v1.12.0

Code changes

HiPO is out! Our new factorisation-based interior point solver, developed by Filippo Zanetti, is officially integrated in HiGHS! HiPO is multi-threaded and will improve the performance on many large instances. Metis and BLAS are required for HiPO. In this version, HiPO will be available when HiGHS is built from source with CMake. It can be accessed from C++, C and will also be available when HiGHS is called from JuMP. In a future release, HiPO will be available from Python, C# and more.

Forcing column reduction now checks the bound on the column dual rather than whether the dual row activity is zero fixing #2409

Now handling correctly the case where an infeasible MIP has a feasible relaxation, so no ray is computed fixing #2415

Fixed minor bug exposed by #2441 in Highs::setSolution() for a sparse user solution when the moidel is empty, and only clearing the dual data before solving with modified objective in Highs::multiobjectiveSolve() so that user-supplied solution is not cleared.

The irreducible infeasibility system (IIS) facility now detects infeasibility due to bounds on constraint activity values (implied by variable bounds) being incompatible with constraint bounds. A kIisStrategyLight mode for the iis_strategy option has been introduced so that only infeasibility due to incompatible variable/constraint bounds and constraint activity values is checked for. The LP corresponding to any known IIS is now formed and held as a data member of the HighsIis class. It can be obtained as a const reference using Highs::getIisLp(), and written to a file using Highs::writeIisModel(const std::string& filename = "")

Prompted by #2463, the HiGHS solution and basis files now match data to any column and row names in the model, only assuming that the data are aligned with column and row indices if there are no names in the model. This requires a new version (v2) of the HiGHS basis file. Basis files from v1 are still read, but deprecated. Now, when writing out a model, basis or solution, column and row names are added to the model - previously they were created temporarily and inconsistentyly on the fly. If the model has existing names, then distinctive names are created to replace any blank names, but names with spaces or duplicate names yield an error status return.

Refactored strong branching to minimize duplicated code

Only for LPs is there a choice of solver. Previously, when setting the solver option to anything other than "choose", any incumbent model was solved as an LP, using that LP solver. This has caused confusiuon for users, and is unnecessary now that there is the solve_relaxation option. Now, if the incumbent model is a QP or MIP, it is solved as such (unless solve_relaxation is true for a MIP), and the value of the solver option only determines what solver is used to solve an LP. If the value of solver is "choose", then HiGHS will use what it expects to be the best solver for the problem; if value of solver is "ipm", then HiGHS will use what it expects to be the better IPM solver (of HiPO and IPX) for the problem; if value of solver is "hipo", then HiGHS will use the HiPO IPM solver (if available in the build); if value of solver is "ipx", then HiGHS will use the IPX IPM solver; if value of solver is "pdlp", then HiGHS will use the PDLP first-order solver. The option mip_lp_solver has been introduced to define which LP solver is used when solving LPs in the MIP solver for which an advanced basis is not known - typically the "root node" LP. Note that The PDLP solver cannot be used to solve such LPs, since it does not yield a basic solution. If an interior point solver fails to obtain a basic solution, the simplex solver will then be used. The option mip_ipm_solver has been introduced to define which IPM solver is used when solving LPs in the MIP solver for which IPM is mandatory - typically the analytic centre calculation. When LPs are to be solved by an IPM solver, the HiPO solver is used (if available in the build) unless IPX has been specified explicitly.

As per #2487, trivial heuristics now run before feasibility jump (FJ), and FJ will use any existing incumbent. FJ will clip any finite variable values in the incumbent to lower and upper bounds, and falls back to the existing logic (lower bound if finite, else upper bound if finite, else 0) for any infinite values in the incumbent.

Prompted by #2460, the options user_objective_scale and user_bound_scale apply uniform (power-of-two) scaling to the objective and bounds of a model, and now respect the following restrictions

• For a MIP, column bounds cannot be scaled, so the scaling is achieved by scaling the cost and constraint matrix column
• For a QP, Hessian entries must be scaled down (up) when bounds are scaled up (down) so that all terms in the objective are scaled by a constant.

