Semantic Scholar Open Access 2020 72 sitasi

A Review of Robust Operations Management under Model Uncertainty

Mengshi Lu Z. Shen

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Abstrak

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.

Topik & Kata Kunci

Computer Science

Penulis (2)

Mengshi Lu

Z. Shen

Format Sitasi

APA MLA BibTeX

Lu, M., Shen, Z. (2020). A Review of Robust Operations Management under Model Uncertainty. https://doi.org/10.1111/poms.13239

Akses Cepat

Lihat di Sumber doi.org/10.1111/poms.13239

Informasi Jurnal

Tahun Terbit: 2020
Bahasa: en
Total Sitasi: 72×
Sumber Database: Semantic Scholar
DOI: 10.1111/poms.13239
Akses: Open Access ✓