Presentation 1996/12/14
An Evaluation of Four Existing Algorithms and a New Neural Network Algorithm for Traveling Salesman Problems
Yasuhito Shikata, Nobuo Funabiki, Seishi Nishikawa,
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Abstract(in English) The traveling salesman problem is a well-known NP-hard combinatorial optimization problem. To solve the problem many researchers have developed algorithms. In this paper, first, we compare the features of 4 main algorithms. Second, we propose a new neural network algorithm whose energy function takes 0 when the neuron outputs represent a tour. At last, we compare their performance with 5 bench mark problems .The results show that It is found that a proposal algorithm is superior to trivial neural network but inferior to these algorisms.
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Keyword(in English) Traveling salesman problem / NP-hard / Gradual Neural Network / Combinatorial optimization problem / Genetic Algorithm
Paper # NC96-62
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Committee NC
Conference Date 1996/12/14(1days)
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Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) An Evaluation of Four Existing Algorithms and a New Neural Network Algorithm for Traveling Salesman Problems
Sub Title (in English)
Keyword(1) Traveling salesman problem
Keyword(2) NP-hard
Keyword(3) Gradual Neural Network
Keyword(4) Combinatorial optimization problem
Keyword(5) Genetic Algorithm
1st Author's Name Yasuhito Shikata
1st Author's Affiliation Division of Informatics and Mathematical Sciences, Graduate School of Engineering Science, Osaka University()
2nd Author's Name Nobuo Funabiki
2nd Author's Affiliation Division of Informatics and Mathematical Sciences, Graduate School of Engineering Science, Osaka University
3rd Author's Name Seishi Nishikawa
3rd Author's Affiliation Division of Informatics and Mathematical Sciences, Graduate School of Engineering Science, Osaka University
Date 1996/12/14
Paper # NC96-62
Volume (vol) vol.96
Number (no) 430
Page pp.pp.-
#Pages 8
Date of Issue