23 citations · 69 across the 6 of their papers we have counts for
4 papers · 1 filter
The Cone epsilon-Dominance: An Approach for Evolutionary Multiobjective Optimization
Lucas S. Batista, Felipe Campelo, Frederico G. Guimarães +1
We propose the cone epsilon-dominance approach to improve convergence and diversity in multiobjective evolutionary algorithms (MOEAs). A cone-eps-MOEA is presented and compared wit…
Tuning metaheuristics by sequential optimization of regression models
Áthila R. Trindade, Felipe Campelo
Tuning parameters is an important step for the application of metaheuristics to problem classes of interest. In this work we present a tuning framework based on the sequential opti…
Sample size estimation for power and accuracy in the experimental comparison of algorithms
Felipe Campelo, Fernanda Takahashi
Experimental comparisons of performance represent an important aspect of research on optimization algorithms. In this work we present a methodology for defining the required sample…
The MOEADr Package - A Component-Based Framework for Multiobjective Evolutionary Algorithms Based on Decomposition
Felipe Campelo, Lucas S. Batista, Claus Aranha
Multiobjective Evolutionary Algorithms based on Decomposition (MOEA/D) represent a widely used class of population-based metaheuristics for the solution of multicriteria optimizati…