"Statistics"

ELMOEA/D-DE: Extreme Learning Surrogate Models in Multi-objective Optimization Based on Decomposition and Differential Evolution

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 …

Harmony Search for Multi-objective Optimization

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) …