title: A Biogeography-Based Optimization Algorithm Hybridized with Tabu Search for the Quadratic Assignment Problem.
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.
authors.affiliation: Faculty of Computing, Universiti Teknologi Malaysia (UTM), 81310 Johor Bahru, Johor, Malaysia.
authors.forename: Wee Loon
authors.initials: WL
authors.lastname: Lim
authors.affiliation: School of Quantitative Sciences, UUM College of Arts and Sciences, Universiti Utara Malaysia, 06010 Sintok, Kedah, Malaysia.
authors.forename: Antoni
authors.initials: A
authors.lastname: Wibowo
authors.affiliation: Faculty of Information and Communication Technology, Universiti Teknikal Malaysia Melaka, Hang Tuah Jaya, 76100 Durian Tunggal, Melaka, Malaysia.
authors.forename: Mohammad Ishak
authors.initials: MI
authors.lastname: Desa
authors.affiliation: Faculty of Computing, Universiti Teknologi Malaysia (UTM), 81310 Johor Bahru, Johor, Malaysia.
authors.forename: Habibollah
authors.initials: H
authors.lastname: Haron
mesh_terms: D000465:Algorithms; D000818:Animals; D001185:Artificial Intelligence; D003198:Computer Simulation; D063426:Human Migration; D006801:Humans; D008954:Models, Biological
references.citation: Evol Comput. 2011 Summer;19(2):167-88
references.pmid: 20807078
references.citation: IEEE Trans Cybern. 2014 Mar;44(3):429-44
references.pmid: 23757559