Multiple Surrogate-Assisted Many-Objective Optimization for Computationally Expensive Engineering Design

[1]  Tapabrata Ray,et al.  An Enhanced Decomposition-Based Evolutionary Algorithm With Adaptive Reference Vectors , 2018, IEEE Transactions on Cybernetics.

[2]  Kaisa Miettinen,et al.  A Surrogate-Assisted Reference Vector Guided Evolutionary Algorithm for Computationally Expensive Many-Objective Optimization , 2018, IEEE Transactions on Evolutionary Computation.

[3]  Tapabrata Ray,et al.  Decomposition Based Evolutionary Algorithm with a Dual Set of reference vectors , 2017, 2017 IEEE Congress on Evolutionary Computation (CEC).

[4]  Dipti Srinivasan,et al.  A Survey of Multiobjective Evolutionary Algorithms Based on Decomposition , 2017, IEEE Transactions on Evolutionary Computation.

[5]  Hisao Ishibuchi,et al.  Performance of Decomposition-Based Many-Objective Algorithms Strongly Depends on Pareto Front Shapes , 2017, IEEE Transactions on Evolutionary Computation.

[6]  Tapabrata Ray,et al.  A Novel Decomposition Based Evolutionary Algorithm for Engineering Design Optimization , 2017 .

[7]  Ye Tian,et al.  PlatEMO: A MATLAB Platform for Evolutionary Multi-Objective Optimization [Educational Forum] , 2017, IEEE Computational Intelligence Magazine.

[8]  Tapabrata Ray,et al.  Multi-Objective Optimization With Multiple Spatially Distributed Surrogates , 2016 .

[9]  Tapabrata Ray,et al.  Multiple surrogate assisted multiobjective optimization using improved pre-selection , 2016, 2016 IEEE Congress on Evolutionary Computation (CEC).

[10]  Tapabrata Ray,et al.  Use of Infeasible Solutions During Constrained Evolutionary Search: A Short Survey , 2016, ACALCI.

[11]  Xin Yao,et al.  A New Dominance Relation-Based Evolutionary Algorithm for Many-Objective Optimization , 2016, IEEE Transactions on Evolutionary Computation.

[12]  Bernhard Sendhoff,et al.  A Reference Vector Guided Evolutionary Algorithm for Many-Objective Optimization , 2016, IEEE Transactions on Evolutionary Computation.

[13]  Qingfu Zhang,et al.  An Evolutionary Many-Objective Optimization Algorithm Based on Dominance and Decomposition , 2015, IEEE Transactions on Evolutionary Computation.

[14]  Xin Yao,et al.  Many-Objective Evolutionary Algorithms , 2015, ACM Comput. Surv..

[15]  Tapabrata Ray,et al.  A Decomposition-Based Evolutionary Algorithm for Many Objective Optimization , 2015, IEEE Transactions on Evolutionary Computation.

[16]  Tapabrata Ray,et al.  Optimum Oil Production Planning Using Infeasibility Driven Evolutionary Algorithm , 2013, Evolutionary Computation.

[17]  T. Gal,et al.  Multicriteria Decision Making: Advances in MCDM Models, Algorithms, Theory, and Applications , 2012 .

[18]  Lucas Bradstreet,et al.  A Fast Way of Calculating Exact Hypervolumes , 2012, IEEE Transactions on Evolutionary Computation.

[19]  Kazuhiro Saitou,et al.  A Co-Evolutionary Approach for Design Optimization via Ensembles of Surrogates With Application to Vehicle Crashworthiness , 2012 .

[20]  Yaochu Jin,et al.  Surrogate-assisted evolutionary computation: Recent advances and future challenges , 2011, Swarm Evol. Comput..

[21]  Christopher A. Mattson,et al.  A Computationally Assisted Methodology for Preference-Guided Conceptual Design , 2010 .

[22]  Hisao Ishibuchi,et al.  Many-Objective Test Problems to Visually Examine the Behavior of Multiobjective Evolution in a Decision Space , 2010, PPSN.

[23]  Tapabrata Ray,et al.  Multi-objective design optimisation using multiple adaptive spatially distributed surrogates , 2009 .

[24]  Hirotaka Nakayama,et al.  Meta-Modeling in Multiobjective Optimization , 2008, Multiobjective Optimization.

[25]  Nicola Beume,et al.  Scalarization versus indicator-based selection in multi-objective CMA evolution strategies , 2008, 2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence).

[26]  Hisao Ishibuchi,et al.  Evolutionary many-objective optimization: A short review , 2008, 2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence).

[27]  Qingfu Zhang,et al.  MOEA/D: A Multiobjective Evolutionary Algorithm Based on Decomposition , 2007, IEEE Transactions on Evolutionary Computation.

[28]  R. Haftka,et al.  Ensemble of surrogates , 2007 .

[29]  G. Gary Wang,et al.  Review of Metamodeling Techniques in Support of Engineering Design Optimization , 2007, DAC 2006.

[30]  R. Lyndon While,et al.  A review of multiobjective test problems and a scalable test problem toolkit , 2006, IEEE Transactions on Evolutionary Computation.

[31]  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.

[32]  Leo Breiman,et al.  Bagging Predictors , 1996, Machine Learning.

[33]  Marco Laumanns,et al.  Scalable Test Problems for Evolutionary Multiobjective Optimization , 2005, Evolutionary Multiobjective Optimization.

[34]  Yaochu Jin,et al.  A comprehensive survey of fitness approximation in evolutionary computation , 2005, Soft Comput..

[35]  Salvador Pintos,et al.  An Optimization Methodology of Alkaline-Surfactant-Polymer Flooding Processes Using Field Scale Numerical Simulation and Multiple Surrogates , 2005 .

[36]  T. Simpson,et al.  Comparative studies of metamodelling techniques under multiple modelling criteria , 2001 .

[37]  Yoram Singer,et al.  Boosting Applied to Tagging and PP Attachment , 1999, EMNLP.

[38]  Kaisa Miettinen,et al.  Nonlinear multiobjective optimization , 1998, International series in operations research and management science.

[39]  John E. Dennis,et al.  Normal-Boundary Intersection: A New Method for Generating the Pareto Surface in Nonlinear Multicriteria Optimization Problems , 1998, SIAM J. Optim..