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Volumn , Issue , 2011, Pages 623-628

Survey of oppositional algorithms

Author keywords

Biogeography based optimization; evolutionary algorithms; opposition

Indexed keywords

BENCH-MARK PROBLEMS; BIOGEOGRAPHY-BASED OPTIMIZATIONS; EFFECTIVE ALGORITHMS; HIGH-DIMENSIONAL PROBLEMS; OPPOSITION; OPPOSITION-BASED LEARNING; OPTIMIZATION PROBLEMS; REAL-WORLD PROBLEM;

EID: 84859945143     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICCITechn.2011.6164863     Document Type: Conference Paper
Times cited : (15)

References (21)
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    • (2011) Proceedings of the 2011 IEEE Congress on Evolutionary Computation , pp. 1490-1497
    • Ergezer, M.1    Simon, D.2
  • 9
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    • Rahnamayan, S.1    Wang, G.G.2
  • 11
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    • An adaptive differential evolution algorithm with opposition-based mechanisms, applied to the tuning of a chess program
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    • (2008) Advances in Differential Evolution , pp. 287-298
    • Boškovic, B.1    Greiner, S.2    Brest, J.3    Zamuda, A.4
  • 14
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    • An oppositional biogeography-based optimization technique to reconstruct organ boundaries in the human thorax using electrical impedance tomography
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    • (2011) Physiological Measurement , vol.32 , pp. 767
    • Rashid, A.1    Kim, B.2    Khambampati, A.3    Kim, S.4    Kim, K.5
  • 18
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    • The chc adaptive search algorithm: How to have safe search when engaging in nontraditional genetic recombination
    • L. Eshelman, "The chc adaptive search algorithm: How to have safe search when engaging in nontraditional genetic recombination," Foundations of genetic algorithms, vol. 1, no. 265-283, p. 108, 1991.
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  • 21
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    • (2006) Lecture Notes in Computer Science , vol.4253 , pp. 677-683
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.