Citation

Goerigk M, Deghdak K, Heßler P. Transp. Res. E Logist. Transp. Rev. 2014; 71: 82-97.

Copyright

(Copyright © 2014, Elsevier Publishing)

DOI

10.1016/j.tre.2014.08.007

PMID

unavailable

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.