DOI

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.

Язык оригиналаанглийский
Название основной публикацииArtificial Intelligence in Intelligent Systems - Proceedings of 10th Computer Science On-line Conference, 2021
РедакторыRadek Silhavy
ИздательSpringer Nature
Страницы337-346
Число страниц10
ISBN (печатное издание)9783030774448
DOI
СостояниеОпубликовано - 2021
Событие10th Computer Science Online Conference, CSOC 2021 - Virtual, Online
Продолжительность: 1 апр 20211 апр 2021

Серия публикаций

НазваниеLecture Notes in Networks and Systems
Том229
ISSN (печатное издание)2367-3370
ISSN (электронное издание)2367-3389

конференция

конференция10th Computer Science Online Conference, CSOC 2021
ГородVirtual, Online
Период1/04/211/04/21

    Предметные области Scopus

  • Системотехника
  • Обработка сигналов
  • Компьютерные сети и коммуникации

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