Feedback-control operators for improved Pareto-set description : application to a polymer extrusion process.

• Autor(a) principal: Carrano, Eduardo Gontijo
• Data de Publicação: 2015
• Outros Autores: Coelho, Dayanne Gouveia, Cunha, António Gaspar, Wanner, Elizabeth Fialho, Takahashi, Ricardo Hiroshi Caldeira
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Institucional da UFOP
• Texto Completo: http://www.repositorio.ufop.br/handle/123456789/7018; https://doi.org/10.1016/j.engappai.2014.10.016
• topic: Evolutionary computation; Multiobjective optimization; Genetic algorithms; Polymer extrusion; Local search

This paper presents a new class of operators for multiobjective evolutionary algorithms that are inspired on feedback-control techniques. The proposed operators, the archive-set reduction and the surface-filling crossover, have the purpose of enhancing the quality of the description of the Pareto-set in multiobjective optimization problems. They act on the Pareto -estimate sample set, performing operations that eliminate archive points in the most crowded regions, and generate new points in the less populated regions, leading to a dynamic equilibrium that tends to generate a uniform sampling of the efficient solution set. The internal parameters of those operators are coordinated by feedback-control inspired techniques, which ensure that the desired equilibrium is attained. Numerical experiments in some benchmark problems and in a real problem of optimization of a single screw extrusion system for polymer processing show that the proposed methodology is able to generate more detailed descriptions of Pareto-optimal fronts than the ones produced by usual algorithms.