Multi-Objective Optimization with an Adaptive Resonance Theory-Based Estimation of Distribution Algorithm: A Comparative Study
暂无分享,去创建一个
Jesús García | José M. Molina López | Luis Martí | Antonio Berlanga | Jesús García | J. M. Molina | A. Berlanga | Luis Martí
[1] Beat Kleiner,et al. Graphical Methods for Data Analysis , 1983 .
[2] David B. Fogel,et al. The Burden of Proof: Part II , 2008, WCCI.
[3] Karl-Heinz Waldmann,et al. Operations Research Proceedings 2006 , 2007 .
[4] H. B. Mann,et al. On a Test of Whether one of Two Random Variables is Stochastically Larger than the Other , 1947 .
[5] Carlos M. Fonseca,et al. An Improved Dimension-Sweep Algorithm for the Hypervolume Indicator , 2006, 2006 IEEE International Conference on Evolutionary Computation.
[6] David W. Corne,et al. Learning-assisted evolutionary search for scalable function optimization: LEM(ID3) , 2010, IEEE Congress on Evolutionary Computation.
[7] Gary B. Lamont,et al. Evolutionary Algorithms for Solving Multi-Objective Problems , 2002, Genetic Algorithms and Evolutionary Computation.
[8] Witold Kosiński,et al. Advances in Evolutionary Algorithms , 2008 .
[9] Marco Laumanns,et al. Performance assessment of multiobjective optimizers: an analysis and review , 2003, IEEE Trans. Evol. Comput..
[10] R. Lyndon While,et al. A faster algorithm for calculating hypervolume , 2006, IEEE Transactions on Evolutionary Computation.
[11] Lothar Thiele,et al. A Tutorial on the Performance Assessment of Stochastic Multiobjective Optimizers , 2006 .
[12] J. A. Lozano,et al. Towards a New Evolutionary Computation: Advances on Estimation of Distribution Algorithms (Studies in Fuzziness and Soft Computing) , 2006 .
[13] Peter J. Fleming,et al. On the Evolutionary Optimization of Many Conflicting Objectives , 2007, IEEE Transactions on Evolutionary Computation.
[14] Jonathan L. Shapiro,et al. Diversity Loss in General Estimation of Distribution Algorithms , 2006, PPSN.
[15] S. Grossberg. Studies of mind and brain : neural principles of learning, perception, development, cognition, and motor control , 1982 .
[16] Tobias Friedrich,et al. Approximating the Volume of Unions and Intersections of High-Dimensional Geometric Objects , 2008, ISAAC.
[17] David W. Corne,et al. The simplest evolution/learning hybrid: LEM with KNN , 2008, 2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence).
[18] R. Lyndon While,et al. A review of multiobjective test problems and a scalable test problem toolkit , 2006, IEEE Transactions on Evolutionary Computation.
[19] Jesús García,et al. Introducing MONEDA: scalable multiobjective optimization with a neural estimation of distribution algorithm , 2008, GECCO '08.
[20] Eckart Zitzler,et al. HypE: An Algorithm for Fast Hypervolume-Based Many-Objective Optimization , 2011, Evolutionary Computation.
[21] Riccardo Poli,et al. Genetic and Evolutionary Computation , 2006, Intelligenza Artificiale.
[22] Kalyanmoy Deb,et al. Faster Hypervolume-Based Search Using Monte Carlo Sampling , 2008, MCDM.
[23] John M. Chambers,et al. Graphical Methods for Data Analysis , 1983 .
[24] Kalyanmoy Deb,et al. On Handling a Large Number of Objectives A Posteriori and During Optimization , 2008, Multiobjective Problem Solving from Nature.
[25] M. E. Muller,et al. A Note on the Generation of Random Normal Deviates , 1958 .
[26] Qingfu Zhang,et al. An evolutionary algorithm with guided mutation for the maximum clique problem , 2005, IEEE Transactions on Evolutionary Computation.
