Early supplier involvement in new product development is strategically important for the success of most firms. We therefore discuss how to configure an appropriate supply chain network for new product development. First, we propose a supply chain configuration model under a multi-objective optimization framework. We then develop a solution procedure based on a multi-objective evolutionary algorithm, i.e. NSGA-II (Non-Sorting Genetic Algorithm-II), to minimize the total supply chain cost and time-to-market. The efficiency of the proposed solution procedure is discussed along with a laptop assembly case study. The results obtained from NSGA-II are also compared from SPEA-II (Strength Pareto Evolutionary Algorithm-II).

供应商及早参与新产品开发对大多数公司的成功具有重要的战略意义。因此，我们讨论了如何为新产品开发配置适当的供应链网络。首先，我们提出了一个多目标优化框架下的供应链配置模型。然后，我们基于多目标进化算法（即NSGA-II（非排序遗传算法-II））开发解决方案程序，以最大程度地减少总供应链成本和缩短产品上市时间。与笔记本电脑组装案例研究一起讨论了提出的解决方案的效率。从NSGA-II获得的结果也与SPEA-II（强度帕累托进化算法-II）进行了比较。