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Automatic Component-Wise Design of Multiobjective Evolutionary Algorithms

2015; Institute of Electrical and Electronics Engineers; Volume: 20; Issue: 3 Linguagem: Inglês

10.1109/tevc.2015.2474158

1941-0026

Leonardo C. T. Bezerra, Manuel López‐Ibáñez, Thomas Stützle,

Metaheuristic Optimization Algorithms Research

Multi-objective evolutionary algorithms are typically proposed, studied and applied as monolithic blocks with a few numerical parameters that need to be set.Few works have studied how the algorithmic components of these evolutionary algorithms can be classified and combined to produce new algorithmic designs.The motivation for studies of this latter type stem from the development of flexible software frameworks and the usage of automatic algorithm configuration methods to find novel algorithm designs.In this paper, we propose a multi-objective evolutionary algorithm template and a new conceptual view of its components that surpasses existing frameworks in both the number of algorithms that can be instantiated from the template and the flexibility to produce novel algorithmic designs.We empirically demonstrate the flexibility of our proposed framework by automatically designing multi-objective evolutionary algorithms for continuous and combinatorial optimization problems.The automatically designed algorithms are often able to outperform six traditional multi-objective evolutionary algorithms from the literature, even after tuning their numerical parameters.