Let’s apply this mental model to the Oil Supply Chain model.
We start by cataloguing the agents. In AnyLogic you can double click on any of the agents to see the relevant functions, properties, state charts, etc.
FuelTruck
Fuel Trucks transport oil from refineries and storage agents to retailer agents.
Refinery
Refinery Agents take unprocessed oil and refine it into oil that can be delivered to storage units / retailers
Retailer
Retailers represent customer demand for oil and request and receive oil from fuel agents.
Storage
Storage agents hold unrefined and refined oil.
In the AnyLogic model there are three different types of storage locations: ports, storages, and distributors
All of these share lots of features, so we’ll be able to make use of HASH’s composable behaviors to define our agents.
Tanker
Tankers deliver oil from ‘outside the sim’ (they actually generate it) to storage units
If you’ve been following along you’ll notice we left off one agent - Pipelines. Pipelines act as a flow regulator, decreasing quantity in one agent and delivering it to another. In our simulation we're going to use messages to accomplish a similar thing. Messaging is a key primitive operation provided by HASH, and as you’ll see we use it throughout the simulation.
Since we can represent the behavior of Pipelines completely through messages, we'll effectively combine it with the Storage agents to reduce the number of agents in the simulation, and the complexity of interactions. But more on that later.
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