Publication detail

The quadratic assignment problem: metaheuristic optimization using HC12 algorithm

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"
}