메뉴 건너뛰기




Volumn 173, Issue , 2016, Pages 1868-1884

Self-organizing multiobjective optimization based on decomposition with neighborhood ensemble

Author keywords

Evolutionary algorithm; Multiobjective optimization; Neighborhood ensemble; Reproduction; Self organizing map

Indexed keywords

ALGORITHMS; CONFORMAL MAPPING; EVOLUTIONARY ALGORITHMS; FACSIMILE; LAKES; OPTIMIZATION; SELF ORGANIZING MAPS;

EID: 84955177072     PISSN: 09252312     EISSN: 18728286     Source Type: Journal    
DOI: 10.1016/j.neucom.2015.08.092     Document Type: Article
Times cited : (52)

References (58)
  • 2
    • 0000599395 scopus 로고
    • Multiple objective optimization with vector evaluated genetic algorithms
    • Lawrence Erlbaum Associates Inc., New Jersey, USA
    • J.D. Schaffer, Multiple objective optimization with vector evaluated genetic algorithms, in: Proceedings of the 1st International Conference on Genetic Algorithms, Lawrence Erlbaum Associates Inc., New Jersey, USA, 1985, pp. 93-100.
    • (1985) Proceedings of the 1st International Conference on Genetic Algorithms , pp. 93-100
    • Schaffer, J.D.1
  • 4
    • 84878475995 scopus 로고    scopus 로고
    • Aggregate meta-models for evolutionary multiobjective and many-objective optimization
    • Pilát M., Neruda R. Aggregate meta-models for evolutionary multiobjective and many-objective optimization. Neurocomputing 2013, 116:392-402.
    • (2013) Neurocomputing , vol.116 , pp. 392-402
    • Pilát, M.1    Neruda, R.2
  • 5
    • 84899502057 scopus 로고    scopus 로고
    • Interactive evolutionary algorithms with decision-makers preferences for solving interval multi-objective optimization problems
    • Gong D., Ji X., Sun J., Sun X. Interactive evolutionary algorithms with decision-makers preferences for solving interval multi-objective optimization problems. Neurocomputing 2014, 137:241-251.
    • (2014) Neurocomputing , vol.137 , pp. 241-251
    • Gong, D.1    Ji, X.2    Sun, J.3    Sun, X.4
  • 6
    • 77949266538 scopus 로고    scopus 로고
    • A multi-objective memetic and hybrid methodology for optimizing the parameters and performance of artificial neural networks
    • Almeida L.M., Ludermir T.B. A multi-objective memetic and hybrid methodology for optimizing the parameters and performance of artificial neural networks. Neurocomputing 2010, 73(79):1438-1450.
    • (2010) Neurocomputing , vol.73 , Issue.79 , pp. 1438-1450
    • Almeida, L.M.1    Ludermir, T.B.2
  • 7
    • 84867804047 scopus 로고    scopus 로고
    • An evolutionary multiobjective sleep-scheduling scheme for differentiated coverage in wireless sensor networks
    • Sengupta S., Das S., Nasir M., Vasilakos A.V., Pedrycz W. An evolutionary multiobjective sleep-scheduling scheme for differentiated coverage in wireless sensor networks. IEEE Trans. Syst. Man Cybern. Part C: Appl. Rev. 2012, 42(6):1093-1102.
    • (2012) IEEE Trans. Syst. Man Cybern. Part C: Appl. Rev. , vol.42 , Issue.6 , pp. 1093-1102
    • Sengupta, S.1    Das, S.2    Nasir, M.3    Vasilakos, A.V.4    Pedrycz, W.5
  • 9
    • 0036530772 scopus 로고    scopus 로고
    • A fast and elitist multiobjective genetic algorithm: NSGA-II
    • Deb K., Pratap A., Agarwal S., Meyarivan T. A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Trans. Evol. Comput. 2002, 6(2):182-197.
    • (2002) IEEE Trans. Evol. Comput. , vol.6 , Issue.2 , pp. 182-197
    • Deb, K.1    Pratap, A.2    Agarwal, S.3    Meyarivan, T.4
  • 10
    • 2942547409 scopus 로고    scopus 로고
    • SPEA2: improving the strength Pareto evolutionary algorithm
    • Optimisation and Control with Application to Industrial Problems (EUROGEN 2001), International Centre for Numerical Methods in Engineering (CIMNE), Athens
    • E. Zitzler, M. Laumanns, L. Thiele, SPEA2: improving the strength Pareto evolutionary algorithm, in: Evolutionary Methods for Design, Optimisation and Control with Application to Industrial Problems (EUROGEN 2001), International Centre for Numerical Methods in Engineering (CIMNE), Athens, 2002, pp. 95-100.
