期刊
PRODUCTION AND OPERATIONS MANAGEMENT
卷 30, 期 6, 页码 1927-1943出版社
WILEY
DOI: 10.1111/poms.13239
关键词
operations management; robust optimization; model uncertainty
资金
- NSF [CMMI-1727478]
- NSFC [71991462]
- Tsinghua-UC Berkeley Shenzhen Institute
In recent years, robust optimization has made significant progress in operations management, addressing issues such as model uncertainty. There are many research opportunities and challenges to be explored in the future.
Over the past two decades, there has been explosive growth in the application of robust optimization in operations management (robust OM), fueled by both significant advances in optimization theory and a volatile business environment that has led to rising concerns about model uncertainty. We review some common modeling frameworks in robust OM, including the representation of uncertainty and the decision-making criteria, and sources of model uncertainty that have arisen in the literature, such as demand, supply, and preference. We discuss the successes of robust OM in addressing model uncertainty, enriching decision criteria, generating structural results, and facilitating computation. We also discuss several future research opportunities and challenges.
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