The end goal of Problem Modeling is to produce a problem description to feed the Optimization Engine.
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In practice, this description is a groovy Groovy map in the Run Logic. Then a A specific API transforms this map into JSON. Then the backend transforms the JSON problem description into an actual multi-agent system.
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The steps to create a specific model description are:
Get to know the structure of the
Run.groovyLogic: understand its structure logic.Define the dimensions categories hierarchies.
Define the spaces.
Define the scopes inside each space.
Define the variables inside each scope.
Define the criteria inside each scope.
The easiest way is to write the description space is by space following the graphical description. The binding to the data is done through scopes: inputs and outputs of the Optimization Engine are model tables named after the space and scopes to which they pertain (e.g. Problem_ByProduct_All contains the data for the scope All in the space ByProduct).
Understanding the underlying concepts is important. Page As a reference, see Main Concepts for Optimization Problems is the reference.
This section also provides a problem description sample.
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A problem description does not exist in isolation and is delivered along with a Model Logic responsible for providing the mappings, in the form of Model Tables, between this high-level description of the problem and the actual values coming from the partition’s transactional and master data. This step is documented in the next section Problem Tables.