DocumentCode :
506624
Title :
An improved niche genetic algorithm
Author :
Ming, Huang ; Nan, Liu ; Xu, Liang
Author_Institution :
Software Technol. Inst., Dalian Jiao Tong Univ. Dalian, Dalian, China
Volume :
2
fYear :
2009
fDate :
20-22 Nov. 2009
Firstpage :
291
Lastpage :
293
Abstract :
Based on the genetic algorithm for solving multi-objective optimization easily leads to the defect of premature and slow convergence, so an improved niche genetic algorithm is proposed. This algorithm is to select distance parameter equals to the minimum Euclidean distance between the best individuals, using the method of allele comparison to determine within the distance parameter individuals whether similar. Using this method solves the problem of multi-objective optimization, which can produce a better niche environment, greatly protect the diversity of population and improve the search efficiency. The simulation results show that new algorithm effectively avoids falling into local optimal solutions, and performance is superior to the existing algorithms.
Keywords :
genetic algorithms; minimum Euclidean distance; multiobjective optimization; niche genetic algorithm; Biological cells; Electronic mail; Euclidean distance; Genetic algorithms; Job shop scheduling; Optimal control; Optimization methods; Protection; Scheduling algorithm; Software maintenance; distance parameter; multi-objective; niche genetic algorithm;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Computing and Intelligent Systems, 2009. ICIS 2009. IEEE International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-4754-1
Electronic_ISBN :
978-1-4244-4738-1
Type :
conf
DOI :
10.1109/ICICISYS.2009.5357965
Filename :
5357965
Link To Document :
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