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Volumn , Issue , 2010, Pages 55-62

Development of efficient particle swarm optimizers by using concepts from evolutionary algorithms

Author keywords

Evolutionary optimization; G3 PCX; Particle swarm optimization; Recombination; Steady state PSO; Unimodal problems

Indexed keywords

EVOLUTIONARY OPTIMIZATIONS; G3-PCX; PARTICLE SWARM; RECOMBINATION; STEADY-STATE PSO; UNIMODAL;

EID: 77955906588     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1830483.1830492     Document Type: Conference Paper
Times cited : (27)

References (20)
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    • A. Banks, J. Vincet, andC. Anyakoha. A review of particle swarm optimization. part i: background and development. Natural Computing, 6(4):467-484, 2007.
    • (2007) Natural Computing , vol.6 , Issue.4 , pp. 467-484
    • Banks, A.1    Vincet, J.2    Anyakoha, C.3
  • 4
    • 0036464756 scopus 로고    scopus 로고
    • The particle swarm - Explosion, stability, and convergence in a multidimensional complex space
    • Feb
    • M. Clerc andJ. Kennedy. The particle swarm - explosion, stability, and convergence in a multidimensional complex space. Evolutionary Computation, IEEE Transactions on, 6(1):58-73, Feb 2002.
    • (2002) Evolutionary Computation, IEEE Transactions on , vol.6 , Issue.1 , pp. 58-73
    • Clerc, M.1    Kennedy, J.2
  • 6
    • 0141466594 scopus 로고    scopus 로고
    • MOPSO: A proposal for multiple objective particle swarm optimization
    • IEEE
    • CA. C. Coello andM. S. Lechuga. MOPSO: A proposal for multiple objective particle swarm optimization. In Congress on Evolutionary Computation, pages 825-830. IEEE, 2002.
    • (2002) Congress on Evolutionary Computation , pp. 825-830
    • Coello, C.A.C.1    Lechuga, M.S.2
  • 7
    • 0036885602 scopus 로고    scopus 로고
    • A computationally efficient evolutionary algorithm for real-parameter optimization
    • K. Deb, A. Anand, andD. Joshi. A computationally efficient evolutionary algorithm for real-parameter optimization. Evolutionary Computation Journal, 10(4):371-395, 2002.
    • (2002) Evolutionary Computation Journal , vol.10 , Issue.4 , pp. 371-395
    • Deb, K.1    Anand, A.2    Joshi, D.3
  • 10
    • 1842535329 scopus 로고    scopus 로고
    • A hybrid of genetic algorithm and particle swarm optimization for recurrent network design
    • C-F Juang. A hybrid of genetic algorithm and particle swarm optimization for recurrent network design. IEEE Trans. Syst Man Cybern - Part B: Cybern, 34(2):997-1006, 2004.
    • (2004) IEEE Trans. Syst Man Cybern - Part B: Cybern , vol.34 , Issue.2 , pp. 997-1006
    • Juang, C.-F.1
  • 13
  • 16
    • 70449955511 scopus 로고    scopus 로고
    • Empirical comparison of MOPSO methods - Guide selection and diversity
    • N. Padhye, J. Branke, andS. Mostaghim. Empirical comparison of MOPSO methods - guide selection and diversity. In Proceedings of CEC, pages 2516 - 2523, 2009.
    • (2009) Proceedings of CEC , pp. 2516-2523
    • Padhye, N.1    Branke, J.2    Mostaghim, S.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.