RPSGAe - Reduced Pareto Set Genetic Algorithm : application to polymer extrusion

Publicado na serie "Lecture notes in economics and mathematical systems" ; 535In this paper a Multiobjective Optimization Genetic Algorithm, denoted as Reduced Pareto Set Genetic Algorithm with Elitism (RPSGAe), is presented and its performance is assessed. The algorithm is compared with other Evolutionary Multi-Objective Algorithms - EMOAs (SPEA2, PAES and NSGA-II) using problems from the literature and statistical comparison techniques. The results obtained showed that the RPSGAe algorithm has good overall performance. Finally, the RPSGAe algorithm was applied to the optimization of the polymer extrusion process. The aim is to implement an automatic optimization scheme capable of defining the values of important process parameters, such as operating conditions and screw geometry, yielding the best performance in terms of prescribed attributes. The results obtained for specific case studies have physical meaning and correspond to a successful process optimization