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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:

1. Get to know the structure of the Run.groovy Logic: understand its structure logic.

2. Define the dimensions hierarchies.

3. Define the spaces.

4. Define the scopes inside each space.

5. Define the variables inside each scope.

6. 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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