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Research Article | Open Access |

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

Author 1: Gamal Abd El-Nasser A. Said Author 2: Abeer M. Mahmoud Author 3: El-Sayed M. El-Horbaty
International Journal of Advanced Computer Science and Applications (IJACSA) · Vol. 5, No. 1 · Published 2014 · Cited by 88

DOI: https://doi.org/10.14569/IJACSA.2014.050101

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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.

Keywords

Quadratic Assignment Problem (QAP) Genetic Algorithm (GA) Tabu Search (TS) Simulated Annealing (SA) Performance Analysis

How to Cite this Article

Said, G. A. E. A., Mahmoud, A. M., & El-Horbaty, E. M. (2014). A Comparative Study of Meta-heuristic Algorithms for Solving Quadratic Assignment Problem. International Journal of Advanced Computer Science and Applications, 5(1). https://doi.org/10.14569/IJACSA.2014.050101

Said, Gamal Abd El-Nasser A., et al.. "A Comparative Study of Meta-heuristic Algorithms for Solving Quadratic Assignment Problem." International Journal of Advanced Computer Science and Applications, vol. 5, no. 1, 2014, https://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},
  volume    = {5},
  number    = {1},
  year      = {2014},
  publisher = {The Science and Information Organization},
  author    = {Gamal Abd El-Nasser A. Said and Abeer M. Mahmoud and El-Sayed M. El-Horbaty},
  doi       = {10.14569/IJACSA.2014.050101},
  url       = {https://doi.org/10.14569/IJACSA.2014.050101}
}

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