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An empirical analysis of constraint handling on evolutionary multi-objective algorithms for the Environmental/Economic Load Dispatch problem

This paper analyses different multi-objective evolutionary algorithms to deal with the Environmental/Economic Load Dispatch (EELD). EELD is formulated as a multi-objective optimization problem in which two competing objectives (fuel cost and …

Extreme Learning Surrogate Models in Multi-objective Optimization based on Decomposition

This paper proposes ELMOEA/D, a surrogate-assisted MOEA, for solving costly multi-objective problems in small evaluation budgets. The proposed approach encompasses a state-of-the-art MOEA based on decomposition and Differential Evolution (MOEA/D-DE) …