Standard

Bilevel Models for Investment Policy in Resource-Rich Regions. / Lavlinskii, Sergey; Panin, Artem; Plyasunov, Alexander.

Mathematical Optimization Theory and Operations Research - 19th International Conference, MOTOR 2020, Revised Selected Papers. ed. / Yury Kochetov; Igor Bykadorov; Tatiana Gruzdeva. Springer Science and Business Media Deutschland GmbH, 2020. p. 36-50 (Communications in Computer and Information Science; Vol. 1275 CCIS).

Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review

Harvard

Lavlinskii, S, Panin, A & Plyasunov, A 2020, Bilevel Models for Investment Policy in Resource-Rich Regions. in Y Kochetov, I Bykadorov & T Gruzdeva (eds), Mathematical Optimization Theory and Operations Research - 19th International Conference, MOTOR 2020, Revised Selected Papers. Communications in Computer and Information Science, vol. 1275 CCIS, Springer Science and Business Media Deutschland GmbH, pp. 36-50, 19th International Conference on Mathematical Optimization Theory and Operations Research,MOTOR 2020, Novosibirsk, Russian Federation, 06.07.2020. https://doi.org/10.1007/978-3-030-58657-7_5

APA

Lavlinskii, S., Panin, A., & Plyasunov, A. (2020). Bilevel Models for Investment Policy in Resource-Rich Regions. In Y. Kochetov, I. Bykadorov, & T. Gruzdeva (Eds.), Mathematical Optimization Theory and Operations Research - 19th International Conference, MOTOR 2020, Revised Selected Papers (pp. 36-50). (Communications in Computer and Information Science; Vol. 1275 CCIS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-58657-7_5

Vancouver

Lavlinskii S, Panin A, Plyasunov A. Bilevel Models for Investment Policy in Resource-Rich Regions. In Kochetov Y, Bykadorov I, Gruzdeva T, editors, Mathematical Optimization Theory and Operations Research - 19th International Conference, MOTOR 2020, Revised Selected Papers. Springer Science and Business Media Deutschland GmbH. 2020. p. 36-50. (Communications in Computer and Information Science). doi: 10.1007/978-3-030-58657-7_5

Author

Lavlinskii, Sergey ; Panin, Artem ; Plyasunov, Alexander. / Bilevel Models for Investment Policy in Resource-Rich Regions. Mathematical Optimization Theory and Operations Research - 19th International Conference, MOTOR 2020, Revised Selected Papers. editor / Yury Kochetov ; Igor Bykadorov ; Tatiana Gruzdeva. Springer Science and Business Media Deutschland GmbH, 2020. pp. 36-50 (Communications in Computer and Information Science).

BibTeX

@inproceedings{6bfe6f1f161448bab597d9b1a17d6511,
title = "Bilevel Models for Investment Policy in Resource-Rich Regions",
abstract = "This article continues the research of the authors into cooperation between public and private investors in the natural resource sector. This work aims to analyze the partnership mechanisms in terms of efficiency, using the game-theoretical Stackelberg model. Such mechanisms determine the investment policy of the state and play an important role in addressing a whole range of issues related to the strategic management of the natural resource sector in Russia. For bilevel mathematical programming problems, the computational complexity will be evaluated and effective solution algorithms based on metaheuristics and allowing solving large-dimensional problems will be developed. This opens up the possibility of a practical study on the real data of the properties of Stackelberg equilibrium, which determines the design of the mechanism for forming investment policies. The simulation results will allow not only to assess the impact of various factors on the effectiveness of the generated subsoil development program but also to formulate the basic principles that should guide the state in the management process.",
keywords = "Bilevel mathematical programming problems, Probabilistic local search algorithm, Stackelberg game, Subsoil development program",
author = "Sergey Lavlinskii and Artem Panin and Alexander Plyasunov",
note = "Publisher Copyright: {\textcopyright} 2020, Springer Nature Switzerland AG. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.; 19th International Conference on Mathematical Optimization Theory and Operations Research,MOTOR 2020 ; Conference date: 06-07-2020 Through 10-07-2020",
year = "2020",
month = jul,
doi = "10.1007/978-3-030-58657-7_5",
language = "English",
isbn = "9783030586560",
series = "Communications in Computer and Information Science",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "36--50",
editor = "Yury Kochetov and Igor Bykadorov and Tatiana Gruzdeva",
booktitle = "Mathematical Optimization Theory and Operations Research - 19th International Conference, MOTOR 2020, Revised Selected Papers",
address = "Germany",

}

RIS

TY - GEN

T1 - Bilevel Models for Investment Policy in Resource-Rich Regions

AU - Lavlinskii, Sergey

AU - Panin, Artem

AU - Plyasunov, Alexander

N1 - Publisher Copyright: © 2020, Springer Nature Switzerland AG. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.

PY - 2020/7

Y1 - 2020/7

N2 - This article continues the research of the authors into cooperation between public and private investors in the natural resource sector. This work aims to analyze the partnership mechanisms in terms of efficiency, using the game-theoretical Stackelberg model. Such mechanisms determine the investment policy of the state and play an important role in addressing a whole range of issues related to the strategic management of the natural resource sector in Russia. For bilevel mathematical programming problems, the computational complexity will be evaluated and effective solution algorithms based on metaheuristics and allowing solving large-dimensional problems will be developed. This opens up the possibility of a practical study on the real data of the properties of Stackelberg equilibrium, which determines the design of the mechanism for forming investment policies. The simulation results will allow not only to assess the impact of various factors on the effectiveness of the generated subsoil development program but also to formulate the basic principles that should guide the state in the management process.

AB - This article continues the research of the authors into cooperation between public and private investors in the natural resource sector. This work aims to analyze the partnership mechanisms in terms of efficiency, using the game-theoretical Stackelberg model. Such mechanisms determine the investment policy of the state and play an important role in addressing a whole range of issues related to the strategic management of the natural resource sector in Russia. For bilevel mathematical programming problems, the computational complexity will be evaluated and effective solution algorithms based on metaheuristics and allowing solving large-dimensional problems will be developed. This opens up the possibility of a practical study on the real data of the properties of Stackelberg equilibrium, which determines the design of the mechanism for forming investment policies. The simulation results will allow not only to assess the impact of various factors on the effectiveness of the generated subsoil development program but also to formulate the basic principles that should guide the state in the management process.

KW - Bilevel mathematical programming problems

KW - Probabilistic local search algorithm

KW - Stackelberg game

KW - Subsoil development program

UR - http://www.scopus.com/inward/record.url?scp=85092075092&partnerID=8YFLogxK

U2 - 10.1007/978-3-030-58657-7_5

DO - 10.1007/978-3-030-58657-7_5

M3 - Conference contribution

AN - SCOPUS:85092075092

SN - 9783030586560

T3 - Communications in Computer and Information Science

SP - 36

EP - 50

BT - Mathematical Optimization Theory and Operations Research - 19th International Conference, MOTOR 2020, Revised Selected Papers

A2 - Kochetov, Yury

A2 - Bykadorov, Igor

A2 - Gruzdeva, Tatiana

PB - Springer Science and Business Media Deutschland GmbH

T2 - 19th International Conference on Mathematical Optimization Theory and Operations Research,MOTOR 2020

Y2 - 6 July 2020 through 10 July 2020

ER -

ID: 25674955