@article{ref1,
title="A comprehensive evacuation planning model and genetic solution algorithm",
journal="Transportation research part E: logistics and transportation review",
year="2014",
author="Goerigk, Marc and Deghdak, Kaouthar and Heßler, Philipp",
volume="71",
number="",
pages="82-97",
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.<p />",
language="en",
issn="1366-5545",
doi="10.1016/j.tre.2014.08.007",
url="http://dx.doi.org/10.1016/j.tre.2014.08.007"
}