Presentation 2004/11/20
Evolutionary Computation with Linkage Identification for Solving TSP
Shin-ichiro UMEZANE, Satoshi FUJITA,
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Abstract(in English) This paper proposes a new linkage identification scheme for the genetic algorithm (GA). GA is widely known as a "good" metaheuristic for solving many combinatorial optimization problems, such as the traveling salesman problem (TSP) and the knapsack problem. In the proposed method, we realize a linkage identification (i.e., identification of an appropriate set of building blocks) with a high accuracy by focusing on the close relationship between "genes" that may frequently occur in solving combinatorial problems. The performance of the proposed method is experimentally evaluated by using TSPLIB, that is known as a benchmark set for TSP. The result of experiments shows that the proposed method could reduce the imbalance of solutions as well as the badness of solutions, with a high probability.
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Keyword(in English) evolutionary computation / linkage identification / genetic algorithm / traveling salesman problem
Paper # NC2004-100
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Committee NC
Conference Date 2004/11/20(1days)
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Registration To Neurocomputing (NC)
Language JPN
Title (in Japanese) (See Japanese page)
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Title (in English) Evolutionary Computation with Linkage Identification for Solving TSP
Sub Title (in English)
Keyword(1) evolutionary computation
Keyword(2) linkage identification
Keyword(3) genetic algorithm
Keyword(4) traveling salesman problem
1st Author's Name Shin-ichiro UMEZANE
1st Author's Affiliation Department of Information Engineering, Graduate School of Engineering Hiroshima University()
2nd Author's Name Satoshi FUJITA
2nd Author's Affiliation Department of Information Engineering, Graduate School of Engineering Hiroshima University
Date 2004/11/20
Paper # NC2004-100
Volume (vol) vol.104
Number (no) 474
Page pp.pp.-
#Pages 6
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