 
								An Improved Firefly Algorithm Based on Local Search Method for Solving Global Optimization Problems
								
								
									
										Issue:
										Volume 2, Issue 6, December 2016
									
									
										Pages:
										51-57
									
								 
								
									Received:
										9 December 2016
									
									Accepted:
										20 December 2016
									
									Published:
										1 March 2017
									
								 
								
									
										
											
												DOI:
												
												10.11648/j.ijmfs.20160206.11
											
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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.
										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 ...
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