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Hierarchical Multi-agent Model for the Management of a Regional Industrial Network Complex Научная публикация

Журнал Lecture Notes in Information Systems and Organisation
ISSN: 2195-4968 , E-ISSN: 2195-4976
Вых. Данные Год: 2023, Том: 61, Страницы: 331-350 Страниц : 20 DOI: 10.1007/978-3-031-30351-7_25
Ключевые слова Multi-agent hierarchical control, Intelligent semantic network, Regional industrial, Network complex
Авторы Shorikov Andrey F. 1
Организации
1 Institute of Economics of the Ural Branch of the Russian Academy of Sciences

Информация о финансировании (1)

1 Российский научный фонд 22-28-01868

Реферат: The paper considers the description of the dynamics and optimization of the regional network industrial complex in the presence of risks (disturbances) and information uncertainty. For their formalization, the economic-mathematical model in the form of a two-level multi-agent hierarchical intelligent semantic network is proposed. It describes the formalization of the problems of parameter identification, structurally balanced interaction, the prognosis of development and optimization of a guaranteed (minimax approach) result of managing the state of objects and processes of the regional industrial network complex in the presence of risks (disturbances) and information uncertainty within the proposed two-level multi-agent hierarchical intelligent semantic network. The paper presents the methodology for solving the tasks under consideration. The economic-mathematical model of the regional network industrial complex proposed in the article makes it possible to develop algorithms for optimizing the processes under study, which can serve as the basis for creating intelligent management decision support systems.
Библиографическая ссылка: Shorikov A.F.
Hierarchical Multi-agent Model for the Management of a Regional Industrial Network Complex
Lecture Notes in Information Systems and Organisation. 2023. V.61. P.331-350. DOI: 10.1007/978-3-031-30351-7_25 Scopus OpenAlex
Даты:
Поступила в редакцию: 22 окт. 2022 г.
Принята к публикации: 12 дек. 2022 г.
Опубликована online: 30 мая 2023 г.
Идентификаторы БД:
Scopus: 2-s2.0-85163294473
OpenAlex: W4378678814
Цитирование в БД: Пока нет цитирований
Альметрики: