In order to promote the logistics system,a joint Location-Inventory Problem( LIP) model with lead-time is built,considering disruption risks,stochastic demands,facility capacity constraints. The goal is to minimize system cost and maximize customer satisfaction. A discrete nonlinear mixed integer programming model with 2 goals is built to describe the problem. An improved Non-dominated Sort Genetic Algorithm ( NSGA ) based on niching technology is worked out to solve the model. Numerical example and control experiment indicate that the Pateto front solution set can be obtained and the improved NSGA has obvious advantages compared with standard NSGA. In practical application, optimal decision schemes can be selected from a cluster of Pateto solutions according to the preferences and actual needs of decision makers.%为实现物流系统整体优化，考虑失灵风险、随机需求、设施容量约束、提前期等因素，以系统总成本最小与客户满意度最高为目标，建立一个两级物流网络的随机多目标定位-库存问题模型。该模型是一个双目标的非线性离散混合整数规划模型。在此基础上，设计一种改进的基于小生境技术的非支配排序多目标遗传算法。实验结果表明，该算法可得模型的Pateto前沿解集，与标准非支配排序遗传算法相比，改进算法在收敛代数及解的数量和分布上均具有明显优势。在实际应用中，决策者可根据需要及偏好在Pateto候选解中选择合适的优化决策方案。
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