Engineering an efficient two-phase local search algorithm for the co-rotating twin-screw extruder configuration problem

Abstract

The twin-screw configuration problem arises during polymer extrusion and compounding. It consists in defining the location of a set of pre-defined screw elements along the screw axis in order to optimize different, typically conflicting objectives. In this paper, we present a simple yet effective stochastic local search (SLS) algorithm for this problem. Our algorithm is based on efficient single-objective iterative improvement algorithms, which have been developed by studying different neighborhood structures, neighborhood search strategies, and neighborhood restrictions. These algorithms are embedded into a variation of the two-phase local search framework to tackle various bi-objective versions of this problem. An experimental comparison with a previously proposed multi-objective evolutionary algorithm shows that a main advantage of our SLS algorithm is that it converges faster to a high-quality approximation to the Pareto front.