Using multiobjective optimization algorithms and decision making support to solve polymer extrusion problems

Abstract

Single screw extrusion is a major polymer processing operation. Its optimization is crucial for producing good quality products at suitable costs. This study addresses extrusion as a multiobjective optimization problem that can be solved using evolutionary algorithms incorporating decision making and robustness strategies for selecting solutions. This approach enables focusing the search for solutions in favored regions where the preference was defined either by the relative importance of the objectives or determined considering the robustness of solutions against perturbations in the design variables. The outcome of this strategy provides not only a better insight into the problem at hand, but also facilitates the choice of a single solution for practical implementation. The usefulness of the approach is illustrated by several case studies involving the definition of the most adequate operating conditions, of the best screw geometry and the two together.