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Volumn , Issue , 2012, Pages

Generalized opposition-based artificial bee colony algorithm

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL BEE COLONIES; ARTIFICIAL BEE COLONY ALGORITHMS; FORAGING BEHAVIORS; FUNCTION OPTIMIZATION; HONEY BEE; INITIALIZATION STEP; OPPOSITION-BASED LEARNING;

EID: 84866848302     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CEC.2012.6252939     Document Type: Conference Paper
Times cited : (56)

References (21)
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  • 2
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    • Performance assessment of foraging algorithms vs. evolutionary algorithms
    • M. El-Abd, "Performance assessment of foraging algorithms vs. evolutionary algorithms," Information Sciences, vol. 182, no. 1, pp. 243-263, 2012.
    • (2012) Information Sciences , vol.182 , Issue.1 , pp. 243-263
    • El-Abd, M.1
  • 6
    • 77955960329 scopus 로고    scopus 로고
    • Black-box optimization benchmarking for noiseless function testbed using artificial bee colony algorithm
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    • El-Abd, M.1
  • 15
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    • Enhanced opposition-based differential evolution for solving high-dimensional continuous optimization problems
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    • (2011) Soft Computing , vol.15 , Issue.11 , pp. 2127-2140
    • Wang, H.1    Wu, Z.2    Rahnamayan, S.3
  • 16
    • 79960494356 scopus 로고    scopus 로고
    • Enhancing particle swarm optimization using generalized opposition-based learning
    • H. Wang, Z. Wu, S. Rahnamayan, Y. Liu, and M. Ventresca, "Enhancing particle swarm optimization using generalized opposition-based learning," Information sciences, vol. 181, no. 20, pp. 4699-4714, 2011.
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  • 18
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    • An artificial bee colony (ABC) algorithm for numeric function optimization
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  • 19
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.