    • (2002) Evolutionary Methods for Design , pp. 95-100
    • Zitzler, E.1    Laumanns, M.2    Thiele, L.3
  • 12
    • 0001953837 scopus 로고
    • Genetic algorithms for multiobjective optimization: formulation, discussion and generalization
    • Morgan Kaufmann Publisher, San Francisco, CA, USA
    • C.M. Fonseca, P.J. Fleming, et al., Genetic algorithms for multiobjective optimization: formulation, discussion and generalization, in: Proceedings of the 5th Conference on Genetic Algorithms, Morgan Kaufmann Publisher, San Francisco, CA, USA, 1993, pp. 416-423.
    • (1993) Proceedings of the 5th Conference on Genetic Algorithms , pp. 416-423
    • Fonseca, C.M.1    Fleming, P.J.2
  • 13
    • 0034199912 scopus 로고    scopus 로고
    • Approximating the nondominated front using the Pareto archived evolution strategy
    • Knowles J.D., Corne D.W. Approximating the nondominated front using the Pareto archived evolution strategy. Evol. Comput. 2000, 8(2):149-172.
    • (2000) Evol. Comput. , vol.8 , Issue.2 , pp. 149-172
    • Knowles, J.D.1    Corne, D.W.2
  • 16
    • 0033318858 scopus 로고    scopus 로고
    • Multiobjective evolutionary algorithms: a comparative case study and the strength Pareto approach
    • Zitzler E., Thiele L. Multiobjective evolutionary algorithms: a comparative case study and the strength Pareto approach. IEEE Trans. Evol. Comput. 1999, 3(4):257-271.
    • (1999) IEEE Trans. Evol. Comput. , vol.3 , Issue.4 , pp. 257-271
    • Zitzler, E.1    Thiele, L.2
  • 18
    • 33947669974 scopus 로고    scopus 로고
    • SMS-EMOA: multiobjective selection based on dominated hypervolume
    • Beume N., Naujoks B., Emmerich M. SMS-EMOA: multiobjective selection based on dominated hypervolume. Eur. J. Oper. Res. 2007, 181(3):1653-1669.
    • (2007) Eur. J. Oper. Res. , vol.181 , Issue.3 , pp. 1653-1669
    • Beume, N.1    Naujoks, B.2    Emmerich, M.3
  • 19
    • 79951564654 scopus 로고    scopus 로고
    • HypE: an algorithm for fast hypervolume-based many-objective optimization
    • Bader J., Zitzler E. HypE: an algorithm for fast hypervolume-based many-objective optimization. Evol. Comput. 2011, 19(1):45-76.
    • (2011) Evol. Comput. , vol.19 , Issue.1 , pp. 45-76
    • Bader, J.1    Zitzler, E.2
  • 20
    • 34548108555 scopus 로고    scopus 로고
    • MOEA/D: a multiobjective evolutionary algorithm based on decomposition
    • Zhang Q., Li H. MOEA/D: a multiobjective evolutionary algorithm based on decomposition. IEEE Trans. Evol. Comput. 2007, 11(6):712-731.
    • (2007) IEEE Trans. Evol. Comput. , vol.11 , Issue.6 , pp. 712-731
    • Zhang, Q.1    Li, H.2
  • 21
    • 84901842799 scopus 로고    scopus 로고
    • Decomposition of a multiobjective optimization problem into a number of simple multiobjective subproblems
    • Liu H.-L., Gu F., Zhang Q. Decomposition of a multiobjective optimization problem into a number of simple multiobjective subproblems. IEEE Trans. Evol. Comput. 2014, 18(3):450-455.
    • (2014) IEEE Trans. Evol. Comput. , vol.18 , Issue.3 , pp. 450-455
    • Liu, H.-L.1    Gu, F.2    Zhang, Q.3
  • 22
    • 0032141635 scopus 로고    scopus 로고
    • A multi-objective genetic local search algorithm and its application to flowshop scheduling
    • Ishibuchi H., Murata T. A multi-objective genetic local search algorithm and its application to flowshop scheduling. IEEE Trans. Syst. Man Cybern. Part C: Appl. Rev. 1998, 28(3):392-403.
