DocumentCode :
2910386
Title :
Dynamic diversity control by injecting artificial chromosomes for solving TSP problems
Author :
Chang, Pei-Chann ; Huang, Wei-Hsiu ; Liu, Julie Yu-Chih ; Cycer Chen ; Ting, Ching-Jung
Author_Institution :
Dept. of Inf. Manage., Yuan Ze Univ., Taoyuan
fYear :
2008
fDate :
1-6 June 2008
Firstpage :
542
Lastpage :
549
Abstract :
The applications of genetic algorithms (GAs) in solving combinatorial problems are frequently faced with a problem of early convergence and the evolutionary processes are often trapped in a local but not global optimum. This premature convergence occurs when the population of a genetic algorithm reaches a suboptimal state that the genetic operators can no longer produce offspring with a better performance than their parents. In the literature, plenty of work has been investigated to introduce new methods and operators in order to overcome this essential problem of genetic algorithms. As these methods and the belonging operators are rather problem specific in general. In this research, we take a different approach by observing the progress of the evolutionary process and when the diversity of the population dropping below a threshold level then artificial chromosomes with high diversity will be introduced to increase the average diversity level thus to ensure the process can jump out the local optimum. The proposed method is implemented independently of the problem characteristics and can be applied to improve the global convergence behavior of genetic algorithms. The experimental results using TSP instances show that the proposed approach is very effective in preventing the premature convergence when compared with the earlier approaches.
Keywords :
genetic algorithms; travelling salesman problems; TSP problems; artificial chromosomes; combinatorial problems; dynamic diversity control; evolutionary process; genetic algorithms; travelling salesman problems; Biological cells; Cities and towns; Convergence; Evolutionary computation; Genetic algorithms; Hamming distance; Length measurement; Mathematics;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Evolutionary Computation, 2008. CEC 2008. (IEEE World Congress on Computational Intelligence). IEEE Congress on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4244-1822-0
Electronic_ISBN :
978-1-4244-1823-7
Type :
conf
DOI :
10.1109/CEC.2008.4630849
Filename :
4630849
Link To Document :
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