A Comparative Study of Meta-heuristic Algorithms for Solving Quadratic Assignment Problem
Journal Title: International Journal of Advanced Computer Science & Applications - Year 2014, Vol 5, Issue 1
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.
Authors and Affiliations
Gamal Abd A. Said, Abeer Mahmoud, El-Sayed El-Horbaty
Keywords
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- EP ID EP147105
- DOI 10.14569/IJACSA.2014.050101
- Views 103
- Downloads 0
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