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Adjustable robust strategies for flood protection

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  • Postek, Krzysztof
  • den Hertog, Dick
  • Kind, Jarl
  • Pustjens, Chris

Abstract

Flood protection is of major importance to many flood-prone regions and involves substantial investment and maintenance costs. Modern flood risk management often requires determining a cost-efficient protection strategy, i.e., one which has the lowest possible long run cost and which satisfies flood protection standards imposed by the regulator throughout the entire planning horizon. There are two challenges that complicate the modeling: (i) uncertainty - many of the important parameters on which the strategies are based (e.g. the sea level rise) are uncertain, and will be known only in the future, and (ii) adjustability - decisions implemented at later time stages need to adapt to the realized uncertainty values. We develop a new mathematical model addressing both issues, based on recent advances in integer robust optimization, and we apply it to the Rhine Estuary - Drechtsteden area in the Netherlands. Our approach shows, among others, that (i) considering 40% uncertainty about the sea level rise leads to a solution with less than 10% increase in the total cost, (ii) solutions taking the uncertainty into account are cheaper in the long run if the ‘bad scenarios’ for the uncertainty materialize, even if the ‘optimistic solutions’ are allowed to be repaired later on, and (iii) the optimal here-and-now investment decisions change when uncertainty and adjustability are included in the model.

Suggested Citation

  • Postek, Krzysztof & den Hertog, Dick & Kind, Jarl & Pustjens, Chris, 2019. "Adjustable robust strategies for flood protection," Omega, Elsevier, vol. 82(C), pages 142-154.
  • Handle: RePEc:eee:jomega:v:82:y:2019:i:c:p:142-154
    DOI: 10.1016/j.omega.2017.12.009
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    References listed on IDEAS

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    1. Postek, K.S. & den Hertog, D., 2016. "Multi-stage Adjustable Robust Mixed-Integer Optimization via Iterative Splitting of the Uncertainty set (Revision of CentER Discussion Paper 2014-056)," Other publications TiSEM 08442e3a-d1eb-42b3-8f13-8, Tilburg University, School of Economics and Management.
    2. Krzysztof Postek & Dick den Hertog, 2016. "Multistage Adjustable Robust Mixed-Integer Optimization via Iterative Splitting of the Uncertainty Set," INFORMS Journal on Computing, INFORMS, vol. 28(3), pages 553-574, August.
    3. Gabrel, Virginie & Murat, Cécile & Thiele, Aurélie, 2014. "Recent advances in robust optimization: An overview," European Journal of Operational Research, Elsevier, vol. 235(3), pages 471-483.
    4. Ruud Brekelmans & Dick den Hertog & Kees Roos & Carel Eijgenraam, 2012. "Safe Dike Heights at Minimal Costs: The Nonhomogeneous Case," Operations Research, INFORMS, vol. 60(6), pages 1342-1355, December.
    5. Carel Eijgenraam & Jarl Kind & Carlijn Bak & Ruud Brekelmans & Dick den Hertog & Matthijs Duits & Kees Roos & Pieter Vermeer & Wim Kuijken, 2014. "Economically Efficient Standards to Protect the Netherlands Against Flooding," Interfaces, INFORMS, vol. 44(1), pages 7-21, February.
    6. Dimitris Bertsimas & Iain Dunning, 2016. "Multistage Robust Mixed-Integer Optimization with Adaptive Partitions," Operations Research, INFORMS, vol. 64(4), pages 980-998, August.
    7. Dimitris Bertsimas & Angelos Georghiou, 2015. "Design of Near Optimal Decision Rules in Multistage Adaptive Mixed-Integer Optimization," Operations Research, INFORMS, vol. 63(3), pages 610-627, June.
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    Cited by:

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    More about this item

    Keywords

    Robust optimization; Flood protection; Adjustability; Adaptivity;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming

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