Now consider an application where the user wishes to solve a linear program using the simplex method, then modify the problem slightly and solve the modified problem. As an example, let's say a user wishes to add a few new constraints to a problem based on the results of the first solution. The second solution should ideally start from the basis of the first, since starting from an advanced basis is usually significantly faster if the problem is only modified slightly.

The advanced presolve interface can potentially make this and many other sequences of operations more efficient. It provides facilities to restrict the set of presolve reductions performed so that subsequent problem modifications can be accommodated. It also provides routines to translate constraints on the original problem to constraints on the presolved problem, so new constraints can be added to the presolved problem. In short, it provides a variety of capabilities.

When considering mixed integer programs, the advanced presolve interface plays a very different role. The branch & cut process needs to be restarted from scratch when the problem is even slightly modified, so preserving advanced start information isn't useful. The main benefit of the advanced presolve interface for MIPs is that it allows a user to translate decisions made during the branch & cut process (and based on the presolved problem) back to the corresponding constraints and variables in the original problem. This makes it easier for a user to control the branch & cut process. Details on the advanced MIP callback interface are provided in Advanced MIP Control Interface.