Algorithm in the fluidized-bed reactor for the polymerization of propylene

Abstract

A modified artificial bee optimization is proposed in this study. The algorithm is based on the colony behavior of certain bee species to achieve optimal solution in the bounded environment. The proposed algorithm is designed by improving the exploration knowledge of onlooker bee from meta-heuristic concept in search space. The multiple searches is proposed in the exploration phase to evaluate the multi objective functions. The performance of the proposed algorithm is tested on the typical benchmark equations and complex case of the polymerization of propylene in fluidized bed reactor. The proposed technique is able to provide an optimal solutions and it shows a good performance in term of convergence, accuracy and computational load.