Decision Support to Product Configuration Considering Component Replenishment Uncertainty: A Stochastic Programming Approach
Decision Support to Product Configuration Considering Component Replenishment Uncertainty: A Stochastic Programming Approach
复制标题
考虑元件补货不确定性的产品配置决策支持：随机规划方法
DOI：
10.1016/j.dss.2017.11.004
复制
发表时间：
2018
影响因子：
7.5
通讯作者：
Bill Wang
中科院分区：
文献类型：
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作者：
Dong Yang;Xiaohong Li;Roger J. Jiao;Bill Wang
产品配置就是在大规模定制生产环境下，对零部件的选择和组合做出决策，从而构成定制产品。然而，现有的产品配置器没有考虑产品配置设置中的不确定性(如部件供应)。针对部件补货提前期的不确定性，利用两阶段随机规划方法，提出了一种新的随机决策模型。此外，还采用了零部件供应的预采购策略，以降低总配置成本并缩短定制产品的交付日期。利用拉格朗日松弛算法对产品配置随机决策模型进行求解。通过计算机配置和护林员钻机配置的实例研究，验证了随机决策模型的有效性。与商业求解器(CPLEX)的计算比较表明，所提出的随机决策模型提供了具有竞争力的解结果。
Product configuration is to make decisions on component selections and combination to constitute a customized product under mass customization production. However, the uncertainties (such as component supplies) in product configuration setting are not considered in the existing product configurators. To handle the uncertainty in component replenishment lead-time, a new stochastic decision model is proposed in this paper using two-stage stochastic programming approach. Further, a pre-procuring strategy for component supply is employed to reduce total configuration costs and shorten the delivery date of customized products. The stochastic decision model for product configuration is solved by using Lagrangian relaxation algorithm. The effectiveness of the stochastic decision model is demonstrated through case studies from both computer configuration and ranger drilling machine configuration. Computational comparisons with a commercial solver (CPLEX) indicate that the proposed stochastic decision model provides competitive solution results.