DocumentCode
495571
Title
Introducing Gene Clusters into a P2P Based TSP Solving Algorithm
Author
Guangzhi, Ma ; Yansheng, Lu ; Enmin, Song ; Wei, Zhang
Author_Institution
Sch. of Comput., Huazhong Univ. of Sci. & Technol., Wuhan, China
Volume
4
fYear
2009
fDate
March 31 2009-April 2 2009
Firstpage
795
Lastpage
799
Abstract
The TSP (traveling salesman problem) genetic algorithm is very possible of destroying ever found pieces of a path. To prevent the found pieces from being destroyed, a P2P based TSP genetic algorithm P2PTSPGA which make use of gene clusters is presented. The gene cluster which stands for a series of cities is past down in whole to the offspring from their parent individuals, and is smashed after the first optimum is found to prevent the algorithm from falling into a local optimum. Experiments on CHN144 and instances of TSPLIB show that the optimal solutions are the same as the published results, except the solution 3859 for TSP225 is better than the result 3916 published up-to-date. Our experiments also show that the P2PTSPGA has a high performance in solving such TSPs that number of cities is less than 5000.
Keywords
genetic algorithms; peer-to-peer computing; travelling salesman problems; CHN144; NP-hard problem; P2P based TSP genetic algorithm; P2PTSPGA; TSPLIB; gene clusters; traveling salesman problem; Acceleration; Biological cells; Cities and towns; Clustering algorithms; Computer science; Convergence; Genetic algorithms; Genetic engineering; Genetic mutations; Traveling salesman problems; Gene Cluster; Genetic Algorithm; Peer to Peer; Traveling Salesman Problem;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Science and Information Engineering, 2009 WRI World Congress on
Conference_Location
Los Angeles, CA
Print_ISBN
978-0-7695-3507-4
Type
conf
DOI
10.1109/CSIE.2009.468
Filename
5171105
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