Parallel Algorithm of Global Optimization and Its Use for Solving Inverse Problems of Chemical Kinetics

Authors

  • Konstantin A. Barkalov Lobachevsky State University of Nizhny Novgorod; Scientific and Educational Mathematical Center "Mathematics of Future Technologies"
  • Ekaterina N. Varseeva Lobachevsky State University of Nizhny Novgorod
  • Ilya G. Lebedev Lobachevsky State University of Nizhny Novgorod; Scientific and Educational Mathematical Center "Mathematics of Future Technologies"
  • Anna L. Khashper LLC "SIBINTEK-SOFT"
  • Artem S. Urlukov Catalysis Institute, Siberian Branch of the Russian Academy of Sciences; Novosibirsk State University
  • Irek M. Gubaydullin Institute of Petrochemistry and Catalysis
  • Iskander F. Khisametdinov Ufa State Petroleum Technological University

DOI:

https://doi.org/10.14529/cmse260202

Keywords:

global optimization, multi-extremal functions, parallel computing, chemical kinetics, inverse problems

Abstract

The article discusses the use of parallel computing for selecting parameters of a mathematical model of low-temperature steam conversion process of hydrocarbons contained in associated petroleum gas. For this chemical process, it is necessary to develop its kinetic model, i.e., determine the corresponding kinetic reaction parameters. To achieve this, an inverse problem is solved where values of kinetic parameters are sought based on experimental data. Mathematically, the inverse problem of chemical kinetics corresponds to a global optimization problem. A parallel information-statistical algorithm for global search combined with local refinement of the best solution was used to solve this problem. The algorithm is deterministic and relies on the assumption of Lipschitz continuity of the objective function, which is typical for many other approaches to constructing global optimization methods. In this case, solving multidimensional problems reduces to solving equivalent one-dimensional problems. The corresponding reduction is based on using a Peano curve that maps the unit interval of the real axis onto a hypercube. Parallelization of the algorithm is organized according to the "master-workers" scheme with shared memory usage. The found optimal model parameters allowed adequately simulating the process of low-temperature steam conversion of light hydrocarbons using a catalyst.

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Published

2026-09-22

Issue

Vol. 15 No. 2 (2026)

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