Performance comparison of evolutionary techniques enhanced by Lozi chaotic map in the task of reactor geometry optimization

Abstract

In this study the performance of two popular evolutionary computational techniques (particle swarm optimization and differential evolution) is compared in the task of batch reactor geometry optimization. Both algorithms are enhanced with chaotic pseudo-random number generator (CPRNG) based on Lozi chaotic map. It is depicted the course of the reactor processes dynamical parameters for the best obtained solutions for both algorithms and numerical values of cost functions are compared. The promising results are discussed. Proceedings 28th European Conference on Modelling and Simulation © ECMS Flaminio Squazzoni, Fabio Baronio, Claudia Archetti, Marco Castellani (Editors).