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Using Clustering Techniques to Improve the Performance of a Multi-objective Particle Swarm Optimizer., and . GECCO (1), volume 3102 of Lecture Notes in Computer Science, page 225-237. Springer, (2004)Use of a goal-constraint-based approach for finding the region of interest in multi-objective problems., , and . J. Heuristics, 25 (1): 107-139 (2019)Business-driven policy optimization for service management., , , , , , and . Int. J. Netw. Manag., 25 (2): 113-140 (2015)Two novel approaches for many-objective optimization., , and . IEEE Congress on Evolutionary Computation, page 1-8. IEEE, (2010)Instance Selection Based on Linkage Trees., , and . CCE, page 1-6. IEEE, (2021)A Long-term Memory Approach for Dynamic Multiobjective Evolutionary Algorithms., , and . IJCCI (ECTA-FCTA), page 333-337. SciTePress, (2011)A Comparative Study of Neighborhood Topologies for Particle Swarm Optimizers., , and . IJCCI, page 152-159. INSTICC Press, (2009)Handling Dynamic Multiobjective Problems with Particle Swarm Optimization., , and . ICAART (1), page 337-342. INSTICC Press, (2010)Evolutionary Instance Selection Based on Preservation of the Data Probability Density Function., , and . Computación y Sistemas, (2022)A Taxonomy for Metamodeling Frameworks for Evolutionary Multiobjective Optimization., , , and . IEEE Trans. Evol. Comput., 23 (1): 104-116 (2019)