Application of Honey-Bee Mating Optimization to Naphtha Reforming Reactor

Abstract

Abstract Modeling and optimization of the process of continuous catalytic reforming (CCR) of naphtha was investigated. The process model is based on a network of four main reactions which was proved to be quite effective in terms of industrial application. Temperatures of the inlet of four reactors were selected as the decision variables. The honey-bee mating optimization (HBMO) and the genetic algorithm (GA) were applied to solve the optimization problem and the results of these two methods were compared. The profit was considered as the objective function which was subject to maximization. Optimization of the CCR moving bed reactors to reach maximum profit was carried out by the HBMO algorithm and the inlet temperature reactors were considered as decision variables. The optimization results showed that an increase of 3.01% in the profit can be reached based on the results of the HBMO algorithm. Comparison of the performance of optimization by the HBMO and the GA for the naphtha reforming model showed that the HBMO is an effective and rapid converging technique which can reach a better optimum results than the GA. The results showed that the HBMO has a better performance than the GA in finding the global optimum with fewer number of objective function evaluations. Also, it was shown that the HBMO is less likely to get stuck in a local optimum.