CVAR公司
模棱两可
数学优化
稳健优化
整数规划
选择(遗传算法)
预期短缺
计算机科学
线性规划
集合(抽象数据类型)
供应链管理
运筹学
供应链
风险管理
数学
经济
人工智能
管理
程序设计语言
法学
政治学
作者
Yuqiang Feng,Yanju Chen,Baoding Liu
标识
DOI:10.1080/00207543.2022.2127963
摘要
This paper studies the supplier selection and order allocation (SS&OA) problem, where risks include a series of disruption scenarios with uncertain probability of occurrence. It is a challenge for industry decision-makers to balance the average cost and the level of risk under the ambiguity set for probabilities. To address this challenge, a two-stage distributionally robust (DR) Mean-CVaR model is presented for the SS&OA problem. A procedure is developed for constructing the ambiguity set, and Polyhedral and Box ambiguity sets are constructed to characterise the uncertain probabilities. The worst-case Mean-CVaR criterion is employed for the second-stage cost within the ambiguity set to trade off the expected cost and CVaR value. Three measures are incorporated to increase the resilience of the supply chain. The proposed robust model is reformulated into two mixed-integer linear programming models. A real case of the Huawei cell phone manufacturer is used to illustrate the validity of the proposed approach in numerical settings. Experimental results show that the new optimising approach can provide a robust SS&OA solution to immunise against the influence caused by uncertain probabilities. By comparative analyses, some management insights are obtained for industry decision-makers.
科研通智能强力驱动
Strongly Powered by AbleSci AI