What is multimethod modeling (hybrid simulation)?
Building one model that combines simulation methods, such as system dynamics, discrete events, and agents, to capture different parts of a problem.
Multimethod modeling (hybrid simulation) diagram example
Multimethod modeling, also called hybrid simulation, means using more than one simulation approach inside a single model. A typical case is smooth flows for a market, queues for a factory, and individual agents for customers, all feeding each other. It matters because real problems rarely fit one method, and forcing them into one can hide the cause of the result.
How it works
The idea is to pick the method that fits each part of the problem. Large aggregate quantities, such as total demand or cash, suit continuous simulation. Work that waits for scarce resources suits discrete-event simulation. Parts where individual choices and interactions matter suit agent-based modeling. The parts exchange information at each step, for example a market model passes demand to a factory model, and the factory passes back delivery times.
The main risk is complexity. Every extra method adds assumptions to document and numbers to check, and the combined model is harder to validate. A good rule is to start with the simplest single method that answers the question and add a second only when you can name what it adds. Hybrid does not mean better; it means each piece is described in the form that is natural for it.
Example
Say a clinic wants to plan staffing. A continuous part models how the local population grows and how many people become ill each month, which gives 600 patient arrivals per month. A discrete part sends those 600 patients through registration, a nurse, and a doctor, each with limited capacity. If waiting grows past 30 minutes, some patients go elsewhere, which lowers next month's arrivals. Neither part alone shows that loop. This is an illustration with round numbers.
How to model it in Machinations
A Machinations diagram can hold several styles at once. Use Pools and rates on resource connections for the aggregate part, a Source with random timing and a Pool as a queue for the event-driven part, and Gates with probabilities for individual choices. Link the parts with state connections and Registers, then Play and chart the results. Use a Lever to test a policy across all parts together.
See multimethod modeling (hybrid simulation) in a system you can Play
Build the rules in a Machinations diagram, change a value and Play it to watch how the system responds.