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An EA-based approach to design optimization using evidence theory.

, and . GECCO, page 1139-1146. ACM, (2011)

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A Reliable Classification of Gene Clusters for Cancer Samples Using a Hybrid Multi-Objective Evolutionary Procedure., , and . Analysis of Biological Data: A Soft Computing Approach, volume 3 of Science, Engineering, and Biology Informatics, World Scientific, (2007)What Makes a Problem Hard for a Classifier System?, , and . IlliGAL Report No 92007. Department of General Engineering, 117 Transportation Building, 104 South Mathews Avenue, Urbana, IL 61801-2996, (1992)Discrete Time-Cost Tradeoff with a Novel Hybrid Meta-Heuristic., , , and . MCDM, volume 634 of Lecture notes in economics and mathematical systems, page 177-188. Springer, (2008)Uniform adaptive scaling of equality and inequality constraints within hybrid evolutionary-cum-classical optimization., and . Soft Comput., 20 (6): 2367-2382 (2016)Data mining methods for knowledge discovery in multi-objective optimization: Part A - Survey., , and . Expert Syst. Appl., (2017)Classifying Metamodeling Methods for Evolutionary Multi-objective Optimization: First Results., , , and . EMO, volume 10173 of Lecture Notes in Computer Science, page 160-175. Springer, (2017)An integrated approach to automated innovization for discovering useful design principles: Case studies from engineering., , , , and . Appl. Soft Comput., (2014)Worst-case conditional hardness and fast algorithms with random inputs for non-dominated sorting., , , , and . GECCO Companion, page 185-186. ACM, (2020)Gap finding and validation in evolutionary multi- and many-objective optimization., , , and . GECCO, page 578-586. ACM, (2020)Towards sustainable forest management strategies with MOEAs., , , , , and . GECCO, page 1046-1054. ACM, (2020)