Under construction.
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View Code? Open in Web Editor NEWPresolve routines for mathematical optimization
License: Mozilla Public License 2.0
Presolve routines for mathematical optimization
License: Mozilla Public License 2.0
If we want to be able to use Multifloats.jl, we need to be careful about arithmetic operations with Inf
.
Our current implementation relies on conventions like Inf + 1 == Inf
and -1 * Inf == -Inf
, from which Multifloats.jl deviates.
After taking a quick glance, it shouldn't be too hard for us to add manual checks to avoid arithmetic operations with Inf
when possible.
We can also add Float64x2
to the tests.
The question of how MIP reductions (resp. LP reductions) should handle continuous (resp integer) variables has come up a few times now.
It might make sense to fully separate LP reductions from MIP reductions (incidentally, we already have src/lp
and src/mip
), at least for now.
We can still have a "meta-main" presolve!
function that would check whether a problem is LP/MIP and call the appropriate LP/MIP-specific "main" presolve. Data structures like ProblemData
and style conventions can also be shared.
Pros:
Cons:
@joehuchette what do you think?
Is it time?
Coarse roadmap towards implementing the reductions described in this paper (which is, AFAIK, the most comprehensive and recent paper on the subject).
The table below follows the paper's structure, namely:
3. Individual row reduction
4. Individual variable reduction
5. Multiple row reductions
6. Multiple variable reductions
7. Full-problem reduction
The second and third columns indicate whether each reduction is applicable to LP/MIP models (see detailed legend below)
Reduction | LP | MIP | Current progress |
---|---|---|---|
3.1 Redundant constraints | ✔️ | ✔️ | LP:🚧 📝; MIP: 🙅 |
3.2 Bound strengthening | ✔️ | ✔️ | LP:🚧 📝; MIP: 🙅 |
3.3 Coefficient strengthening | ❌ | ✔️ | 🟢 #14 |
3.4 C-G strengthening | ❌ | ✔️ | 🙅 |
3.5 Euclidean and modular inverse | ❌ | ✔️ | 🙅 |
3.6 Single-row probing | ❌ | ✔️ | 🙅 |
3.7 SOS reductions | ❌ | ✔️ | 🙅 |
4.1 Fixed variables | ✔️ | ✔️ | 🟢 #7 |
4.2 Rounding integer bounds | ❌ | ✔️ | 🚧 #8 |
4.3 Strengthen SC/SI bounds | ❌ | ✔️ | 🙅 |
4.4 Dual fixing | ✔️ | ✔️ | 🙅 |
4.5 Implied-free variables | ✔️ | ✔️ | LP:🚧 📝; MIP: 🙅 |
5.1 Redundancy detection | ✔️ | ✔️ | 🙅 |
5.2. Parallel rows | ✔️ | ✔️ | 🙅 |
5.3 Non-zero cancellation | ✔️ | ✔️ | 🙅 |
5.4 (multi-row) bound strengthening | ✔️ | ✔️ | 🙅 |
5.5 Clique merging | ❌ | ✔️ | 🙅 |
6.1 Dual fixing extension | ❓ | ✔️ | 🙅 |
6.2 Redundant penalty variables | ✔️ | ✔️ | 🙅 |
6.3 Parallel columns | ✔️ | ✔️ | 🙅 |
6.4 Dominated columns | ✔️ | ✔️ | 🙅 |
7.1 Symmetric variables | ❌ | ✔️ | 🙅 |
7.2 Probing | ❌ | ✔️ | 🙅 |
7.3 Disconnected components | ✔️ | ✔️ | 🙅 |
7.4 Almost disconnected components | ✔️ | ✔️ | 🙅 |
7.5 Complementary slackness | ❌ | ✔️ | 🙅 |
7.6 Implied integer | ❌ | ✔️ | 🙅 |
Legend:
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