Anais do Simpósio Brasileiro de Pesquisa Operacional
Anais do Simpósio Brasileiro de Pesquisa Operacional

This paper presents an evolutionary algorithm for multi-objective optimization problems, based on the Biased Random-Key Genetic Algorithm (BRKGA) and on the Elitist Non-dominated Sorting Genetic Algorithm (NSGA-II). Computational experiments applied to the Multi-Objective Multi-Dimensional Knapsack Problem compared our algorithm with other multi-objective metaheuristics algorithms from the literature, namely the NSGA-II, the Non-dominated Sorting Particle Swarm Optimization (NSPSO), the Multi-Objective Evolutionary Algorithm by Decomposition with Differential Evolution (MOEA/D-DE), the Multi-objective Hypervolume-based Ant Colony Optimizer (MHACO), and the Improved Harmony Search (IHS). The results show that our methodology obtained competitive results with respect to the hypervolumes from the obtained non-dominated fronts.