MB-GNG: Addressing drawbacks in multi-objective optimization estimation of distribution algorithms

Operations Research Letters

Volumn 39, Issue 2, 2011, Pages 150-154

  Martí, Luis ^a   Garca, Jesús ^a   Berlanga, Antonio ^a   Coello Coello, Carlos A ^b   Molina, José M ^a  

^a UNIVERSIDAD CARLOS III DE MADRID   (Spain)

^b DEPARTAMENTO DE FÍSICA   (Mexico)

Author keywords

Estimation of distribution algorithm; Growing neural gas; Model building; Multi objective optimization

Indexed keywords

ESTIMATION OF DISTRIBUTION ALGORITHMS; GROWING NEURAL GAS; MULTI OBJECTIVE; OPTIMIZATION PROBLEMS;

ESTIMATION; EVOLUTIONARY ALGORITHMS; HEURISTIC ALGORITHMS; MODEL BUILDINGS;

MULTIOBJECTIVE OPTIMIZATION;

EID: 79953065576     PISSN: 01676377     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.orl.2011.01.002     Document Type: Article

References (16)

1. C.W. Ahn, and R.S. Ramakrishna Multiobjective real-coded Bayesian optimization algorithm revisited: Diversity preservation GECCO07: Proceedings of the 9th Annual Conference on Genetic and Evolutionary Computation 2007 ACM Press New York, NY, USA 593 600 (Pubitemid 47291583)
2. T. Bck Evolutionary Algorithms in Theory and Practice 1996 Oxford University Press New York, Oxford
3. P.A.N. Bosman, and D. Thierens The balance between proximity and diversity in multiobjective evolutionary algorithms IEEE Transactions on Evolutionary Computation 7 2003 174 188
4. J. Branke, K. Miettinen, K. Deb, R. Sowinski, Multiobjective Optimization Lecture Notes in Computer Science vol. 5252 2008 Springer-Verlag Berlin/Heidelberg
5. C.A. Coello Coello, G.B. Lamont, and D.A. Van Veldhuizen Evolutionary algorithms for solving multi-objective problems Genetic and Evolutionary Computation 2nd ed. 2007 Springer New York
6. W.J. Conover Practical Nonparametric Statistics 3rd ed. 1999 John Wiley & Sons New York
7. P. Dagum, and M. Luby Approximating probabilistic inference in Bayesian belief networks is NP-hard Artificial Intelligence 60 1993 141 153 (Pubitemid 23622908)
8. B. Fritzke A growing neural gas network learns topologies G. Tesauro, D.S. Touretzky, T.K. Leen, Advances in Neural Information Processing Systems vol. 7 1995 MIT Press Cambridge, MA 625 632
9. C. Igel, N. Hansen, and S. Roth Covariance matrix adaptation for multi-objective optimization Evolutionary Computation 15 2007 1 28
10. T.M. Martinetz, S.G. Berkovich, and K.J. Shulten Neural-gas network for vector quantization and its application to time-series prediction IEEE Transactions on Neural Networks 4 1993 558 560
11. M. Pelikan, K. Sastry, and D.E. Goldberg Multiobjective estimation of distribution algorithms M. Pelikan, K. Sastry, E. Cant-Paz, Scalable Optimization via Probabilistic Modeling: From Algorithms to Applications Studies in Computational Intelligence 2006 Springer-Verlag 223 248
12. A.K. Qin, and P.N. Suganthan Robust growing neural gas algorithm with application in cluster analysis Neural Networks 17 2004 1135 1148 (Pubitemid 39539533)
13. J. Shapiro, Diversity loss in general estimation of distribution algorithms, in: Parallel Problem Solving from Nature (PPSN IX), pp. 92101.
14. T.J. Stewart, O. Bandte, H. Braun, N. Chakraborti, M. Ehrgott, M. Gbelt, Y. Jin, H. Nakayama, S. Poles, and D. Di Stefano Real-world applications of multiobjective optimization J. Branke, M. Kaisa, K. Deb, R. Sowinski, Multiobjective Optimization Lecture Notes in Computer Science vol. 5252 2008 Springer-Verlag Berlin/Heidelberg 285 327
15. R. Xu, and D. Wunsch II Clustering IEEE Press Series on Computational Intelligence illustrated ed. 2008 Wiley, IEEE Press New York
16. Q. Zhang, A. Zhou, and Y. Jin RM-MEDA: A regularity model-based multiobjective estimation of distribution algorithm IEEE Transactions on Evolutionary Computation 12 2008 41 63 (Pubitemid 351330331)