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The State of Robust Optimization

In: Robustness Analysis in Decision Aiding, Optimization, and Analytics

Author

Listed:
  • Seçil Sözüer

    (Lehigh University)

  • Aurélie C. Thiele

    (Lehigh University)

Abstract

This survey presents a broad overview of the developments in robust optimization over the past 5 years, i.e., between 2011 and 2015. We highlight the advancement of knowledge both with respect to the theory of robust optimization and application areas. From a theoretical standpoint, we describe novel findings in static and multi-stage decision making, the connection with stochastic optimization, distributional robustness and robust nonlinear optimization. In terms of application areas, we consider inventory and logistics, finance, revenue management and health care. We conclude with guidelines for researchers interested in immunizing their problem against uncertainty.

Suggested Citation

  • Seçil Sözüer & Aurélie C. Thiele, 2016. "The State of Robust Optimization," International Series in Operations Research & Management Science, in: Michael Doumpos & Constantin Zopounidis & Evangelos Grigoroudis (ed.), Robustness Analysis in Decision Aiding, Optimization, and Analytics, chapter 0, pages 89-112, Springer.
    • Handle: RePEc:spr:isochp:978-3-319-33121-8_5
    DOI: 10.1007/978-3-319-33121-8_5
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    Cited by:

    1. Mengshi Lu & Zuo‐Jun Max Shen, 2021. "A Review of Robust Operations Management under Model Uncertainty," Production and Operations Management, Production and Operations Management Society, vol. 30(6), pages 1927-1943, June.
    2. Yanıkoğlu, İhsan & Gorissen, Bram L. & den Hertog, Dick, 2019. "A survey of adjustable robust optimization," European Journal of Operational Research, Elsevier, vol. 277(3), pages 799-813.
    3. Shunichi Ohmori, 2021. "A Predictive Prescription Using Minimum Volume k -Nearest Neighbor Enclosing Ellipsoid and Robust Optimization," Mathematics, MDPI, vol. 9(2), pages 1-16, January.

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