A Surrogate-Assisted Reference Vector Guided Evolutionary Algorithm for Computationally Expensive Many-Objective Optimization
暂无分享,去创建一个
Kaisa Miettinen | Yaochu Jin | Tinkle Chugh | Jussi Hakanen | Karthik Sindhya | Yaochu Jin | K. Miettinen | Jussi Hakanen | K. Sindhya | Tinkle Chugh | Karthik Sindhya
[1] Kaisa Miettinen,et al. A survey on handling computationally expensive multiobjective optimization problems with evolutionary algorithms , 2017, Soft Computing.
[2] Bo Zhang,et al. Balancing Convergence and Diversity in Decomposition-Based Many-Objective Optimizers , 2016, IEEE Transactions on Evolutionary Computation.
[3] Bernhard Sendhoff,et al. A Reference Vector Guided Evolutionary Algorithm for Many-Objective Optimization , 2016, IEEE Transactions on Evolutionary Computation.
[4] Ye Tian,et al. A Knee Point-Driven Evolutionary Algorithm for Many-Objective Optimization , 2015, IEEE Transactions on Evolutionary Computation.
[5] Qingfu Zhang,et al. An Evolutionary Many-Objective Optimization Algorithm Based on Dominance and Decomposition , 2015, IEEE Transactions on Evolutionary Computation.
[6] Kiyoshi Tanaka,et al. Evolutionary many-objective optimization using dynamic ε-Hoods and Chebyshev function , 2015, 2015 IEEE Congress on Evolutionary Computation (CEC).
[7] Gexiang Zhang,et al. A Many-Objective Evolutionary Algorithm With Enhanced Mating and Environmental Selections , 2015, IEEE Transactions on Evolutionary Computation.
[8] Kazuyuki Murase,et al. Evolutionary Path Control Strategy for Solving Many-Objective Optimization Problem , 2015, IEEE Transactions on Cybernetics.
[9] Bernhard Sendhoff,et al. A Multiobjective Evolutionary Algorithm Using Gaussian Process-Based Inverse Modeling , 2015, IEEE Transactions on Evolutionary Computation.
[10] Tom Dhaene,et al. Fast calculation of multiobjective probability of improvement and expected improvement criteria for Pareto optimization , 2014, J. Glob. Optim..
[11] Kalyanmoy Deb,et al. An Evolutionary Many-Objective Optimization Algorithm Using Reference-Point-Based Nondominated Sorting Approach, Part I: Solving Problems With Box Constraints , 2014, IEEE Transactions on Evolutionary Computation.
[12] Lamjed Ben Said,et al. Steady state IBEA assisted by MLP neural networks for expensive multi-objective optimization problems , 2014, GECCO.
[13] Shigeru Obayashi,et al. Kriging model based many-objective optimization with efficient calculation of expected hypervolume improvement , 2014, 2014 IEEE Congress on Evolutionary Computation (CEC).
[14] Kalyanmoy Deb,et al. A review of hybrid evolutionary multiple criteria decision making methods , 2014, 2014 IEEE Congress on Evolutionary Computation (CEC).
[15] Carlos A. Brizuela,et al. A survey on multi-objective evolutionary algorithms for many-objective problems , 2014, Comput. Optim. Appl..
[16] Kishalay Mitra,et al. Multi-Objective Optimization of Bulk Vinyl Acetate Polymerization with Branching , 2014 .
[17] Roman Neruda,et al. Aggregate meta-models for evolutionary multiobjective and many-objective optimization , 2013, Neurocomputing.
[18] Neil D. Lawrence,et al. Gaussian Processes for Big Data , 2013, UAI.
[19] Vincenzo Catania,et al. A Study on Evolutionary Multi-Objective Optimization with Fuzzy Approximation for Computational Expensive Problems , 2012, PPSN.
[20] Kaname Narukawa,et al. Examining the Performance of Evolutionary Many-Objective Optimization Algorithms on a Real-World Application , 2012, 2012 Sixth International Conference on Genetic and Evolutionary Computing.
[21] Lucas Bradstreet,et al. A Fast Way of Calculating Exact Hypervolumes , 2012, IEEE Transactions on Evolutionary Computation.
[22] Roman Neruda,et al. Improving many-objective optimizers with aggregate meta-models , 2011, 2011 11th International Conference on Hybrid Intelligent Systems (HIS).
