Результаты исследований: Публикации в книгах, отчётах, сборниках, трудах конференций › статья в сборнике материалов конференции › научная › Рецензирование
Equilibrium Commodity Flow Assignment in Simple Networks. / Krylatov, Alexander; Lonyagina, Yulia.
Artificial Intelligence in Intelligent Systems - Proceedings of 10th Computer Science On-line Conference, 2021. ред. / Radek Silhavy. Springer Nature, 2021. стр. 337-346 (Lecture Notes in Networks and Systems; Том 229).Результаты исследований: Публикации в книгах, отчётах, сборниках, трудах конференций › статья в сборнике материалов конференции › научная › Рецензирование
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TY - GEN
T1 - Equilibrium Commodity Flow Assignment in Simple Networks
AU - Krylatov, Alexander
AU - Lonyagina, Yulia
N1 - Publisher Copyright: © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.
PY - 2021
Y1 - 2021
N2 - Today efficient commodity management seems impossible without the support of intelligent systems and computing based on mathematical models of commodity flow assignment since a modern market network is a large-scale system with many elements. The present paper is devoted to the equilibrium commodity flow assignment problem, which solution is valuable from decision-making perspectives. The paper attempts to fill the gap in the analytical relations between the equilibrium commodity assignment pattern and demand-supply parameters. We study commodity assignment in the case of linear demand, supply, and transportation functions. The problem is formulated in a form of nonlinear optimization program with dual variables reflecting supply and demand prices. The equilibrium commodity assignment pattern is obtained explicitly via equilibrium prices. For simple networks of three and four nodes we are lucky to obtain explicit conditions for identification of active commodity flows. In other words, once the demand-supply parameters are given, then active commodity flows can be identified explicitly.
AB - Today efficient commodity management seems impossible without the support of intelligent systems and computing based on mathematical models of commodity flow assignment since a modern market network is a large-scale system with many elements. The present paper is devoted to the equilibrium commodity flow assignment problem, which solution is valuable from decision-making perspectives. The paper attempts to fill the gap in the analytical relations between the equilibrium commodity assignment pattern and demand-supply parameters. We study commodity assignment in the case of linear demand, supply, and transportation functions. The problem is formulated in a form of nonlinear optimization program with dual variables reflecting supply and demand prices. The equilibrium commodity assignment pattern is obtained explicitly via equilibrium prices. For simple networks of three and four nodes we are lucky to obtain explicit conditions for identification of active commodity flows. In other words, once the demand-supply parameters are given, then active commodity flows can be identified explicitly.
KW - Equilibrium commodity assignment
KW - Multi-commodity network
KW - Nonlinear optimization
UR - http://www.scopus.com/inward/record.url?scp=85115862578&partnerID=8YFLogxK
UR - https://www.mendeley.com/catalogue/ff6a3d41-e72b-3238-8c23-842f17033038/
U2 - 10.1007/978-3-030-77445-5_31
DO - 10.1007/978-3-030-77445-5_31
M3 - Conference contribution
AN - SCOPUS:85115862578
SN - 9783030774448
T3 - Lecture Notes in Networks and Systems
SP - 337
EP - 346
BT - Artificial Intelligence in Intelligent Systems - Proceedings of 10th Computer Science On-line Conference, 2021
A2 - Silhavy, Radek
PB - Springer Nature
T2 - 10th Computer Science Online Conference, CSOC 2021
Y2 - 1 April 2021 through 1 April 2021
ER -
ID: 87511150