Presentation 2013-03-14
A Chaotic Local Search Algorithm with Adaptive Exchange of Elements for Quadratic Assignment Problems
Akio WATANABE, Kaori KURODA, Kantaro FUJIWARA, Tohru IKEGUCHI,
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Abstract(in English) The quadratic assignment problem(QAP)is one of the NP-hard combinatorial optimization problems. Then, it is required to develop approximate algorithms for finding near optimal solutions in realistic time. 0n the other hand, to solve traveling salesman problems which is a special case of QAP, the Lin-Kernighan algorithm has been proposed. In this report, we propose an algorithm for solving QAPs by introducing characteristic property of searching process in the Lin-Kernighan algorithm. We also in- troduced chaotic dynamics into the proposed algorithm to escape undesirable local minima. To evaluate solving performance of the proposed method, we compared the performance of the proposed method with that of the conventional methods. As a result, the solving performance of the proposed method with chaotic dynamics exhibits smaller gaps from optimal solutions than the conventional algorithms.
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Keyword(in English) combinatorial optimization / quadratic assignment problems / local search
Paper # NLP2012-145
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Committee NLP
Conference Date 2013/3/7(1days)
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Registration To Nonlinear Problems (NLP)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) A Chaotic Local Search Algorithm with Adaptive Exchange of Elements for Quadratic Assignment Problems
Sub Title (in English)
Keyword(1) combinatorial optimization
Keyword(2) quadratic assignment problems
Keyword(3) local search
1st Author's Name Akio WATANABE
1st Author's Affiliation Faculty of Engineering, Saitama University()
2nd Author's Name Kaori KURODA
2nd Author's Affiliation Graduate School of Science and Engineering, Saitama University
3rd Author's Name Kantaro FUJIWARA
3rd Author's Affiliation Graduate School of Science and Engineering, Saitama University
4th Author's Name Tohru IKEGUCHI
4th Author's Affiliation Graduate School of Science and Engineering, Saitama University:Brain Science Institute, Saitama University
Date 2013-03-14
Paper # NLP2012-145
Volume (vol) vol.112
Number (no) 487
Page pp.pp.-
#Pages 6
Date of Issue