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Abstract

We heuristically solve an evacuation problem with limited capacity shelters. An evolutionary learning algorithm is developed for the combined route- and shelter-assignment problem. It is complemented with a heuristic method for the fair minimization of shelter capacities. Different behavioral assumptions fair vs. globally optimal) are investigated. The proposed approaches are discussed in the context of a real-world tsunami evacuation problem.

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