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Volumn , Issue , 2012, Pages

Solving high objective problems in fixed interactions with the decision maker

Author keywords

decision maker calls; Evolutionary multi objective optimization algorithm; interactive multi objective optimization algorithm; multiple criteria decision making; preference based multi objective optimization; value function

Indexed keywords

DECISION MAKERS; EVOLUTIONARY MULTIOBJECTIVE OPTIMIZATION; MULTI OBJECTIVE OPTIMIZATIONS (MOO); MULTIPLE CRITERIA DECISION MAKING; VALUE FUNCTIONS;

EID: 84866856660     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CEC.2012.6256552     Document Type: Conference Paper
Times cited : (2)

References (14)
  • 4
    • 77957600209 scopus 로고    scopus 로고
    • An interactive evolutionary multi-objective optimization method based on progressively approximated value functions
    • K. Deb, A. Sinha, P. Korhonen, and J. Wallenius. An interactive evolutionary multi-objective optimization method based on progressively approximated value functions. IEEE Transactions on Evolutionary Computation, 14(5):723-739, 2010.
    • (2010) IEEE Transactions on Evolutionary Computation , vol.14 , Issue.5 , pp. 723-739
    • Deb, K.1    Sinha, A.2    Korhonen, P.3    Wallenius, J.4
  • 5
    • 33745917564 scopus 로고    scopus 로고
    • Scalable test problems for evolutionary multi-objective optimization
    • A. Abraham, L. Jain, and R. Goldberg, editors, London: Springer-Verlag
    • K. Deb, L. Thiele, M. Laumanns, and E. Zitzler. Scalable test problems for evolutionary multi-objective optimization. In A. Abraham, L. Jain, and R. Goldberg, editors, Evolutionary Multiobjective Optimization, pages 105-145. London: Springer-Verlag, 2005.
    • (2005) Evolutionary Multiobjective Optimization , pp. 105-145
    • Deb, K.1    Thiele, L.2    Laumanns, M.3    Zitzler, E.4
  • 7
    • 57049189011 scopus 로고    scopus 로고
    • Interactive multiobjective optimization with the pareto memetic algorithm
    • A. Jaszkiewicz. Interactive multiobjective optimization with the pareto memetic algorithm. Foundations of Computing and Decision Sciences, 32(1):15-32, 2007.
    • (2007) Foundations of Computing and Decision Sciences , vol.32 , Issue.1 , pp. 15-32
    • Jaszkiewicz, A.1
  • 9
    • 0942277866 scopus 로고    scopus 로고
    • An interactive evolutionary metaheuristic for multiobjective combinatorial optimization
    • December
    • S. Phelps and M. Koksalan. An interactive evolutionary metaheuristic for multiobjective combinatorial optimization. Management Science, 49(12):1726-1738, December 2003.
    • (2003) Management Science , vol.49 , Issue.12 , pp. 1726-1738
    • Phelps, S.1    Koksalan, M.2
  • 10
    • 79959483003 scopus 로고    scopus 로고
    • Progressively interactive evolutionary multi-objective optimization method using generalized polynomial value functions
    • IEEE Press
    • A. Sinha, K. Deb, P. Korhonen, and J. Wallenius. Progressively interactive evolutionary multi-objective optimization method using generalized polynomial value functions. In 2010 IEEE Congress on Evolutionary Computation (CEC-2010), pages 1-8. IEEE Press, 2010.
    • (2010) 2010 IEEE Congress on Evolutionary Computation (CEC-2010) , pp. 1-8
    • Sinha, A.1    Deb, K.2    Korhonen, P.3    Wallenius, J.4
  • 12
    • 0000417016 scopus 로고
    • The use of reference objectives in multiobjective optimization
    • G. Fandel and T. Gal, editors, Berlin: Springer-Verlag
    • A. P. Wierzbicki. The use of reference objectives in multiobjective optimization. In G. Fandel and T. Gal, editors, Multiple Criteria Decision Making Theory and Applications, pages 468-486. Berlin: Springer-Verlag, 1980.
    • (1980) Multiple Criteria Decision Making Theory and Applications , pp. 468-486
    • Wierzbicki, A.P.1
  • 13
    • 2942547409 scopus 로고    scopus 로고
    • SPEA2: Improving the strength pareto evolutionary algorithm for multiobjective optimization
    • K. C. Giannakoglou, D. T. Tsahalis, J. Périaux, K. D. Papailiou, and T. Fogarty, editors, Athens, Greece, International Center for Numerical Methods in Engineering (Cmine)
    • E. Zitzler, M. Laumanns, and L. Thiele. SPEA2: Improving the strength pareto evolutionary algorithm for multiobjective optimization. In K. C. Giannakoglou, D. T. Tsahalis, J. Périaux, K. D. Papailiou, and T. Fogarty, editors, Evolutionary Methods for Design Optimization and Control with Applications to Industrial Problems, pages 95-100, Athens, Greece, 2001. International Center for Numerical Methods in Engineering (Cmine).
    • (2001) Evolutionary Methods for Design Optimization and Control with Applications to Industrial Problems , pp. 95-100
    • Zitzler, E.1    Laumanns, M.2    Thiele, L.3
  • 14
    • 0034199979 scopus 로고    scopus 로고
    • Comparison of multiobjective evolutionary algorithms: Empirical results
    • Eckart Zitzler, Kalyanmoy Deb, and Lothar Thiele. Comparison of multiobjective evolutionary algorithms: Empirical results. Evolutionary Computation Journal, 8(2):125-148, 2000.
    • (2000) Evolutionary Computation Journal , vol.8 , Issue.2 , pp. 125-148
    • Zitzler, E.1    Deb, K.2    Thiele, L.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.