An Improved Firefly Algorithm Based on Local Search Method for Solving Global Optimization Problems

R. M. Rizk-Allah

doi:doi:10.11648/j.ijmfs.20160206.11

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An Improved Firefly Algorithm Based on Local Search Method for Solving Global Optimization Problems

R. M. Rizk-Allah

Published in International Journal of Management and Fuzzy Systems (Volume 2, Issue 6)

Received: 9 December 2016 Accepted: 20 December 2016 Published: 1 March 2017

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Abstract

This paper proposes an improved firefly algorithm (IFA)based on local search method for solving globaloptimization problems. The main feature of the proposed algorithm is to improve the solutions quality generated from the fireflies by embedding the local search method. Moreover, the new solutions are generated based on the movement formula of the fireflies that is modified by exponential formula. The exponential formula reduces the randomization parameter so that it decreases gradually as the optimum is approaching. In addition, local search method (LSM) is introduced to improve the solution quality. Finally, the proposed algorithm is tested on several benchmark problems from the usual literature and the numerical results have demonstrated the superiority of the proposed algorithm in finding the global optimal solution.

Published in	International Journal of Management and Fuzzy Systems (Volume 2, Issue 6)
DOI	10.11648/j.ijmfs.20160206.11
Page(s)	51-57
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2017. Published by Science Publishing Group

Keywords

Firefly Algorithm, Local Search Method, Global Optimization

References

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R. M. Rizk-Allah. (2017). An Improved Firefly Algorithm Based on Local Search Method for Solving Global Optimization Problems. International Journal of Management and Fuzzy Systems, 2(6), 51-57. https://doi.org/10.11648/j.ijmfs.20160206.11

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ACS Style

R. M. Rizk-Allah. An Improved Firefly Algorithm Based on Local Search Method for Solving Global Optimization Problems. Int. J. Manag. Fuzzy Syst. 2017, 2(6), 51-57. doi: 10.11648/j.ijmfs.20160206.11

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AMA Style

R. M. Rizk-Allah. An Improved Firefly Algorithm Based on Local Search Method for Solving Global Optimization Problems. Int J Manag Fuzzy Syst. 2017;2(6):51-57. doi: 10.11648/j.ijmfs.20160206.11

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@article{10.11648/j.ijmfs.20160206.11,
  author = {R. M. Rizk-Allah},
  title = {An Improved Firefly Algorithm Based on Local Search Method for Solving Global Optimization Problems},
  journal = {International Journal of Management and Fuzzy Systems},
  volume = {2},
  number = {6},
  pages = {51-57},
  doi = {10.11648/j.ijmfs.20160206.11},
  url = {https://doi.org/10.11648/j.ijmfs.20160206.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijmfs.20160206.11},
  abstract = {This paper proposes an improved firefly algorithm (IFA)based on local search method for solving globaloptimization problems. The main feature of the proposed algorithm is to improve the solutions quality generated from the fireflies by embedding the local search method. Moreover, the new solutions are generated based on the movement formula of the fireflies that is modified by exponential formula. The exponential formula reduces the randomization parameter so that it decreases gradually as the optimum is approaching. In addition, local search method (LSM) is introduced to improve the solution quality. Finally, the proposed algorithm is tested on several benchmark problems from the usual literature and the numerical results have demonstrated the superiority of the proposed algorithm in finding the global optimal solution.},
 year = {2017}
}

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TY  - JOUR
T1  - An Improved Firefly Algorithm Based on Local Search Method for Solving Global Optimization Problems
AU  - R. M. Rizk-Allah
Y1  - 2017/03/01
PY  - 2017
N1  - https://doi.org/10.11648/j.ijmfs.20160206.11
DO  - 10.11648/j.ijmfs.20160206.11
T2  - International Journal of Management and Fuzzy Systems
JF  - International Journal of Management and Fuzzy Systems
JO  - International Journal of Management and Fuzzy Systems
SP  - 51
EP  - 57
PB  - Science Publishing Group
SN  - 2575-4947
UR  - https://doi.org/10.11648/j.ijmfs.20160206.11
AB  - This paper proposes an improved firefly algorithm (IFA)based on local search method for solving globaloptimization problems. The main feature of the proposed algorithm is to improve the solutions quality generated from the fireflies by embedding the local search method. Moreover, the new solutions are generated based on the movement formula of the fireflies that is modified by exponential formula. The exponential formula reduces the randomization parameter so that it decreases gradually as the optimum is approaching. In addition, local search method (LSM) is introduced to improve the solution quality. Finally, the proposed algorithm is tested on several benchmark problems from the usual literature and the numerical results have demonstrated the superiority of the proposed algorithm in finding the global optimal solution.
VL  - 2
IS  - 6
ER  -