    • (1998) IEEE Trans. Syst. Man Cybern. Part C: Appl. Rev. , vol.28 , Issue.3 , pp. 392-403
    • Ishibuchi, H.1    Murata, T.2
  • 24
    • 84906947832 scopus 로고    scopus 로고
    • MOEA/D with opposition-based learning for multiobjective optimization problem
    • Ma X., Liu F., Qi Y., Gong M., Yin M., Li L., Jiao L., Wu J. MOEA/D with opposition-based learning for multiobjective optimization problem. Neurocomputing 2014, 146(1):48-64.
    • (2014) Neurocomputing , vol.146 , Issue.1 , pp. 48-64
    • Ma, X.1    Liu, F.2    Qi, Y.3    Gong, M.4    Yin, M.5    Li, L.6    Jiao, L.7    Wu, J.8
  • 25
    • 84888430701 scopus 로고    scopus 로고
    • ADEMO/D: multiobjective optimization by an adaptive differential evolution algorithm
    • Venske S.M., Gonalves R.A., Delgado M.R. ADEMO/D: multiobjective optimization by an adaptive differential evolution algorithm. Neurocomputing 2014, 127(0):65-77.
    • (2014) Neurocomputing , vol.127 , pp. 65-77
    • Venske, S.M.1    Gonalves, R.A.2    Delgado, M.R.3
  • 26
    • 40249102027 scopus 로고    scopus 로고
    • RM-MEDA: a regularity model based multiobjective estimation of distribution algorithm
    • Zhang Q., Zhou A., Jin Y. RM-MEDA: a regularity model based multiobjective estimation of distribution algorithm. IEEE Trans. Evol. Comput. 2008, 12(1):41-63.
    • (2008) IEEE Trans. Evol. Comput. , vol.12 , Issue.1 , pp. 41-63
    • Zhang, Q.1    Zhou, A.2    Jin, Y.3
  • 27
    • 59149098713 scopus 로고    scopus 로고
    • Rotated problems and rotationally invariant crossover in evolutionary multi-objective optimization
    • Iorio A., Li X. Rotated problems and rotationally invariant crossover in evolutionary multi-objective optimization. Int. J. Comput. Intell. Appl. 2008, 7(2):149-186.
    • (2008) Int. J. Comput. Intell. Appl. , vol.7 , Issue.2 , pp. 149-186
    • Iorio, A.1    Li, X.2
  • 28
    • 84901377430 scopus 로고    scopus 로고
    • Multiobjective evolutionary algorithm based on mixture Gaussian models
    • Zhou A., Zhang Q., Zhang G. Multiobjective evolutionary algorithm based on mixture Gaussian models. J. Softw. 2014, 25(5):913-928.
    • (2014) J. Softw. , vol.25 , Issue.5 , pp. 913-928
    • Zhou, A.1    Zhang, Q.2    Zhang, G.3
  • 29
    • 0345404396 scopus 로고    scopus 로고
    • The self-organizing map
    • Kohonen T. The self-organizing map. Neurocomputing 1998, 78(9):1-6.
    • (1998) Neurocomputing , vol.78 , Issue.9 , pp. 1-6
    • Kohonen, T.1
  • 30
    • 10644295753 scopus 로고    scopus 로고
    • Input determination for neural network models in water resources applications. Part 1. background and methodology
    • Bowden G.J., Dandy G.C., Maier H.R. Input determination for neural network models in water resources applications. Part 1. background and methodology. J. Hydrol. 2005, 301(1):75-92.
    • (2005) J. Hydrol. , vol.301 , Issue.1 , pp. 75-92
    • Bowden, G.J.1    Dandy, G.C.2    Maier, H.R.3
  • 31
    • 84906949014 scopus 로고    scopus 로고
    • A general framework for evolutionary multiobjective optimization via manifold learning
    • Li K., Kwong S. A general framework for evolutionary multiobjective optimization via manifold learning. Neurocomputing 2014, 146:65-74.
    • (2014) Neurocomputing , vol.146 , pp. 65-74
    • Li, K.1    Kwong, S.2
  • 32
    • 84901403917 scopus 로고    scopus 로고
    • Connectedness, regularity and the success of local search in evolutionary multi-objective optimization
    • IEEE
    • Y. Jin, B. Sendhoff, Connectedness, regularity and the success of local search in evolutionary multi-objective optimization, in: Proceedings of the IEEE Congress on Evolutionary Computation (CEC 2003), IEEE, 2003, pp. 1910-1917.
