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A comprehensive evacuation planning model and genetic solution algorithm

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  • Goerigk, Marc
  • Deghdak, Kaouthar
  • Heßler, Philipp

Abstract

We consider the problem of evacuating an urban area. Several planning aspects need to be considered in such a scenario, which are usually considered separately. We propose a macroscopic multi-criteria optimization model that includes several such questions simultaneously, and develop a genetic algorithm to solve the problem heuristically. Its applicability is extended by also considering how to aggregate instance data, and how to generate solutions for the original instance starting from a reduced solution. In computational experiments using real-world data, we demonstrate the effectiveness of our approach and compare different levels of data aggregation.

Suggested Citation

  • Goerigk, Marc & Deghdak, Kaouthar & Heßler, Philipp, 2014. "A comprehensive evacuation planning model and genetic solution algorithm," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 71(C), pages 82-97.
  • Handle: RePEc:eee:transe:v:71:y:2014:i:c:p:82-97
    DOI: 10.1016/j.tre.2014.08.007
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    5. Fatemeh Sabouhi & Ali Bozorgi-Amiri & Mohammad Moshref-Javadi & Mehdi Heydari, 2019. "An integrated routing and scheduling model for evacuation and commodity distribution in large-scale disaster relief operations: a case study," Annals of Operations Research, Springer, vol. 283(1), pages 643-677, December.
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    8. P. Heßler & H. W. Hamacher, 2016. "Sink location to find optimal shelters in evacuation planning," EURO Journal on Computational Optimization, Springer;EURO - The Association of European Operational Research Societies, vol. 4(3), pages 325-347, September.
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