DocumentCode :
3270312
Title :
An Algorithm Constrained by Complex Network´s Structure for Solving TSP
Author :
Yiying Chen ; Zexing Zhang ; Wenbin Li
Author_Institution :
Dept. of Inf. Eng., Shijiazhuang Univ. of Econ., Shijiazhuang, China
fYear :
2013
fDate :
16-18 Jan. 2013
Firstpage :
270
Lastpage :
273
Abstract :
The genetic algorithm is easy to fall into precocious, An improved genetic algorithm is proposed to solve this problem. On the one hand, the algorithm cancels the selection operator. On the other hand, by means of the structure of a complex network, individuals´ evolutions are limited to a small population (an individual and its neighbors). The advantage of this algorithm is: first that it does not need to design too many run-parameters for the genetic algorithm. Further, it effectively avoid the premature phenomenon occurred. Experimental results show the effectiveness of the algorithm. It achieves the design purpose.
Keywords :
complex networks; computational complexity; genetic algorithms; network theory (graphs); travelling salesman problems; TSP; complex network; genetic algorithm; selection operator; traveling salesman problem; Algorithm design and analysis; Cities and towns; Complex networks; Convergence; Genetic algorithms; Sociology; Statistics; Complex Network; Generic Algorithm; NP-Hard;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent System Design and Engineering Applications (ISDEA), 2013 Third International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4673-4893-5
Type :
conf
DOI :
10.1109/ISDEA.2012.67
Filename :
6454753
Link To Document :
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