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Parallel Gravitational Search Algorithm in Solving the Inverse Problem of Chemical Kinetics. / Enikeeva, Leniza; Marchenko, Mikhail; Smirnov, Dmitrii et al.

Supercomputing - 6th Russian Supercomputing Days, RuSCDays 2020, Revised Selected Papers. ed. / Vladimir Voevodin; Sergey Sobolev. Springer Science and Business Media Deutschland GmbH, 2020. p. 98-109 (Communications in Computer and Information Science; Vol. 1331).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review

Harvard

Enikeeva, L, Marchenko, M, Smirnov, D & Gubaydullin, I 2020, Parallel Gravitational Search Algorithm in Solving the Inverse Problem of Chemical Kinetics. in V Voevodin & S Sobolev (eds), Supercomputing - 6th Russian Supercomputing Days, RuSCDays 2020, Revised Selected Papers. Communications in Computer and Information Science, vol. 1331, Springer Science and Business Media Deutschland GmbH, pp. 98-109, 6th Russian Supercomputing Days, RuSCDays 2020, Moscow, Russian Federation, 21.09.2020. https://doi.org/10.1007/978-3-030-64616-5_9

APA

Enikeeva, L., Marchenko, M., Smirnov, D., & Gubaydullin, I. (2020). Parallel Gravitational Search Algorithm in Solving the Inverse Problem of Chemical Kinetics. In V. Voevodin, & S. Sobolev (Eds.), Supercomputing - 6th Russian Supercomputing Days, RuSCDays 2020, Revised Selected Papers (pp. 98-109). (Communications in Computer and Information Science; Vol. 1331). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-64616-5_9

Vancouver

Enikeeva L, Marchenko M, Smirnov D, Gubaydullin I. Parallel Gravitational Search Algorithm in Solving the Inverse Problem of Chemical Kinetics. In Voevodin V, Sobolev S, editors, Supercomputing - 6th Russian Supercomputing Days, RuSCDays 2020, Revised Selected Papers. Springer Science and Business Media Deutschland GmbH. 2020. p. 98-109. (Communications in Computer and Information Science). doi: 10.1007/978-3-030-64616-5_9

Author

Enikeeva, Leniza ; Marchenko, Mikhail ; Smirnov, Dmitrii et al. / Parallel Gravitational Search Algorithm in Solving the Inverse Problem of Chemical Kinetics. Supercomputing - 6th Russian Supercomputing Days, RuSCDays 2020, Revised Selected Papers. editor / Vladimir Voevodin ; Sergey Sobolev. Springer Science and Business Media Deutschland GmbH, 2020. pp. 98-109 (Communications in Computer and Information Science).

BibTeX

@inproceedings{6a53c3f742d342dcacf851abe4e47b01,
title = "Parallel Gravitational Search Algorithm in Solving the Inverse Problem of Chemical Kinetics",
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.",
keywords = "Chemical kinetics, Global optimization, Gravitational search algorithm, Mathematical modeling, Metaheuristic algorithm, Parallel computing technologies",
author = "Leniza Enikeeva and Mikhail Marchenko and Dmitrii Smirnov and Irek Gubaydullin",
note = "Funding Information: Acknowledgements. The reported study was funded by RFBR, project number 19-37-60014 (mathematical modeling) and project number 18-01-00599 (parallel implementation). Publisher Copyright: {\textcopyright} 2020, Springer Nature Switzerland AG. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.; 6th Russian Supercomputing Days, RuSCDays 2020 ; Conference date: 21-09-2020 Through 22-09-2020",
year = "2020",
doi = "10.1007/978-3-030-64616-5_9",
language = "English",
isbn = "9783030646158",
series = "Communications in Computer and Information Science",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "98--109",
editor = "Vladimir Voevodin and Sergey Sobolev",
booktitle = "Supercomputing - 6th Russian Supercomputing Days, RuSCDays 2020, Revised Selected Papers",
address = "Germany",

}

RIS

TY - GEN

T1 - Parallel Gravitational Search Algorithm in Solving the Inverse Problem of Chemical Kinetics

AU - Enikeeva, Leniza

AU - Marchenko, Mikhail

AU - Smirnov, Dmitrii

AU - Gubaydullin, Irek

N1 - Funding Information: Acknowledgements. The reported study was funded by RFBR, project number 19-37-60014 (mathematical modeling) and project number 18-01-00599 (parallel implementation). Publisher Copyright: © 2020, Springer Nature Switzerland AG. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.

PY - 2020

Y1 - 2020

N2 - 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.

AB - 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.

KW - Chemical kinetics

KW - Global optimization

KW - Gravitational search algorithm

KW - Mathematical modeling

KW - Metaheuristic algorithm

KW - Parallel computing technologies

UR - http://www.scopus.com/inward/record.url?scp=85097832032&partnerID=8YFLogxK

U2 - 10.1007/978-3-030-64616-5_9

DO - 10.1007/978-3-030-64616-5_9

M3 - Conference contribution

AN - SCOPUS:85097832032

SN - 9783030646158

T3 - Communications in Computer and Information Science

SP - 98

EP - 109

BT - Supercomputing - 6th Russian Supercomputing Days, RuSCDays 2020, Revised Selected Papers

A2 - Voevodin, Vladimir

A2 - Sobolev, Sergey

PB - Springer Science and Business Media Deutschland GmbH

T2 - 6th Russian Supercomputing Days, RuSCDays 2020

Y2 - 21 September 2020 through 22 September 2020

ER -

ID: 27341713