Abstract

The article describes a parallel gravitational search algorithm and its application to solving the inverse problem of chemical kinetics. The relevance of the study of metaheuristic algorithms, including the gravitational search algorithm, is given. It is shown that recently, these algorithms are becoming increasingly popular. The optimization problem is formulated on the example of solving the inverse kinetic problem. The process under study is propane pre-reforming over Ni catalyst, which is an industrially important chemical process. The description of the algorithm and its pseudocode are presented, after which the performance of the gravitational search algorithm is compared with other metaheuristic methods. The algorithm demonstrated its competitiveness, as a result of which it was applied to solve a specific industrial problem. Using this algorithm, the direct and inverse problems of chemical kinetics are solved, and the optimal values of the kinetic parameters of the reaction are found. It is proved that the model correctly describes the available experimental data.

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