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arXiv · 1407.4863

A Comparative Study of Meta-heuristic Algorithms for Solving Quadratic Assignment Problem

Gamal Abd El-Nasser A. Said·Abeer M. Mahmoud·El-Sayed M. El-Horbaty
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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.

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Gamal Abd El-Nasser A. Said, Abeer M. Mahmoud, El-Sayed M. El-Horbaty. 2014-07-18. A Comparative Study of Meta-heuristic Algorithms for Solving Quadratic Assignment Problem. https://doi.org/10.14569/ijacsa.2014.050101

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