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MATOUŠEK, R. DOBROVSKÝ, L. KŮDELA, J.
Original Title
The quadratic assignment problem: metaheuristic optimization using HC12 algorithm
Type
conference paper
Language
English
Original Abstract
The Quadratic Assignment Problem (QAP) is a classical NP-hard combinatorial optimization problem. In the paper will be presented suitable metaheuristic algorithm HC12. The algorithm is population based and uses a massive parallel search of the binary space which represents the solution space of the QAP. The presented implementation of the metaheuristic HC12 utilizes the latest GPU CUDA platform. The results are presented on standard test problems from the QAP library.
Keywords
Quadratic assignment problem, Massively parallel algorithm
Authors
MATOUŠEK, R.; DOBROVSKÝ, L.; KŮDELA, J.
Released
13. 7. 2019
Publisher
ACM
Location
New York, NY, USA
ISBN
978-1-4503-6748-6
Book
GECCO '19 Proceedings of the Genetic and Evolutionary Computation Conference Companion
Pages from
153
Pages to
154
Pages count
2
URL
https://dl.acm.org/citation.cfm?doid=3319619.3322088
BibTex
@inproceedings{BUT157692, author="Radomil {Matoušek} and Ladislav {Dobrovský} and Jakub {Kůdela}", title="The quadratic assignment problem: metaheuristic optimization using HC12 algorithm", booktitle="GECCO '19 Proceedings of the Genetic and Evolutionary Computation Conference Companion", year="2019", pages="153--154", publisher="ACM", address="New York, NY, USA", doi="10.1145/3319619.3322088", isbn="978-1-4503-6748-6", url="https://dl.acm.org/citation.cfm?doid=3319619.3322088" }