    • (2003) Proceedings of the IEEE Congress on Evolutionary Computation (CEC 2003) , pp. 1910-1917
    • Jin, Y.1    Sendhoff, B.2
  • 35
    • 70349855195 scopus 로고    scopus 로고
    • Approximating the set of Pareto-optimal solutions in both the decision and objective spaces by an estimation of distribution algorithm
    • Zhou A., Zhang Q., Jin Y. Approximating the set of Pareto-optimal solutions in both the decision and objective spaces by an estimation of distribution algorithm. IEEE Trans. Evol. Comput. 2009, 13(5):1167-1189.
    • (2009) IEEE Trans. Evol. Comput. , vol.13 , Issue.5 , pp. 1167-1189
    • Zhou, A.1    Zhang, Q.2    Jin, Y.3
  • 36
    • 70449817146 scopus 로고    scopus 로고
    • Hybrid multiobjective estimation of distribution algorithm by local linear embedding and an immune inspired algorithm
    • IEEE
    • D. Yang, L. Jiao, M. Gong, H. Feng, Hybrid multiobjective estimation of distribution algorithm by local linear embedding and an immune inspired algorithm, in: Proceedings of the IEEE Congress on Evolutionary Computation (CEC 2009), IEEE, 2009, pp. 463-470.
    • (2009) Proceedings of the IEEE Congress on Evolutionary Computation (CEC 2009) , pp. 463-470
    • Yang, D.1    Jiao, L.2    Gong, M.3    Feng, H.4
  • 38
    • 84865853865 scopus 로고    scopus 로고
    • A regularity model-based multiobjective estimation of distribution algorithm with reducing redundant cluster operator
    • Wang Y., Xiang J., Cai Z. A regularity model-based multiobjective estimation of distribution algorithm with reducing redundant cluster operator. Appl. Soft Comput. 2012, 12(11):3526-3538.
    • (2012) Appl. Soft Comput. , vol.12 , Issue.11 , pp. 3526-3538
    • Wang, Y.1    Xiang, J.2    Cai, Z.3
  • 40
    • 84902356973 scopus 로고    scopus 로고
    • Improved RM-MEDA with local learning
    • Li Y., Xu X., Li P., Jiao L. Improved RM-MEDA with local learning. Soft Comput. 2013, 18(7):1-15.
    • (2013) Soft Comput. , vol.18 , Issue.7 , pp. 1-15
    • Li, Y.1    Xu, X.2    Li, P.3    Jiao, L.4
  • 41
    • 84861872018 scopus 로고    scopus 로고
    • Multi-objective immune algorithm with Baldwinian learning
    • Qi Y., Liu F., Liu M., Gong M., Jiao L. Multi-objective immune algorithm with Baldwinian learning. Appl. Soft Comput. 2012, 12(8):2654-2674.
    • (2012) Appl. Soft Comput. , vol.12 , Issue.8 , pp. 2654-2674
    • Qi, Y.1    Liu, F.2    Liu, M.3    Gong, M.4    Jiao, L.5
  • 43
    • 84906818172 scopus 로고    scopus 로고
    • MOEA/D with Baldwinian learning inspired by the regularity property of continuous multiobjective problem
    • Ma X., Liu F., Qi Y., Li L., Jiao L., Liu M., Wu J. MOEA/D with Baldwinian learning inspired by the regularity property of continuous multiobjective problem. Neurocomputing 2014, 145:336-352.
    • (2014) Neurocomputing , vol.145 , pp. 336-352
    • Ma, X.1    Liu, F.2    Qi, Y.3    Li, L.4    Jiao, L.5    Liu, M.6    Wu, J.7
  • 44
    • 79955870988 scopus 로고    scopus 로고
    • A self organizing map based hybrid multi-objective optimization of water distribution networks
    • Norouzi K., Rakhshandehroo G. A self organizing map based hybrid multi-objective optimization of water distribution networks. IJST, Trans. Civil Environ. Eng. 2011, 35(C1):105-119.
    • (2011) IJST, Trans. Civil Environ. Eng. , vol.35 , Issue.C1 , pp. 105-119
    • Norouzi, K.1    Rakhshandehroo, G.2
  • 45
    • 84894596823 scopus 로고    scopus 로고
    • Imbalanced evolving self-organizing learning
    • Cai Q., He H., Man H. Imbalanced evolving self-organizing learning. Neurocomputing 2014, 133(8):258-270.
