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Парадигми імітаційного моделювання при дослідженні складних систем з паралелізмом

Парадигми імітаційного моделювання при дослідженні складних систем з паралелізмом

Abstract

Today, simulation modeling is one of the most powerful tools for studying parallel systems, which are characterized by structural, functional and development complexity. Studying modern complex parallel systems requires new approaches based on integration of developed methods belonging to various paradigms of simulation modeling. The paper gives an overview of paradigms which were highlighted in current researches: dynamic systems modeling, discrete-event simulation, system dynamics and agent-based modeling. The element basis, the range of tasks, which can be studied using the considered paradigms, were analyzed, their advantages and disadvantages were described. The problems of simulation modeling, which arise in constructing simulation models for complex parallel systems, requiring the use of elements of various paradigms with continuous and discrete description of properties, were singled out. The requirements to modern modeling tools and promising ways of simulation modeling development were formed.

В статье представлен обзор парадигм имитационного моделирования и проблем, которые возникают при построении имитационных моделей для сложных систем с параллелизмом, которые требуют использования элементов парадигм с непрерывным и дискретным описанием свойств.

У статті представлений огляд парадигм імітаційного моделювання та проблем, що виникають при побудові імітаційних моделей для складних систем з паралелізмом, які потребують використання елементів парадигм з неперервним і дискретним описом властивостей.

Keywords

simulation modeling; discrete-event simulation; system dynamics; agent-based modeling, імітаційне моделювання; дискретно-подієве моделювання; системна динаміка; агентне моделювання, УДК 519.876 : 004.94, имитационное моделирование; дискретно-событийное моделирование; системная динамика; агентное моделирование

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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