址-库存问题(LIP)模型。该模型被描述为一个双目标的非 线性离散混合整数规划模型。针对该模型,基于小生境技术设计一种改进的非支配排序多目标遗传算法Π(NSGAΠ),以丰富非支配解的数量。算例与对照实验结果表明,NAGAΠ 可得模型的Pateto 前沿解集,与标准 NSGAII 相比具有明显的优势,该模型及算法可应用于血站或者某些应急药品仓库的选址布局与库存决策。决策者可根据实际需要及偏好在一簇Pateto 解中选择合适的优化决策方案。

关键词: 选址-库存问题, 设施选址, 库存控制, 多目标优化, 非支配排序遗传算法Π, 混合整数规划

Abstract: Based on the characteristics of logistic network design problem of some special materials,a joint Locationinventory Problem(LIP) model with lead-time is built,considering stochastic demands,facility capacity constraints and the client time constraints. The goal is to minimize system cost and maximize system timeliness. A discrete nonlinear mixed integer programming model with 2 goals is built to describe the problem. An improved NSGAII based on niching technology is worked out to solve the model,in order to enrich the number of non-dominated solutions. Numerical example and control experiment indicate that the Pateto front solution set can be obtained and the improved NSGAII has obvious advantages compared with standard NSGAII. The model and algorithm can be used to make location and inventory decision of blood banks or other emergency medicine warehouses. And optimal decision schemes can be selected from a cluster of Pateto solutions according to the preferences and actual needs of decision makers.

Key words: Location-inventory Problem(LIP), facility location, inventory control, multi-objective optimization, Nodominated Sort Genetic Algorithm II(NSGAII), mixed integer programming

中图分类号: 

• TP399