Titlebook: Evolutionary Multi-Criterion Optimization; 11th International C Hisao Ishibuchi,Qingfu Zhang,Aimin Zhou Conference proceedings 2021 Springe

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Approximating Pareto Fronts in Evolutionary Multiobjective Optimization with Large Population Sizethe approximation of PFs along some specific search directions. In this paper, we studied the extensions of two well-known algorithms (i.e., NSGA-II and MOEA/D) with the ability to find a large population of nondominated solutions with good spread. A region-based archiving method is also suggested t

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Embedding a Repair Operator in Evolutionary Single and Multi-objective Algorithms - An Exploitation-tive problems. The focus in this paper is to highlight the importance of restoring the exploitation-exploration balance, when a new operator is introduced. We show how different combinations of problems and EA characteristics pose different opportunities for restoration of this balance, enabling the

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An Online Machine Learning-Based Prediction Strategy for Dynamic Evolutionary Multi-objective OptimiFinally, the proposed prediction strategy is compared with three state-of-the-art prediction strategies under the same dynamic MOEA/D-DE framework on CEC2018 dynamic optimization competition problems. The experimental results indicate that the PAR-based prediction strategy is promising for dealing w

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