# Documentation

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## Definition of a Multi-Scenario Model

Before diving into the details of working with multiple scenarios, we first need to explain exactly what we mean by the term. Let us start by claiming that it only makes sense to consider a set of models as being different scenarios for the same underlying model if they have a lot in common. They should definitely share the same set of variables. They should also have similar sets of constraints and similar objectives. In our approach, scenarios are described as a set of changes from a single base model. More specifically, scenarios can only modify model features that are present in the base model. We should add that other modifications, including addition and deletion of variables or constraints, can be achieved through the clever use of various tricks. For now, though, it is best to think of scenarios as being small variations on the same base.

What variations do we allow from this base model? Scenarios can differ in the following attributes:

• Linear objective function coefficients.
• Variable lower and upper bounds.
• Constraint right-hand side values.
A single scenario can have multiple changes from the base, so for example you could change an objective coefficient, two variable bounds, and a right-hand side value in the same scenario.

After you have defined a set of scenarios (the specific mechanics for doing so will be described shortly), the next step is to find solutions for all of the scenarios. A single call to the standard Gurobi optimize method is all that is needed. This will of course be much more expensive than finding an optimal solution for a single model, but our goal is for it to be faster and more convenient than formulating and solving separate models for each scenario.