Modular Supply chain optimization considering demand uncertainty to manage risk
Modular Supply chain optimization considering demand uncertainty to manage risk
复制标题
考虑需求不确定性的模块化供应链优化以管理风险
DOI：
10.1002/aic.17367
复制
发表时间：
2021
期刊：
影响因子：
3.7
通讯作者：
M. Ierapetritou
中科院分区：
文献类型：
--
作者：
Atharv Bhosekar;Oluwadare Badejo;M. Ierapetritou
由于现代市场的竞争加剧和市场波动，需求不确定性下的供应链一直是一个具有挑战性的问题。规划决策的灵活性使模块化制造成为解决这一问题的有希望的方法。在这项工作中，考虑了需求不确定性下的多周期流程和供应链网络设计问题。混合整数两阶段随机规划问题由表示流程设计的整数变量和表示供应链中物料流的连续变量组成。该问题是使用滚动范围方法解决的。 Benders分解用于降低优化问题的计算复杂度。为了促进规避风险的决策，模型中纳入了下行风险衡量指标。结果证明了模块化设计在满足产品需求方面的多项优势。获得了最小化预期成本和下行风险目标的帕累托最优曲线。
Supply chain under demand uncertainty has been a challenging problem due to increased competition and market volatility in modern markets. Flexibility in planning decisions makes modular manufacturing a promising way to address this problem. In this work, the problem of multiperiod process and supply chain network design is considered under demand uncertainty. A mixed integer two‐stage stochastic programming problem is formulated with integer variables indicating the process design and continuous variables to represent the material flow in the supply chain. The problem is solved using a rolling horizon approach. Benders decomposition is used to reduce the computational complexity of the optimization problem. To promote risk‐averse decisions, a downside risk measure is incorporated in the model. The results demonstrate the several advantages of modular designs in meeting product demands. A pareto‐optimal curve for minimizing the objectives of expected cost and downside risk is obtained.