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

Carrano, Eduardo G.; Gouveia Coelho, Dayanne; Gaspar-Cunha, António; Wanner, Elizabeth F. and Takahashi, Ricardo H.C. (2015). Feedback-control operators for improved Pareto-set description:application to a polymer extrusion process. Engineering Applications of Artificial Intelligence, 38 , pp. 147-167.

Abstract

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.

Publication DOI: https://doi.org/10.1016/j.engappai.2014.10.016
Divisions: Engineering & Applied Sciences
Uncontrolled Keywords: evolutionary computation,genetic algorithms,local search,multiobjective optimization,polymer extrusion,Control and Systems Engineering,Artificial Intelligence,Electrical and Electronic Engineering
Published Date: 2015-02

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