文献类型：期刊文献

英文题名：Incorporating risk aversion and fairness considerations into procurement and distribution decisions in a supply chain

作者：Tao, Jin[1,2];Shao, Lusheng[3];Guan, Zhimin[1];Ho, William[3];Talluri, Srinivas[4]

第一作者：Tao, Jin

通讯作者：Guan, ZM[1]

机构：[1]Northeastern Univ, Sch Business Adm, Shenyang, Liaoning, Peoples R China;[2]Henan Univ Econ & Law, Sch Business Adm, Zhengzhou, Henan, Peoples R China;[3]Univ Melbourne, Fac Business & Econ, Melbourne, Vic, Australia;[4]Michigan State Univ, Broad Coll Business, E Lansing, MI 48824 USA

第一机构：Northeastern Univ, Sch Business Adm, Shenyang, Liaoning, Peoples R China

通讯机构：[1]corresponding author), Northeastern Univ, Sch Business Adm, Shenyang, Liaoning, Peoples R China.

年份：2020

卷号：58

期号：7

起止页码：1950-1967

外文期刊名：INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH

收录：;EI(收录号：20192907181379);Scopus(收录号：2-s2.0-85068754085);WOS:【SSCI(收录号:WOS:000475154800001)，SCI-EXPANDED(收录号:WOS:000475154800001)】；

基金：This research is supported by the National Natural Science Foundation of China (Nos. 70972100 and 71372186).

语种：英文

外文关键词：procurement and distribution optimisation; risk aversion; fairness concern; CVaR; normalised normal constraint

摘要：This paper considers a three-tier supply chain in which a manufacturer uses raw materials sourced from multiple suppliers to produce an item and sells it through multiple distributors. We develop an integrated optimisation model to study supply chain procurement and distribution decisions incorporating the manufacturer's aversion to risk and the distributors' concern for fairness in a climate of uncertain supply and demand. Resilient strategies, such as alternative sourcing and transshipment, are also considered when optimising the supply chain cost and service level. To solve the problem, a Monte Carlo simulation-based multi-objective stochastic programming model is built. It uses the CVaR (Conditional Value-at-Risk) and unfairness aversion utility function to reflect the decision maker's risk aversion and the customer's concern for fairness, respectively. A Normalised Normal Constraint based algorithm is adopted to obtain the Pareto Frontier. In addition, the numerical analysis provides some valuable insights for supply chain managers.