This study investigates a multi-project, multi-period, multi-factory and multi-objective supplier selection problem with project life cycles and demand uncertainty. For this problem, we establish a multi-stage mixed integer stochastic programming model with three objectives (i.e., the procurement cost, number of quality defects and delayed delivery quantity). An adapted chaos optimization algorithm based on a maximum similarity method is developed to solve the model. The effectiveness of our solutions is validated by the real data from the auto industry. The sensitivity analysis indicates that all of the values of the three objectives increase and then decrease with the project life cycle

这项研究调查了一个具有项目生命周期和需求不确定性的多项目，多时期，多工厂，多目标的供应商选择问题。针对这一问题，我们建立了一个具有三个目标（即采购成本，质量缺陷数量和延迟交货数量）的多阶段混合整数随机规划模型。提出了一种基于最大相似度的自适应混沌优化算法来求解模型。我们的解决方案的有效性通过来自汽车行业的真实数据进行了验证。敏感性分析表明，三个目标的所有值都随着项目生命周期的增加而减小