Publication detail
The quadratic assignment problem: metaheuristic optimization using HC12 algorithm
MATOUŠEK, R. DOBROVSKÝ, L. KŮDELA, J.
English title
The quadratic assignment problem: metaheuristic optimization using HC12 algorithm
Type
conference paper
Language
en
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.
English 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 in English
Quadratic assignment problem, Massively parallel algorithm
Released
13.07.2019
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–to
153–154
Pages count
2
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",
month="July",
pages="153--154",
publisher="ACM",
address="New York, NY, USA",
isbn="978-1-4503-6748-6"
}