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Digital Object Identifier (DOI) : 10.14569/IJACSA.2014.050101
Article Published in International Journal of Advanced Computer Science and Applications(IJACSA), Volume 5 Issue 1, 2014.
Abstract: Quadratic Assignment Problem (QAP) is an NP-hard combinatorial optimization problem, therefore, solving the QAP requires applying one or more of the meta-heuristic algorithms. This paper presents a comparative study between Meta-heuristic algorithms: Genetic Algorithm, Tabu Search, and Simulated annealing for solving a real-life (QAP) and analyze their performance in terms of both runtime efficiency and solution quality. The results show that Genetic Algorithm has a better solution quality while Tabu Search has a faster execution time in comparison with other Meta-heuristic algorithms for solving QAP.
Gamal Abd El-Nasser A. Said, Abeer M. Mahmoud and El-Sayed M. El-Horbaty, “A Comparative Study of Meta-heuristic Algorithms for Solving Quadratic Assignment Problem” International Journal of Advanced Computer Science and Applications(IJACSA), 5(1), 2014. http://dx.doi.org/10.14569/IJACSA.2014.050101