有容量约束的随机多目标LIP模型及其求解算法  

Stochastic Multi-objective LIP Model with Capacity Constraint and Its Solving Algorithm

作　　者：周愉峰[1] 李志[1] 

机构地区：[1]重庆工商大学重庆市发展信息管理工程技术研究中心,重庆400067

出　　处：《计算机工程》2014年第11期183-188,共6页Computer Engineering

基　　金：国家科技支撑计划基金资助重大项目(2006BAH02A20);国家社会科学基金资助项目(10XGL013);重庆市科技攻关计划基金资助重大项目(CSTC2012gg C00002);重庆市科技攻关计划基金资助重点项目(CSTC;2010AB2102;CSTC;2008AB2084)

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。Based on the characteristics of logistic network design problem of some special materials,a joint Location-inventory 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.

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 

分 类 号：TP399[自动化与计算机技术—计算机应用技术]