A comprehensive evacuation planning model and genetic solution algorithm |
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| Affiliation: | 1. School of Civil and Environmental Engineering, Cornell University, Ithaca, NY 14850, USA;2. Department of Civil and Environmental Engineering, University of Delaware, Newark, DE 19716, USA;3. Renaissance Computing Institute, University of North Carolina at Chapel Hill, 100 Europa Drive, Suite 540, Chapel Hill, NC 27517, USA;4. School of Marine and Atmospheric Sciences, Stony Brook University, New York, NY, USA |
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| 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. |
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| Keywords: | Disaster management Evacuation planning Location-routing Multi-criteria genetic algorithms Data aggregation |
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