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Machine learning based decision support for many-objective optimization problems.

, , , and . Neurocomputing, (2014)

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Combining Simple and Adaptive Monte Carlo Methods for Approximating Hypervolume., and . IEEE Trans. Evol. Comput., 24 (5): 896-907 (2020)Objective Extraction for Simplifying Many-Objective Solution Sets., , , and . IEEE Trans. Emerg. Top. Comput. Intell., 8 (1): 337-349 (February 2024)Approximating the Set of Pareto-Optimal Solutions in Both the Decision and Objective Spaces by an Estimation of Distribution Algorithm., , and . IEEE Trans. Evol. Comput., 13 (5): 1167-1189 (2009)Constrained Subproblems in a Decomposition-Based Multiobjective Evolutionary Algorithm., , , , and . IEEE Trans. Evol. Comput., 20 (3): 475-480 (2016)Offline and Online Objective Reduction via Gaussian Mixture Model Clustering., , , and . IEEE Trans. Evol. Comput., 27 (2): 341-354 (April 2023)Heuristics for Vehicle Routing Problem: A Survey and Recent Advances., , , , , and . CoRR, (2023)Special issue on The 17th Annual UK Workshop on Computational Intelligence., and . Soft Comput., 22 (21): 6965-6966 (2018)Nonlinear Collaborative Scheme for Deep Neural Networks., , , , , and . CoRR, (2018)Smooth Tchebycheff Scalarization for Multi-Objective Optimization., , , , , and . CoRR, (2024)A Batched Scalable Multi-Objective Bayesian Optimization Algorithm., , , , and . CoRR, (2018)