DocumentCode :
2753492
Title :
Selfish-gene Tolerant Generic Algorithms to solve large-scale constraint TSPs
Author :
Sakurai, Yoshitaka ; Onoyama, Takashi ; Kubota, Sen ; Nakamura, Yoshihiro ; Tsuruta, Setsuo
Author_Institution :
Sch. of Inf. Environ., Tokyo Denki Univ., Inzai
fYear :
2006
fDate :
16-18 Sept. 2006
Firstpage :
154
Lastpage :
159
Abstract :
Large-scale distribution network simulation applicable to supply-chain management requires to solve hundreds of time-constraint large-scale (max 2000 cities) traveling salesman problems (TSP) within interactive response time, with practicable optimality. To meet this requirement, a selfish-gene tolerant type GA is proposed. Here, each gene of an individual satisfies only its constraints selfishly, disregarding the constraints of other genes in the same individual Further, to some extent, even individuals that violate constraints can survive over generations and are given the chance of improvement. Our experiment proves that this method provides expert-level solutions for time constraint large-scale TSPs within a few seconds
Keywords :
distribution strategy; genetic algorithms; supply chain management; travelling salesman problems; constraint traveling salesman problems; distribution network simulation; selfish-gene tolerant generic algorithm; supply-chain management; Cities and towns; Delay; Error analysis; Gases; Humans; Large-scale systems; Manufacturing; Production facilities; Time factors; Traveling salesman problems;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Reuse and Integration, 2006 IEEE International Conference on
Conference_Location :
Waikoloa Village, HI
Print_ISBN :
0-7803-9788-6
Type :
conf
DOI :
10.1109/IRI.2006.252405
Filename :
4018482
Link To Document :
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