메뉴 건너뛰기




Volumn 20, Issue 1, 2016, Pages 129-151

A coevolutionary approach to many objective optimization based on a novel ranking method

Author keywords

Coevolution; hypervolume approximation; many objective optimization

Indexed keywords

ALGORITHMS; BENCHMARKING; EVOLUTIONARY ALGORITHMS;

EID: 84955507678     PISSN: 1088467X     EISSN: 15714128     Source Type: Journal    
DOI: 10.3233/IDA-150797     Document Type: Article
Times cited : (3)

References (31)
  • 2
    • 55749105514 scopus 로고    scopus 로고
    • Evolutionary many-objective optimization: A short review
    • IEEE Congress on, Hong Kong
    • H. Ishibuchi, N. Tsukamoto and Y. Nojima, Evolutionary many-objective optimization: A short review, in: Evolutionary Computation, CEC 2008, IEEE Congress on, Hong Kong, (2008).
    • (2008) Evolutionary Computation, CEC 2008
    • Ishibuchi, H.1    Tsukamoto, N.2    Nojima, Y.3
  • 6
    • 79951564654 scopus 로고    scopus 로고
    • HypE: An algorithm for fast hypervolume-based many-objective optimization
    • J. Bader and E. Zitzler, HypE: An algorithm for fast hypervolume-based many-objective optimization, Evolutionary Computation 19(1) (2011), 45-76.
    • (2011) Evolutionary Computation , vol.19 , Issue.1 , pp. 45-76
    • Bader, J.1    Zitzler, E.2
  • 8
    • 84881178765 scopus 로고    scopus 로고
    • Preference-inspired coevolutionary algorithms for many-objective optimization
    • Aug
    • R. Wang, R. Purshouse and P. Fleming, Preference-inspired coevolutionary algorithms for many-objective optimization, Evolutionary Computation, IEEE Transactions on 17(4) (Aug 2013), 474-494.
    • (2013) Evolutionary Computation, IEEE Transactions on , vol.17 , Issue.4 , pp. 474-494
    • Wang, R.1    Purshouse, R.2    Fleming, P.3
  • 9
    • 84866860135 scopus 로고    scopus 로고
    • Handling many-objective problems using an improved NSGA-II procedure
    • Jun
    • K. Deb and H. Jain, Handling many-objective problems using an improved NSGA-II procedure, Evolutionary Computation (CEC), 2012 IEEE Congress on 1(8) (Jun 2012), 10-15.
    • (2012) Evolutionary Computation (CEC), 2012 IEEE Congress on , vol.1 , Issue.8 , pp. 10-15
    • Deb, K.1    Jain, H.2
  • 10
    • 78650736508 scopus 로고    scopus 로고
    • Approximating the least hypervolume contributor: NP-hard in general but fast in practice in
    • Berlin: Springer
    • K. Bringmann and T. Friedrich, Approximating the least hypervolume contributor: NP-hard in general, but fast in practice, in: Evolutionary Multi-Criterion Optimization (EMO09), Berlin: Springer, (2009), 6-20.
    • (2009) Evolutionary Multi-Criterion Optimization (EMO09) , pp. 6-20
    • Bringmann, K.1    Friedrich, T.2
  • 11
    • 70449890209 scopus 로고    scopus 로고
    • Hypervolume approximation using achievement scalarizing functions for evolutionary many-objective optimization
    • May
    • H. Ishibuchi, N. Tsukamoto, Y. Sakane and N. Yusuke, Hypervolume approximation using achievement scalarizing functions for evolutionary many-objective optimization, Evolutionary Computation, 2009, CEC '09. IEEE Congress on 530(537) (May 2009), 18-21.
    • (2009) Evolutionary Computation, 2009, CEC '09. IEEE Congress on , vol.530 , Issue.537 , pp. 18-21
    • Ishibuchi, H.1    Tsukamoto, N.2    Sakane, Y.3    Yusuke, N.4
  • 12
    • 85056263890 scopus 로고    scopus 로고
    • Preference-driven co-evolutionary algorithms show promise for manyobjective optimisation
    • Ouro Preto
    • R.C. Purshouse, C. Jalbə and P.J. Fleming, Preference-driven co-evolutionary algorithms show promise for manyobjective optimisation, in: Evolutionary Multi-Criterion Optimization, Ouro Preto, (2011).
    • (2011) Evolutionary Multi-Criterion Optimization
    • Purshouse, R.C.1    Jalbə, C.2    Fleming, P.J.3
  • 14
    • 0036715683 scopus 로고    scopus 로고
    • Combining convergence and diversity in evolutionary multiobjective optimization
    • M. Laumanns, L. Thiele, K. Deb and E. Zitzler, Combining convergence and diversity in evolutionary multiobjective optimization, Evolutionary Computation 10(3) (2002), 263-282.
    • (2002) Evolutionary Computation , vol.10 , Issue.3 , pp. 263-282
    • Laumanns, M.1    Thiele, L.2    Deb, K.3    Zitzler, E.4
  • 17
    • 34548108555 scopus 로고    scopus 로고
    • MOEA/D: A multiobjective evolutionary algorithm based on decomposition
    • Dec, 731
    • Q. Zhang and H. Li, MOEA/D: A multiobjective evolutionary algorithm based on decomposition, Evolutionary Computation, IEEE Transactions on 11(6) (Dec 2007), 712, 731.
    • (2007) Evolutionary Computation, IEEE Transactions on , vol.11 , Issue.6 , pp. 712
    • Zhang, Q.1    Li, H.2
  • 19
  • 20
    • 0000773783 scopus 로고    scopus 로고
    • Multiobjective optimization using evolutionary algorithms - A comparative case study
    • Amsterdam
    • E. Zitzler and L. Thiele, Multiobjective optimization using evolutionary algorithms - A comparative case study, in: Parallel Problem Solving from Nature, Amsterdam, (1998).
    • (1998) Parallel Problem Solving from Nature
    • Zitzler, E.1    Thiele, L.2
  • 21
    • 33947669974 scopus 로고    scopus 로고
    • SMS-EMOA: Multiobjective selection based on dominated hypervolume
    • N. Beume, B. Naujoks and M. Emmerich, SMS-EMOA: Multiobjective selection based on dominated hypervolume, European Journal of Operational Research 181(3) (2007), 1653-1669.
    • (2007) European Journal of Operational Research , vol.181 , Issue.3 , pp. 1653-1669
    • Beume, N.1    Naujoks, B.2    Emmerich, M.3
  • 27
    • 17444430405 scopus 로고    scopus 로고
    • Solving multiobjective optimization problems using an artificial immune system
    • C.A.C. Coello and N.C. Cortés, Solving multiobjective optimization problems using an artificial immune system, Genetic Programming and Evolvable Machines 6(2) (2005), 163-190.
    • (2005) Genetic Programming and Evolvable Machines , vol.6 , Issue.2 , pp. 163-190
    • Coello, C.A.C.1    Cortés, N.C.2
  • 31
    • 63149100088 scopus 로고    scopus 로고
    • Combining advantages of new chromosome representation scheme and multi-objective genetic algorithms for better clustering
    • IOS Press
    • E.E. Korkmaz, J. Du, R. Alhajj and K. Barker, Combining advantages of new chromosome representation scheme and multi-objective genetic algorithms for better clustering, in: Intelligent Data Analysis, IOS Press 10 (2006), 163-182.
    • (2006) Intelligent Data Analysis , vol.10 , pp. 163-182
    • Korkmaz, E.E.1    Du, J.2    Alhajj, R.3    Barker, K.4


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.