![]() ![]() ĪnyLogic is used to simulate: markets and competition, healthcare, manufacturing, supply chains and logistics, retail, business processes, social and ecosystem dynamics, defense, project and asset management, pedestrian dynamics and road traffic, IT, and aerospace. AnyLogic is cross-platform simulation software that works on Windows, macOS and Linux. It supports agent-based, discrete event, and system dynamics simulation methodologies. Interfaces and feedbacks between system dynamics, agent based, and discrete-event models are very easy in AnyLogic.English, Portuguese, Russian, German, Chinese, SpanishĪnyLogic is a multimethod simulation modeling tool developed by The AnyLogic Company (formerly XJ Technologies). In another example, the population of a city may be modeled as individual agents, and the underlying economic or background infrastructure in system dynamics. Combining them so the consumer market drives the supply chain. For example, the consumer market can be modeled using system dynamics and the supply chain with the agent-based approach. This can be done in a number of different ways. Combining system dynamics with agent-based and discrete-event methodsĪnyLogic is the only tool that allows the combination of system dynamics model components with those developed using agent-based and discrete-event methods. Moreover, a frequently met system dynamics pattern may be saved as a library object and reused within one simulation model or across different models.ĪnyLogic users also benefit from advantages such as model export, cloud model execution, sophisticated animation, and interoperability with other software tools. Complex models can be defined in a hierarchical manner with objects only exposing interface variables as inputs and outputs. ![]() Why AnyLogic?ĪnyLogic inherently offers all the benefits of the object-oriented approach to system dynamics modeling. System dynamics is supported by several tools that are very much alike. System dynamics modeling in AnyLogicĪnyLogic supports the design and simulation of feedback structures such as, stock and flow diagrams, array variables (subscripts) in a way most system dynamics modelers are familiar. Mathematically, a system dynamics simulation model maps to a system of differential equations that are solved numerically in a simulation engine. Use global dependencies and provide quantitative data for them.ĭependencies are non-linear in the real world and need to be modeled with system dynamics simulation software, which is much more powerful than spreadsheets.Models with aggregates, and not individual objects.System dynamics does not consider single events and takes an aggregate view, focusing on policies. material, knowledge, people, money), flows between stocks, and information to determine the flows. The feedback loop is a basic concept of system dynamics.ĭescribing feedback loops and modeling the real-world in system dynamics is done using stocks (e.g. For instance, the more money you invest in marketing, the bigger revenues you have, and so, the more money you can spend on marketing. This is where system dynamics modeling tools give an advantage.įeedback loops - a basic concept of system dynamicsĭependencies, such as advertising and brand perception, are often represented as loops called feedback loops. There is cause and effect, and often there is a time delay which is only visible after long observation. In business, there are a lot of dependencies, for instance, employee morale affecting productivity, or the effect of advertising on brand perception. The effect of change can be understood, and possibilities quantitively tested and analyzed. Understanding these with system dynamics has proven very effective. Read the white paper Causal diagrams to describe global system behaviorĬomplex relationships are found across all areas of business, study, and effort. Read the white paper and see why hybrid models are always a better choice! ![]() In our white paper, Multimethod Simulation Modeling for Business Applications, we investigate three main simulation modeling approaches: system dynamics, agent-based, and discrete-event modeling, and construct a multimethod model example to illustrate the advantages of combining different methods. For example, a telephone network planning a marketing campaign may simulate and analyze the success of new data plan ideas without having to model individual customer interactions. These abstract simulation models may be used for long-term, strategic modeling and simulation. It ignores the fine details of a system, such as the individual properties of people, products, or events, and produces a general representation of a complex system. ![]() System dynamics is a highly abstract method of modeling. ![]()
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