Reliable Flexibility Design of Supply Chains Via Extended Probabilistic Expanders

• 成果类型: Article
• 署名作者: Shen, Hao; Liang, Yong; Shen, Zuo-Jun Max; Teo, Chung-Piaw
• 署名单位: Tsinghua University; Tsinghua University; University of California System; University of California Berkeley; University of California System; University of California Berkeley; National University of Singapore; National University of Singapore
• 刊物名称: PRODUCTION AND OPERATIONS MANAGEMENT
• ISSN/ISSBN: 1059-1478
• DOI: 10.1111/poms.12942
• 发表日期: 2019
• 页码: 700-720
• 关键词: long-chain; SPARSE; performance; benefits

摘要

It is well-known that adding a little flexibility to the right place is an effective strategy to improve the performance of operations in the face of demand uncertainties, to ensure high level of capacity utilization. However, given that system disruptions are ubiquitous, the legacy flexibility designs may perform poorly under disruptions to supply or capacity installations. In this study, we focus on the design of reliable and sparse flexibility structures that consistently meet a reasonable performance criterion under disruptions to both demand and supply. Specifically, we propose a class of structures termed as extended probabilistic expanders, based on the conjecture that the expansion property, rather than the global connectivity, is critical to good performance of the structures. We prove that for a system with n retailers, essentially only O(n) supply routes between suppliers and retailers are necessary to ensure good performance under disruption. In addition, we present an efficient randomized algorithm to construct extended probabilistic expanders, and demonstrate that the construction yields very good structure with the least number of edges asymptotically. We also investigate an extension to systems with structural constraints. Numerical results demonstrate that our design has not only a wide range of applications, but also better performance than a variety of known structures.