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Author Information

R. M. Rizk-Allah

Department of Basic Engineering Science, Faculty of Engineering, Minoufia University, Shebin El-Kom, Egypt

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APA Style

R. M. Rizk-Allah. (2017). An Improved Firefly Algorithm Based on Local Search Method for Solving Global Optimization Problems. International Journal of Management and Fuzzy Systems, 2(6), 51-57. https://doi.org/10.11648/j.ijmfs.20160206.11

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ACS Style

R. M. Rizk-Allah. An Improved Firefly Algorithm Based on Local Search Method for Solving Global Optimization Problems. Int. J. Manag. Fuzzy Syst. 2017, 2(6), 51-57. doi: 10.11648/j.ijmfs.20160206.11

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AMA Style

R. M. Rizk-Allah. An Improved Firefly Algorithm Based on Local Search Method for Solving Global Optimization Problems. Int J Manag Fuzzy Syst. 2017;2(6):51-57. doi: 10.11648/j.ijmfs.20160206.11

Copy | Download

@article{10.11648/j.ijmfs.20160206.11,
  author = {R. M. Rizk-Allah},
  title = {An Improved Firefly Algorithm Based on Local Search Method for Solving Global Optimization Problems},
  journal = {International Journal of Management and Fuzzy Systems},
  volume = {2},
  number = {6},
  pages = {51-57},
  doi = {10.11648/j.ijmfs.20160206.11},
  url = {https://doi.org/10.11648/j.ijmfs.20160206.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijmfs.20160206.11},
  abstract = {This paper proposes an improved firefly algorithm (IFA)based on local search method for solving globaloptimization problems. The main feature of the proposed algorithm is to improve the solutions quality generated from the fireflies by embedding the local search method. Moreover, the new solutions are generated based on the movement formula of the fireflies that is modified by exponential formula. The exponential formula reduces the randomization parameter so that it decreases gradually as the optimum is approaching. In addition, local search method (LSM) is introduced to improve the solution quality. Finally, the proposed algorithm is tested on several benchmark problems from the usual literature and the numerical results have demonstrated the superiority of the proposed algorithm in finding the global optimal solution.},
 year = {2017}
}

Copy | Download

TY  - JOUR
T1  - An Improved Firefly Algorithm Based on Local Search Method for Solving Global Optimization Problems
AU  - R. M. Rizk-Allah
Y1  - 2017/03/01
PY  - 2017
N1  - https://doi.org/10.11648/j.ijmfs.20160206.11
DO  - 10.11648/j.ijmfs.20160206.11
T2  - International Journal of Management and Fuzzy Systems
JF  - International Journal of Management and Fuzzy Systems
JO  - International Journal of Management and Fuzzy Systems
SP  - 51
EP  - 57
PB  - Science Publishing Group
SN  - 2575-4947
UR  - https://doi.org/10.11648/j.ijmfs.20160206.11
AB  - This paper proposes an improved firefly algorithm (IFA)based on local search method for solving globaloptimization problems. The main feature of the proposed algorithm is to improve the solutions quality generated from the fireflies by embedding the local search method. Moreover, the new solutions are generated based on the movement formula of the fireflies that is modified by exponential formula. The exponential formula reduces the randomization parameter so that it decreases gradually as the optimum is approaching. In addition, local search method (LSM) is introduced to improve the solution quality. Finally, the proposed algorithm is tested on several benchmark problems from the usual literature and the numerical results have demonstrated the superiority of the proposed algorithm in finding the global optimal solution.
VL  - 2
IS  - 6
ER  -

Copy | Download