Сравнение методов

	Агентно-ориентированное целочисленное программирование	Агентное моделирование (АМ)
Область	Имитационное моделирование	Имитационное моделирование
Семейство	Process / pipeline	Process / pipeline
Год появления	1990s–2000s	1970s–1990s (formalized as a field)
Автор метода	Emerged from multi-agent systems and operations research communities	Thomas Schelling and Robert Axelrod (foundational contributions, 1970s–1990s)
Тип	Hybrid simulation-optimization	Computational simulation method
Основополагающий источник	Wooldridge, M. (2009). An Introduction to MultiAgent Systems (2nd ed.). Wiley. ISBN: 9780470519462	Axelrod, R. (1997). The Complexity of Cooperation: Agent-Based Models of Competition and Collaboration. Princeton University Press.
Другие названия	ABIP, Agent-based IP, Multi-agent integer programming, ABM-IP	ABM, Ajan Tabanlı Modelleme (ABM), multi-agent simulation, individual-based modeling
Связанные	3	5
Сводка	Agent-Based Integer Programming (ABIP) couples the behavioral richness of agent-based modeling with the combinatorial rigor of integer programming. Individual agents pursue local objectives while a global IP solver enforces discrete feasibility constraints, enabling realistic modeling of multi-actor systems where decisions must be integer-valued — such as resource allocation, scheduling, and network design under emergent interaction effects.	Agent-based modeling (ABM) is a computational simulation method, formalized through the work of Thomas Schelling and Robert Axelrod in the 1970s–1990s, that simulates the behavior of complex systems by specifying and running autonomous agents — individuals, firms, cells, or any bounded entity — whose local interactions with each other and with their environment collectively produce global, system-level patterns that could not be predicted from any single agent's rules alone.