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Methodology to select solutions from the pareto-optimal set: a comparative study.

, , and . GECCO, page 789-796. ACM, (2007)

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Robustness in multi-objective optimization using evolutionary algorithms., and . Comp. Opt. and Appl., 39 (1): 75-96 (2008)Financial distress model prediction using SVM+., , , , and . IJCNN, page 1-7. IEEE, (2010)Combining artificial neural networks and evolution to solve multiobjective knapsack problems., , and . GECCO (Companion), page 19-20. ACM, (2019)Weighted Stress Function Method for Multiobjective Evolutionary Algorithm Based on Decomposition., and . EMO, volume 10173 of Lecture Notes in Computer Science, page 176-190. Springer, (2017)A Real-World Test Problem for EMO Algorithms., and . EMO, volume 2632 of Lecture Notes in Computer Science, page 752-766. Springer, (2003)Competitive coevolutionary algorithm for robust multi-objective optimization: The worst case minimization., , and . CEC, page 586-593. IEEE, (2016)Feedback-control operators for improved Pareto-set description: Application to a polymer extrusion process., , , , and . Eng. Appl. of AI, (2015)Multiobjective evolutionary algorithm based on vector angle neighborhood., and . Swarm and Evolutionary Computation, (2017)Application of Evolutionary Algorithms to the Design of Barrier Screws for Single Screw Extruders., , and . WSC, volume 34 of Advances in Soft Computing, page 763-774. Springer, (2004)An integrated approach to automated innovization for discovering useful design principles: Case studies from engineering., , , , and . Appl. Soft Comput., (2014)