Application of Differential Evolution and PA-jDE in chemical engineering problem

Abstract

In recent years, researchers have used optimization techniques to solve problemsmodelling real-world situations. Among these techniques, the ones that are most suitable for the complexity of these problems are stochastic optimization techniques. The algorithm of the Differential Evolution (DE) has shown itself suitable in its applicability in problems that describe real behaviors; this fact is an incentive for the researchers to look for means to improve its robustness and minimizing computational cost, using methods such as adaptive parameters, adaptive population. Researchers have presented results where it is noticeable the applicability of Differential Evolution in engineering problems. Therefore, this work aims to apply DE and a variant, Self-adapting Differential Evolution algorithm with population Adaptation (PA-jDE), in problems pertaining to the Chemical Engineering field. The results revealed a more rapid convergence of PA-jDE when compared to DE.