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Volumn , Issue , 2013, Pages 349-355

Why parameter control mechanisms should be benchmarked against random variation

Author keywords

[No Author keywords available]

Indexed keywords

CONTROL STRATEGIES; EVOLUTIONARY ALGORITHMS (EAS); NEW PARAMETERS; PARAMETER CONTROL; PARAMETER VALUES; RANDOM VARIATION; STATIC VALUES;

EID: 84881566907     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CEC.2013.6557590     Document Type: Conference Paper
Times cited : (9)

References (18)
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    • Hesser, J.1    M̈anner, R.2
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    • T. Jansen and K. A. D. Jong. An analysis of the role of offspring population size in eas. In W. Langdon et al, editor, Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-2002), pages 238-246. Morgan Kaufmann, San Francisco, 9-13 July 2002.
    • (2002) Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-2002) , pp. 238-246
    • Jansen, T.1    Jong, K.A.D.2
  • 11
    • 84860418410 scopus 로고    scopus 로고
    • Idealized dynamic population sizing for uniformly scaled problems
    • N. Krasnogor et al. , editors Dublin, Ireland, 12-16 July 2011 ACM
    • F. G. Lobo. Idealized dynamic population sizing for uniformly scaled problems. In N. Krasnogor et al. , editors, GECCO '11: Proceedings of the 13th annual conference on Genetic and evolutionary computation, pages 917-924, Dublin, Ireland, 12-16 July 2011. ACM.
    • GECCO '11: Proceedings of the 13th Annual Conference on Genetic and Evolutionary Computation , pp. 917-924
    • Lobo, F.G.1
  • 12
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    • Maintaining healthy population diversity using adaptive crossover, mutation, and selection. Evolutionary Computation
    • B. McGinley, J. Maher, C. O'Riordan, and F. Morgan. Maintaining healthy population diversity using adaptive crossover, mutation, and selection. Evolutionary Computation, IEEE Transactions on, 15(5):692-714, 2011.
    • (2011) IEEE Transactions on , vol.15 , Issue.5 , pp. 692-714
    • McGinley, B.1    Maher, J.2    O'Riordan, C.3    Morgan, F.4
  • 15
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    • Multi-problem parameter tuning using bonesa
    • J. Hao, P. Legrand, P. Collet, N. Monmarché, E. Lutton, and M. Schoenauer, editors
    • S. Smit and A. E. Eiben. Multi-problem parameter tuning using bonesa. In J. Hao, P. Legrand, P. Collet, N. Monmarché, E. Lutton, and M. Schoenauer, editors, Artificial Evolution, pages 222-233, 2011.
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    • Operator and parameter adaptation in genetic algorithms. Soft computing- A fusion of foundations
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.