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Stochastic local search for the strategic planning public-private partnership. / Zyryanov, Alexander A.; Kochetov, Yury A.; Lavlinskii, Sergey M.

в: CEUR Workshop Proceedings, Том 2098, 01.01.2018, стр. 446-463.

Результаты исследований: Научные публикации в периодических изданиях › статья по материалам конференции › Рецензирование

Harvard

Zyryanov, AA, Kochetov, YA & Lavlinskii, SM 2018, 'Stochastic local search for the strategic planning public-private partnership', CEUR Workshop Proceedings, Том. 2098, стр. 446-463.

APA

Zyryanov, A. A., Kochetov, Y. A., & Lavlinskii, S. M. (2018). Stochastic local search for the strategic planning public-private partnership. CEUR Workshop Proceedings, 2098, 446-463.

Vancouver

Zyryanov AA, Kochetov YA, Lavlinskii SM. Stochastic local search for the strategic planning public-private partnership. CEUR Workshop Proceedings. 2018 янв. 1;2098:446-463.

Author

Zyryanov, Alexander A. ; Kochetov, Yury A. ; Lavlinskii, Sergey M. / Stochastic local search for the strategic planning public-private partnership. в: CEUR Workshop Proceedings. 2018 ; Том 2098. стр. 446-463.

BibTeX

@article{940a3e22d8cf4f9d9cf31ebf203ba362,
title = "Stochastic local search for the strategic planning public-private partnership",
abstract = "We present a new bi-level linear integer programming model for the strategic planning of the public-private partnership. This model is an extension of the previously studied models where the ecological, infrastructure, and production projects have known schedules into the planning horizon if they start. A stochastic local search matheuristic is designed for this new problem according to the upper level variables. The optimal solution for the lower level is obtained by CPLEX software. To reduce the running time, we use randomized Flip and Swap neighborhoods. To evaluate the neighboring solutions, we solve the lower level problem approximately with a small fixed deviation from the optimum. Computational results for real world instances for the Tranbaikalian polymetal fields are discussed.",
keywords = "Bilevel mathematical programming problem, Local search, Public-private partnership, Stackelberg game",
author = "Zyryanov, {Alexander A.} and Kochetov, {Yury A.} and Lavlinskii, {Sergey M.}",
year = "2018",
month = jan,
day = "1",
language = "English",
volume = "2098",
pages = "446--463",
journal = "CEUR Workshop Proceedings",
issn = "1613-0073",
publisher = "CEUR-WS",
note = "2018 School-Seminar on Optimization Problems and their Applications, OPTA-SCL 2018 ; Conference date: 08-07-2018 Through 14-07-2018",

}

RIS

TY - JOUR

T1 - Stochastic local search for the strategic planning public-private partnership

AU - Zyryanov, Alexander A.

AU - Kochetov, Yury A.

AU - Lavlinskii, Sergey M.

PY - 2018/1/1

Y1 - 2018/1/1

N2 - We present a new bi-level linear integer programming model for the strategic planning of the public-private partnership. This model is an extension of the previously studied models where the ecological, infrastructure, and production projects have known schedules into the planning horizon if they start. A stochastic local search matheuristic is designed for this new problem according to the upper level variables. The optimal solution for the lower level is obtained by CPLEX software. To reduce the running time, we use randomized Flip and Swap neighborhoods. To evaluate the neighboring solutions, we solve the lower level problem approximately with a small fixed deviation from the optimum. Computational results for real world instances for the Tranbaikalian polymetal fields are discussed.

AB - We present a new bi-level linear integer programming model for the strategic planning of the public-private partnership. This model is an extension of the previously studied models where the ecological, infrastructure, and production projects have known schedules into the planning horizon if they start. A stochastic local search matheuristic is designed for this new problem according to the upper level variables. The optimal solution for the lower level is obtained by CPLEX software. To reduce the running time, we use randomized Flip and Swap neighborhoods. To evaluate the neighboring solutions, we solve the lower level problem approximately with a small fixed deviation from the optimum. Computational results for real world instances for the Tranbaikalian polymetal fields are discussed.

KW - Bilevel mathematical programming problem

KW - Local search

KW - Public-private partnership

KW - Stackelberg game

UR - http://www.scopus.com/inward/record.url?scp=85048021505&partnerID=8YFLogxK

M3 - Conference article

AN - SCOPUS:85048021505

VL - 2098

SP - 446

EP - 463

JO - CEUR Workshop Proceedings

JF - CEUR Workshop Proceedings

SN - 1613-0073

T2 - 2018 School-Seminar on Optimization Problems and their Applications, OPTA-SCL 2018

Y2 - 8 July 2018 through 14 July 2018

ER -

ID: 13754722