Investigation on the Differential Evolution driven by selected six chaotic systems in the task of reactor geometry optimization

In this paper, Differential Evolution (DE) is used in the task of optimization of batch reactor geometry. The novality of the approach is that the six selected discrete dissipative chaotic maps are used as the chaotic pseudo random number generator to drive the mutation and crossover process in the DE. The optimized results obtained are compared with original reactor geometry and process parameters adjustment. The statistical analysis of the results given by six versions of chaos driven DE is compared with canonical DE strategy.