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A biogeography-based optimization algorithm hybridized with tabu search for the quadratic assignment problem


Lim, Wee Loon and Wibowo, Antoni and Desa, Mohammad Ishak and Haron, Habibollah (2016) A biogeography-based optimization algorithm hybridized with tabu search for the quadratic assignment problem. Computational Intelligence and Neuroscience, 2016. pp. 1-12. ISSN 1687-5265

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Abstract

The quadratic assignment problem (QAP) is an NP hard combinatorial optimization problem with a wide variety of applications.Biogeography-based optimization (BBO), a relatively new optimization technique based on the biogeography concept, uses the idea of migration strategy of species to derive algorithm for solving optimization problems.It has been shown that BBO provides performance on a par with other optimization methods.A classical BBO algorithm employs the mutation operator as its diversification strategy. However, this process will often ruin the quality of solutions in QAP.In this paper, we propose a hybrid technique to overcome the weakness of classical BBO algorithm to solve QAP, by replacing the mutation operator with a tabu search procedure.Our experiments using the benchmark instances from QAPLIB show that the proposed hybrid method is able to find good solutions for them within reasonable computational times.Out of 61 benchmark instances tested, the proposed method is able to obtain the best known solutions for 57 of them.

Item Type: Article
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: School of Quantitative Sciences
Depositing User: Dr. Antoni Wibowo
Date Deposited: 20 Jul 2016 03:33
Last Modified: 20 Jul 2016 03:33
URI: http://repo.uum.edu.my/id/eprint/18341

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