[27] Nicola Beume,et al. S-Metric Calculation by Considering Dominated Hypervolume as Klee's Measure Problem , 2009, Evolutionary Computation.
[28] Nicola Beume,et al. SMS-EMOA: Multiobjective selection based on dominated hypervolume , 2007, Eur. J. Oper. Res..
[29] Martin Pelikan,et al. Scalable Optimization via Probabilistic Modeling: From Algorithms to Applications (Studies in Computational Intelligence) , 2006 .
[30] Moonis Ali,et al. Innovations in Applied Artificial Intelligence , 2005 .
[31] Ryszard S. Michalski,et al. LEARNABLE EVOLUTION MODEL: Evolutionary Processes Guided by Machine Learning , 2004, Machine Learning.
[32] Pedro Larrañaga,et al. GA-EDA: hybrid evolutionary algorithm using genetic and estimation of distribution algorithms , 2004 .
[33] Chang Wook Ahn,et al. Multiobjective real-coded bayesian optimization algorithmrevisited: diversity preservation , 2007, GECCO '07.
[34] Charles Gide,et al. Cours d'économie politique , 1911 .
[35] Stephen Grossberg,et al. Studies of mind and brain , 1982 .
[36] Carlos A. Coello Coello,et al. GIAA TECHNINAL REPORT GIAA2010E001 On Current Model-Building Methods for Multi-Objective Estimation of Distribution Algorithms: Shortcommings and Directions for Improvement , 2010 .
[37] Dirk Thierens,et al. The Naive MIDEA: A Baseline Multi-objective EA , 2005, EMO.
[38] Jyrki Wallenius,et al. Bibliometric Analysis of Multiple Criteria Decision Making/Multiattribute Utility Theory , 2008, MCDM.
[39] Kaisa Miettinen,et al. Nonlinear multiobjective optimization , 1998, International series in operations research and management science.
[40] Eckart Zitzler,et al. Dimensionality Reduction in Multiobjective Optimization: The Minimum Objective Subset Problem , 2006, OR.
[41] Theodor J. Stewart,et al. Real-World Applications of Multiobjective Optimization , 2008, Multiobjective Optimization.
[42] Selmer Bringsjord,et al. P=np , 2004, ArXiv.
[43] K. Deb,et al. On Finding Pareto-Optimal Solutions Through Dimensionality Reduction for Certain Large-Dimensional Multi-Objective Optimization Problems , 2022 .
[44] Chang Wook Ahn,et al. Advances in Evolutionary Algorithms: Theory, Design and Practice , 2006, Studies in Computational Intelligence.
[45] Gary B. Lamont,et al. Evolutionary Algorithms for Solving Multi-Objective Problems (Genetic and Evolutionary Computation) , 2006 .
[46] Johannes Bader,et al. Hypervolume-based search for multiobjective optimization: Theory and methods , 2010 .
[47] Nicola Beume,et al. Pareto-, Aggregation-, and Indicator-Based Methods in Many-Objective Optimization , 2007, EMO.
[48] James R. Williamson,et al. Gaussian ARTMAP: A Neural Network for Fast Incremental Learning of Noisy Multidimensional Maps , 1996, Neural Networks.
[49] Edmund K. Burke,et al. Parallel Problem Solving from Nature - PPSN IX: 9th International Conference, Reykjavik, Iceland, September 9-13, 2006, Proceedings , 2006, PPSN.
[50] Marcus Gallagher,et al. On the importance of diversity maintenance in estimation of distribution algorithms , 2005, GECCO '05.
[51] David E. Goldberg,et al. Multiobjective Estimation of Distribution Algorithms , 2006, Scalable Optimization via Probabilistic Modeling.
[52] Kim Fung Man,et al. Multiobjective Optimization , 2011, IEEE Microwave Magazine.
[53] Jesús García,et al. Moving away from error-based learning in multi-objective estimation of distribution algorithms , 2010, GECCO '10.