    • (2014) Neurocomputing , vol.133 , Issue.8 , pp. 258-270
    • Cai, Q.1    He, H.2    Man, H.3
  • 48
    • 67349096676 scopus 로고    scopus 로고
    • Multi-objective genetic local search algorithm using kohonens neural map
    • Hakimi-Asiabar M., Ghodsypour S.H., Kerachian R. Multi-objective genetic local search algorithm using kohonens neural map. Comput. Ind. Eng. 2009, 56(4):1566-1576.
    • (2009) Comput. Ind. Eng. , vol.56 , Issue.4 , pp. 1566-1576
    • Hakimi-Asiabar, M.1    Ghodsypour, S.H.2    Kerachian, R.3
  • 49
    • 78049288241 scopus 로고    scopus 로고
    • Deriving operating policies for multi-objective reservoir systems: application of self-learning genetic algorithm
    • Hakimi-Asiabar M., Ghodsypour S.H., Kerachian R. Deriving operating policies for multi-objective reservoir systems: application of self-learning genetic algorithm. Appl. Soft Comput. 2010, 10(4):1151-1163.
    • (2010) Appl. Soft Comput. , vol.10 , Issue.4 , pp. 1151-1163
    • Hakimi-Asiabar, M.1    Ghodsypour, S.H.2    Kerachian, R.3
  • 50
    • 84865339489 scopus 로고    scopus 로고
    • Low earth orbit regional satellite constellation design via self organization feature maps
    • Zhan W., Liu H., Dai G. Low earth orbit regional satellite constellation design via self organization feature maps. Int. J. Adv. Comput. Technol. 2012, 4(13).
    • (2012) Int. J. Adv. Comput. Technol. , vol.4 , Issue.13
    • Zhan, W.1    Liu, H.2    Dai, G.3
  • 51
    • 67349108023 scopus 로고    scopus 로고
    • Multiobjective optimization problems with complicated Pareto sets, MOEA/D and NSGA-II
    • Li H., Zhang Q. Multiobjective optimization problems with complicated Pareto sets, MOEA/D and NSGA-II. IEEE Trans. Evol. Comput. 2009, 13(2):284-302.
    • (2009) IEEE Trans. Evol. Comput. , vol.13 , Issue.2 , pp. 284-302
    • Li, H.1    Zhang, Q.2
  • 53
    • 84905158884 scopus 로고    scopus 로고
    • Generalized decomposition and cross entropy methods for many-objective optimization
    • Giagkiozis I., Purshouse R., Fleming P. Generalized decomposition and cross entropy methods for many-objective optimization. Inf. Sci. 2014, 282:363-387.
    • (2014) Inf. Sci. , vol.282 , pp. 363-387
    • Giagkiozis, I.1    Purshouse, R.2    Fleming, P.3
  • 54
    • 84875506104 scopus 로고    scopus 로고
    • Generalized decomposition
    • Lecture Notes in Computer Science, Springer, Berilin, Heidelberg
    • I. Giagkiozis, R. Purshouse, P. Fleming, Generalized decomposition, in: Evolutionary Multi-Criterion Optimization, Lecture Notes in Computer Science, Springer, Berilin, Heidelberg, 2013, pp. 428-442.
    • (2013) Evolutionary Multi-Criterion Optimization , pp. 428-442
    • Giagkiozis, I.1    Purshouse, R.2    Fleming, P.3
  • 55
    • 84861827549 scopus 로고    scopus 로고
    • Decomposition-based multiobjective evolutionary algorithm with an ensemble of neighborhood sizes
    • Zhao S.-Z., Suganthan P., Zhang Q. Decomposition-based multiobjective evolutionary algorithm with an ensemble of neighborhood sizes. IEEE Trans. Evol. Comput. 2012, 16(3):442-446.
    • (2012) IEEE Trans. Evol. Comput. , vol.16 , Issue.3 , pp. 442-446
    • Zhao, S.-Z.1    Suganthan, P.2    Zhang, Q.3
  • 56
    • 0034199979 scopus 로고    scopus 로고
    • Comparison of multiobjective evolutionary algorithms. empirical results
    • Zitzler E., Deb K., Thiele L. Comparison of multiobjective evolutionary algorithms. empirical results. Evol. Comput. 2000, 8(2):173-195.
    • (2000) Evol. Comput. , vol.8 , Issue.2 , pp. 173-195
    • Zitzler, E.1    Deb, K.2    Thiele, L.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.