It can happen that presolving removes all rows and columns of a problem. This means all constraints are removed and variables are fixed, so no further LP or MIP solving techniques (like branch-and-bound, heuristics or cutting planes) are required. The optimal solution - if the model is feasible - could already be determined using the various reductions, implications, and propagations that are performed during the presolving phase of Gurobi.
Articles in this section
- What does "Presolve: All rows and columns removed" mean?
- How can I return from multi-objective optimization back to single-objective mode?
- Why can't I get the Pi values for a MIP problem?
- Is Gurobi Optimizer deterministic?
- What is the difference between user cuts and lazy constraints?
- Why do I see increasing/large MIP gap values?
- How does presolve() work?
- How do you implement lazy constraints in Gurobi?
- Can you modify the branch-and-bound algorithm or create a branch-cut-and-price algorithm?
- Does Gurobi have a solution polishing algorithm?