Multimethod Simulation Modeling

Multimethod Simulation Modeling

The idea of multimethod modeling is simple: to seamlessly integrate different methods of modeling and simulation to overcome the drawbacks of individual approaches and get the most from each one. Combining different methods leads to efficient and manageable models without using workarounds.

There are three major methodologies used to build dynamic business simulation models: system dynamics, discrete event modeling, and agent based modeling.

The system dynamics method assumes a high abstraction level and is primarily used for strategic level problems, such as market adoption rates and social process dependency.

Discrete event modeling is mainly used at operational and tactical levels, like manufacturing processes and equipment investment evaluation.

Agent-based models are used at all levels, with the agents possibly being any active entity. Example applications include supply chain optimization and epidemiology.

The benefits of access to different modeling methods

Methods of Simulation Modeling

Building a model requires a level of simplification. Can a broad view be taken, or should fine details be captured? It all depends on the system being modeled and the problem in need of a solution.

Using a single method, it can be difficult to model at the appropriate level of abstraction. It may be possible to model the actions of autonomous entities via system dynamics, but unnecessary when agent based tools avoid the need for additional abstractions and assumptions. Similarly, discrete methods are inefficient for modeling continuous variables when system dynamics methods are available.

Most real-world cases are complex, and it is convenient to describe different parts of a system with different methods. The ability to capture business systems with their real complexity and interactions can be seriously limited using only one method.
Some system elements will have to be excluded or a workaround developed.

Having access to all methods simultaneously gives the flexibility needed to successfully solve the problem at hand.

Production, distribution, and the market model

Here, you can see how production, distribution, and the market can be combined in one model using different techniques. A discrete event model describes the processes within each warehouse. The warehouses then appear as agents on the distribution network. Finally, the market, which drives the system, is modeled with system dynamics. Everything is captured without compromise.

With AnyLogic you are never limited by a single modeling method. You can always choose the most efficient one, or combination, and get the best modeling and simulation to address your problem.

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