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A computational comparison of different algorithms for very large p-median problems
Dalarna University, School of Technology and Business Studies, Computer Engineering.ORCID iD: 0000-0003-1015-8015
2015 (English)In: Evolutionary Computation in Combinatorial Optimization: 15th European Conference, EvoCOP 2015, Copenhagen, Denmark, April 8-10, 2015, Proceedings, Springer, 2015, 13-24 p.Chapter in book (Refereed)
Abstract [en]

In this paper, we propose a new method for solving large scale p-median problem instances based on real data. We compare different approaches in terms of runtime, memory footprint and quality of solutions obtained. In order to test the different methods on real data, we introduce a new benchmark for the p-median problem based on real Swedish data. Because of the size of the problem addressed, up to 1938 candidate nodes, a number of algorithms, both exact and heuristic, are considered. We also propose an improved hybrid version of a genetic algorithm called impGA. Experiments show that impGA behaves as well as other methods for the standard set of medium-size problems taken from Beasley’s benchmark, but produces comparatively good results in terms of quality, runtime and memory footprint on our specific benchmark based on real Swedish data.

Place, publisher, year, edition, pages
Springer, 2015. 13-24 p.
, Lecture Notes in Computer Science, ISSN 0302-9743 ; 9026
National Category
Computer Science
Research subject
Komplexa system - mikrodataanalys
URN: urn:nbn:se:du-19289DOI: 10.1007/978-3-319-16468-7_2ISI: 000361701400002ISBN: 978-3-319-16468-7ISBN: 978-3-319-16467-0OAI: diva2:853060
Available from: 2015-09-11 Created: 2015-09-11 Last updated: 2016-03-15Bibliographically approved

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Rebreyend, Pascal
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