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 …
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) …
Despite the success of Evolutionary Algorithms in solving complex problems, they may require many function evaluations. This becomes an issue when dealing with costly problems. Surrogate models may overcome this difficulty, though their use in …
This paper investigates the efficiency of Harmony Search based algorithms for solving multi-objetive problems. For this task, four variants of the Harmony Search algorithm were adapted in the Non-dominated Sorting Genetic Algorithm II (NSGA-II) …