Gurobi V7.0 added a feature for MIP Solution Pools. Specifically, you can use a solution pool to find the N best solutions, or N solutions that are less than a specified gap from the optimal solution. For details, see the solution pool section in the Reference Manual.
Articles in this section
- 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?
- How do I find additional solutions to a model?
- Does the barrier algorithm return a basic solution for LPs?