Combining CMA-ES and MOEA/DD for many-objective optimization
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Aurora Trinidad Ramirez Pozo | Roberto Santana | José Antonio Lozano | Olacir Rodrigues Castro Junior
[1] Kalyanmoy Deb,et al. A Fast Elitist Non-dominated Sorting Genetic Algorithm for Multi-objective Optimisation: NSGA-II , 2000, PPSN.
[2] R. Lyndon While,et al. A review of multiobjective test problems and a scalable test problem toolkit , 2006, IEEE Transactions on Evolutionary Computation.
[3] Hans-Paul Schwefel,et al. Evolution strategies – A comprehensive introduction , 2002, Natural Computing.
[4] Kalyanmoy Deb,et al. A fast and elitist multiobjective genetic algorithm: NSGA-II , 2002, IEEE Trans. Evol. Comput..
[5] Gary B. Lamont,et al. Evolutionary Algorithms for Solving Multi-Objective Problems (Genetic and Evolutionary Computation) , 2006 .
[6] Carlos A. Coello Coello,et al. Using the Averaged Hausdorff Distance as a Performance Measure in Evolutionary Multiobjective Optimization , 2012, IEEE Transactions on Evolutionary Computation.
[7] Saúl Zapotecas Martínez,et al. Injecting CMA-ES into MOEA/D , 2015, GECCO.
[8] Christian Igel,et al. Steady-State Selection and Efficient Covariance Matrix Update in the Multi-objective CMA-ES , 2007, EMO.
[9] Carlos A. Coello Coello,et al. Solving Multiobjective Optimization Problems Using an Artificial Immune System , 2005, Genetic Programming and Evolvable Machines.
[10] Qingfu Zhang,et al. MOEA/D: A Multiobjective Evolutionary Algorithm Based on Decomposition , 2007, IEEE Transactions on Evolutionary Computation.
[11] Aurora Trinidad Ramirez Pozo,et al. C-Multi: A competent multi-swarm approach for many-objective problems , 2016, Neurocomputing.
[12] 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.
[13] Qingfu Zhang,et al. Multiobjective Optimization Problems With Complicated Pareto Sets, MOEA/D and NSGA-II , 2009, IEEE Transactions on Evolutionary Computation.
[14] Nikolaus Hansen,et al. A restart CMA evolution strategy with increasing population size , 2005, 2005 IEEE Congress on Evolutionary Computation.
[15] W. Kruskal,et al. Use of Ranks in One-Criterion Variance Analysis , 1952 .
[16] Nikolaus Hansen,et al. Adapting arbitrary normal mutation distributions in evolution strategies: the covariance matrix adaptation , 1996, Proceedings of IEEE International Conference on Evolutionary Computation.
[17] 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).
[18] Kalyanmoy Deb,et al. Faster Hypervolume-Based Search Using Monte Carlo Sampling , 2008, MCDM.
[19] Aurora Trinidad Ramirez Pozo,et al. MOEA/D-GM: Using probabilistic graphical models in MOEA/D for solving combinatorial optimization problems , 2015, ArXiv.
[20] Aurora Trinidad Ramirez Pozo,et al. Transfer weight functions for injecting problem information in the multi-objective CMA-ES , 2016, Memetic Computing.
[21] Stefan Roth,et al. Covariance Matrix Adaptation for Multi-objective Optimization , 2007, Evolutionary Computation.
[22] Lucas Bradstreet,et al. A Fast Way of Calculating Exact Hypervolumes , 2012, IEEE Transactions on Evolutionary Computation.
[23] Concha Bielza,et al. A review on probabilistic graphical models in evolutionary computation , 2012, J. Heuristics.
[24] Nikolaus Hansen,et al. Injecting External Solutions Into CMA-ES , 2011, ArXiv.
[25] Marco Laumanns,et al. Scalable Test Problems for Evolutionary Multiobjective Optimization , 2005, Evolutionary Multiobjective Optimization.
[26] R. E. Lee,et al. Distribution-free multiple comparisons between successive treatments , 1995 .