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Testing of Hybrid Genetic Algorithms for Structured Quadratic Assignment Problems
Volume 20, Issue 2 (2009), pp. 255–272
Alfonsas Misevičius   Dalius Rubliauskas  

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https://doi.org/10.15388/Informatica.2009.249
Pub. online: 1 January 2009      Type: Research Article     

Received
1 February 2008
Accepted
1 February 2009
Published
1 January 2009

Abstract

In this paper, an efficient hybrid genetic algorithm (HGA) and its variants for the well-known combinatorial optimization problem, the quadratic assignment problem (QAP) are discussed. In particular, we tested our algorithms on a special type of QAPs, the structured quadratic assignment problems. The results from the computational experiments on this class of problems demonstrate that HGAs allow to achieve near-optimal and (pseudo-)optimal solutions at very reasonable computation times. The obtained results also confirm that the hybrid genetic algorithms are among the most suitable heuristic approaches for this type of QAPs.

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Keywords
combinatorial optimization quadratic assignment problem heuristics meta-heuristics hybrid genetic algorithms

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INFORMATICA

  • Online ISSN: 1822-8844
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