| Parameter-less evolutionary search |
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Genetic And Evolutionary Computation Conference
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Proceedings of the 10th annual conference on Genetic and evolutionary computation
table of contents
Atlanta, GA, USA
POSTER SESSION: Genetic algorithms posters
table of contents
Pages 1133-1134
Year of Publication: 2008
ISBN:978-1-60558-130-9
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Author
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Gregor Papa
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Jozef Stefan Institute, Ljubljana, Slovenia
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Downloads (6 Weeks): 7, Downloads (12 Months): 50, Citation Count: 0
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ABSTRACT
The paper presents the parameter-less implementation of an evolutionary-based search. It does not need any predefined control parameters values, which are usually used for genetic algorithms and similar techniques. Efficiency of the proposed algorithm was evaluated by CEC2006 benchmark functions and a real-world product optimization problem.
REFERENCES
Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.
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J. Brest, S. Greiner, B. Bošković, M. Mernik, and V. Žumer. Self-adapting control parameters in differential evolution: A comparative study on numerical benchmark problems. IEEE Transactions on Evolutionary Computation, 10(6):646--657, December 2006.
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J. Gomez. Self adaptation of operator rates in evolutionary algorithms. In GECCO 2004, pages 1162--1173, 2004.
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G. R. Harik and F. G. Lobo. A parameter-less genetic algorithm. In GECCO 1999, pages 258--265, July 1999.
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J. Liang, T. Runarsson, E. Mezura-Montes, M. Clerc, P. Suganthan,C. C. Coello, and K. Deb. Problem definitions and evaluation criteria for the cec 2006 special session on constrained real-parameter optimization. Technical Report 2006005, Nanyang Technological University, Singapore, March 2006.
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G. Papa. Concurrent operation scheduling and unit allocation with an evolutionary technique in the process of integrated-circuit design. PhD thesis, University of Ljubljana, Ljubljana, Slovenia, October 2002.
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G. Papa and B. Koroušić-Seljak. An artificial intelligence approach to the efficiency improvement of a universal motor. Engineering Applications of Artificial Intelligence, 18(1):47--55, February 2005.
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