[23] Roman Neruda,et al. ASM-MOMA: Multiobjective memetic algorithm with aggregate surrogate model , 2011, 2011 IEEE Congress of Evolutionary Computation (CEC).
[24] Yaochu Jin,et al. Surrogate-assisted evolutionary computation: Recent advances and future challenges , 2011, Swarm Evol. Comput..
[25] Michèle Sebag,et al. Dominance-Based Pareto-Surrogate for Multi-Objective Optimization , 2010, SEAL.
[26] Wolfgang Ponweiser,et al. On Expected-Improvement Criteria for Model-based Multi-objective Optimization , 2010, PPSN.
[27] Qingfu Zhang,et al. Expensive Multiobjective Optimization by MOEA/D With Gaussian Process Model , 2010, IEEE Transactions on Evolutionary Computation.
[28] Carlos A. Coello Coello,et al. A Review of Techniques for Handling Expensive Functions in Evolutionary Multi-Objective Optimization , 2010 .
[29] R. K. Ursem. Multi-objective Optimization using Evolutionary Algorithms , 2009 .
[30] Wolfgang Ponweiser,et al. Multiobjective Optimization on a Limited Budget of Evaluations Using Model-Assisted -Metric Selection , 2008, PPSN.
[31] Hisao Ishibuchi,et al. Evolutionary many-objective optimization: A short review , 2008, 2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence).
[32] Qingfu Zhang,et al. MOEA/D: A Multiobjective Evolutionary Algorithm Based on Decomposition , 2007, IEEE Transactions on Evolutionary Computation.
[33] Michael T. M. Emmerich,et al. Single- and multiobjective evolutionary optimization assisted by Gaussian random field metamodels , 2006, IEEE Transactions on Evolutionary Computation.
[34] Hirotaka Nakayama,et al. Approximate Optimization Using Computaional Intelligence and its Application to Reinforcement of Cable-stayed Bridges , 2006, Integrated Intelligent Systems for Engineering Design.
[35] Joshua D. Knowles,et al. ParEGO: a hybrid algorithm with on-line landscape approximation for expensive multiobjective optimization problems , 2006, IEEE Transactions on Evolutionary Computation.
[36] Nikolaus Hansen,et al. The CMA Evolution Strategy: A Comparing Review , 2006, Towards a New Evolutionary Computation.
[37] R. Lyndon While,et al. A Scalable Multi-objective Test Problem Toolkit , 2005, EMO.
[38] Bernhard Sendhoff,et al. Reducing Fitness Evaluations Using Clustering Techniques and Neural Network Ensembles , 2004, GECCO.
[39] Dirk Thierens,et al. The balance between proximity and diversity in multiobjective evolutionary algorithms , 2003, IEEE Trans. Evol. Comput..
[40] M. Peruggia. Experiments with Mixtures: Designs, Models, and the Analysis of Mixture Data , 2003 .
[41] Bernhard Sendhoff,et al. A framework for evolutionary optimization with approximate fitness functions , 2002, IEEE Trans. Evol. Comput..
[42] Gary B. Lamont,et al. Evolutionary Algorithms for Solving Multi-Objective Problems , 2002, Genetic Algorithms and Evolutionary Computation.
[43] Marco Laumanns,et al. Scalable multi-objective optimization test problems , 2002, Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600).
[44] Kalyanmoy Deb,et al. A fast and elitist multiobjective genetic algorithm: NSGA-II , 2002, IEEE Trans. Evol. Comput..
[45] Søren Nymand Lophaven,et al. DACE - A Matlab Kriging Toolbox , 2002 .
[46] Bernhard Sendhoff,et al. On Evolutionary Optimization with Approximate Fitness Functions , 2000, GECCO.
[47] Richard J. Beckman,et al. A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output From a Computer Code , 2000, Technometrics.
[48] Kaisa Miettinen,et al. Nonlinear multiobjective optimization , 1998, International series in operations research and management science.
[49] Sydney Thomas. Measurement and Modelling of Long Chain Branching , 1998 .
[50] Rainer Storn,et al. Differential Evolution – A Simple and Efficient Heuristic for global Optimization over Continuous Spaces , 1997, J. Glob. Optim..
[51] Tsuyoshi Ando,et al. Majorization relations for Hadamard products , 1995 .
[52] John A. Nelder,et al. A Simplex Method for Function Minimization , 1965, Comput. J..
[53] Robert Hooke,et al. `` Direct Search'' Solution of Numerical and Statistical Problems , 1961, JACM.