Recursive RINS

[nguidotti]

This PR implements the recursive RINS heuristics. More specifically, it applies a dive-like procedure to create a RINS sub-MIP, presolved it with Papilo and then passes to the cut-and-branch procedure. It also launch a CPU FJ worker over the sub-MIP that runs in parallel to cut-and-branch.

Since the current implementation, does not have an unified problem representation, this PR also adds:

• A routine for converting a lp_problem_t (standard form) to user_problem_t (range form).
• Allow Papilo to be applied to an user_problem_t instead of optimization_problem_t.
• Adds an upper bound callback for retrieving the upper bound of the main solver (since it may change if another worker find a better incumbent).

Additionally, the number of worker per diving heuristic is no longer tied to the total number of workers, which allows the solver to use all diving heuristics in low thread counts (we rotate between the different heuristics for each diving worker launch).

Results

MIPLIB2017, 10min, GH200

================================================================================
 main-2026-07-03 (1) vs recursive-submip (2)
================================================================================

------------------------------------------------------------------------------------------------------------------------------
|                                        |       Run 1        |       Run 2        |     Abs. Diff.     |   Rel. Diff. (%)   |
------------------------------------------------------------------------------------------------------------------------------
| Imported                                                 240                  240                   +0                 --- |
| Feasible                                                 227                  228                   +1                 --- |
| Optimal                                                   86                   91                   +5                 --- |
| Solutions with <0.1% primal gap                          138                  151                  +13                 --- |
| Nodes explored (mean)                              1.326e+07            1.296e+07           -3.057e+05               -2.31 |
| Nodes explored (shifted geomean)                   1.262e+04            1.239e+04                 -230               -1.82 |
| Relative MIP gap (mean)                               0.2777               0.2726             -0.00512               -1.84 |
| Relative MIP gap (shifted geomean)                   0.09089              0.08901            -0.001883               -2.07 |
| Solve time (mean)                                      422.6                435.4               +12.79               +3.03 |
| Solve time (shifted geomean)                           196.9                226.6               +29.66               +15.1 |
| Primal gap (mean)                                      9.969                 9.29               -0.679               -6.81 |
| Primal gap (shifted geomean)                          0.4584               0.3491              -0.1093               -23.8 |
| Primal integral (mean)                                 25.02                22.97               -2.051                -8.2 |
| Primal integral (shifted geomean)                      2.849                2.421              -0.4275                 -15 |
------------------------------------------------------------------------------------------------------------------------------


----------------------------------------------------------------------
|             Name             |     status 1     |     status 2     |
----------------------------------------------------------------------
| neos-1171737                           feasible            optimal |
| radiationm40-10-02                     feasible            optimal |
| rail01                                  timeout           feasible |
| ran14x18-disj-8                        feasible            optimal |
| triptim1                               feasible            optimal |
| unitcal_7                              feasible            optimal |
----------------------------------------------------------------------

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[chris-maes]

I only made it through branch_and_bound.cpp. I need to finish the review later.

[chris-maes]

Nit: member variables should end with and underscore has_initial_pseudocost_

[nguidotti]

The other variables do not have the underscore. Do you want me to rename them all?

[chris-maes]

But couldn't clamping cause us to loose feasibility for the lb <= A*x <= ub constraints?

[nguidotti]

@aliceb-nv for viz. This is just the duplicate of the other crush function (since I need to apply for an user_problem_t instead of optimization_problem_t)

[aliceb-nv]

It can. That's the price to pay 😅 Dual reductions inherently cut off part of the polytope. If papilo performed some, we can mostly only hope that canonicalization back into the polytope is possible. Sometimes it may not be (e.g. papilo used DualFix to safely tighten the bounds of some variables because it proved it won't cut off any optimal solution, and then it may decide to do propagation on this.... But, afaik, this is just an inherent risk that cannot practically be avoided)