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

@article{Said2014,
title = {A Comparative Study of Meta-heuristic Algorithms for Solving Quadratic Assignment Problem},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2014.050101},
url = {http://dx.doi.org/10.14569/IJACSA.2014.050101},
year = {2014},
publisher = {The Science and Information Organization},
volume = {5},
number = {1},
author = {Gamal Abd El-Nasser A. Said and Abeer M. Mahmoud and El-Sayed M. El-Horbaty}
}