Performance Comparison Of Evolutionary Techniques Enhanced By Lozi Chaotic Map In The Task Of Reactor Geometry Optimization
نویسندگان
چکیده
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.
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