Genetic Algorithm for Solving Uncapacitated Multiple Allocation Hub Location Problem
Jozef Kratica ; Zorica Stanimirović ; Dušan Tošić ; Vladimir Filipović
Computing and Informatics, Tome 28 (2012) no. 1, p. 415-426 / Harvested from Computing and Informatics
Hub location problems are widely used for network designing. Many variations of these problems can be found in the literature. In this paper we deal with the uncapacitated multiple allocation hub location problem (UMAHLP). We propose a genetic algorithm (GA) for solving UMAHLP that uses binary encoding and genetic operators adapted to the problem. Overall performance of GA implementation is improved by caching technique. We present the results of our computational experience on standard ORLIB instances with up to 200 nodes. The results show that GA approach quickly reaches all optimal solutions that are known so far and also gives results on some large-scale instances that were unsolved before.
Publié le : 2012-01-26
Classification:  Hub location problem; genetic algorithms; evolutionary computation; discrete location and assignment; network design; combinatorial optimization
@article{cai387,
     author = {Jozef Kratica and Zorica Stanimirovi\'c and Du\v san To\v si\'c and Vladimir Filipovi\'c},
     title = {Genetic Algorithm for Solving Uncapacitated Multiple Allocation Hub Location Problem},
     journal = {Computing and Informatics},
     volume = {28},
     number = {1},
     year = {2012},
     pages = { 415-426},
     language = {en},
     url = {http://dml.mathdoc.fr/item/cai387}
}
Jozef Kratica; Zorica Stanimirović; Dušan Tošić; Vladimir Filipović. Genetic Algorithm for Solving Uncapacitated Multiple Allocation Hub Location Problem. Computing and Informatics, Tome 28 (2012) no. 1, pp.  415-426. http://gdmltest.u-ga.fr/item/cai387/