Formerly the options user_cost_scale and user_bound_scale allowed uniform (power-of-two) scaling to the costs and bounds of an LP. The option user_cost_scale is now replaced by user_objective_scale.

After HiGHS determines and logs the coefficient ranges and warns about extreme values, it recommends values of user_objective_scale and user_bound_scale if

• All the objective coefficients (bound values) are smaller than the "excessively small constant" kExcessivelySmallObjectiveCoefficient (kExcessivelySmallBoundValue) - both of which are 1e-4 - suggesting that they are scaled up so that the largest value becomes (just over) the excessively small constant. Since the smallest value can be arbitrarily small, scaling so that this becomes (just over) the small constant is inadvisable, as the largest value could then be scaled up to an extremely large value.
• All the objective coefficients (bound values) are larger than the "excessively large constant" kExcessivelyLargeObjectiveCoefficient (kExcessivelyLargeBoundValue) - both of which are 1e6 - suggesting that they are scaled down so that the largest value becomes (just over) the excessively large constant.

The recommended objective scaling is determined with respect to the recommended bound scaling
Users can obtain the recommended values of user_objective_scale and user_bound_scale by calling Highs::getObjectiveBoundScaling

The irreducible infeasibility system (IIS) facility now detects infeasibility due to bounds on constraint activity values being incompatible with constraint bounds. A kIisStrategyLight mode for the iis_strategy option has been introduced so that only infeasibility due to incompatible variable/constraint bounds and constraint activity values is checked for. The model corresponding to any known IIS is now formed and held as a data member of the HighsIis class. The HighsIis class is available via highspy, and its data members are available via the C API.

Prompted by #2463, when HiGHS writes out a solution or basis for a model without column or row names, it creates names. This avoids a mis-match between the ordering of variables when such a model is written out as a .lp file, and then this and a solution or a basis is read in.

Prompted by #2528, the logging for the HiGHS interior point method (IPM) solvers and PDLP solver has been standardised, and logging has been added to the IPM solver during time-consuming computational phases.

Prompted by #2557, Highs::getFixedLp has been added so that, after solving a MIP, the LP with discrete variables fixed at their optimal values can be formed, allowing it to be passed to HiGHS and solved as an LP.

Prompted by #2581, the QP example in call_highs_from_csharp.cs has been corrected

Prompted by #2582, the C API constants are declared static const to prevent multiple definition linker errors

Build changes

The Bazel build now supports building with Cuda with an optional parameter cupdlp_gpu.

v1.11.0

Build changes

Replace command line parsing library with Cpp11 #2211

CMake updates #2286, the root of the HiGHS source files is now highs/, rather than src/

Add missing include to zstr needed for gcc v15 and clang v19 #2313

Updates for intel llvm compiler on linux #2257

Build directory for Windows MSVC now Release/bin replacing bin/Release #2376

Code changes

Fixed incorrect assertion in HighsMipSolver::solutionFeasible() (fixing #2204)

As part of #2251 cuPDLP-C will start from the incumbent solution in HiGHS. For a model that has been changed, the user must supply a starting solution via a call to Highs::setSolution

getColIntegrality now returns HighsVarType::kContinuous when model_.lp_.integrality_ is empty (fixing #2261)

Now ensuring that when solving a scaled LP with useful but unvalidated basis, it does not lose its scaling after validation, since the scaling factors will be applied to the solution (fixing #2267)

By setting non-empty values of options read_solution_file, read_basis_file, write_model_file (with extension .lp or .mps), write_solution_file, solution_file, write_basis_file, these files will be read or written when calling Highs::run(). Hence options previously only available via the command line interface can be use (for example) by modelling languages that only call Highs::run() (fixing #2269).

Bug #2273 fixed

Added the feasibility jump heuristic as per #1423. This is on by default, but using the option mip_heuristic_run_feasibility_jump=false switches it off.

ZI rounding and shifting MIP primal heuristics have been added (see #2287). They are off by default, but can be activated by setting the options mip_heuristic_run_zi_round and mip_heuristic_run_shifting to be true. Options mip_heuristic_run_rins, mip_heuristic_run_rens and mip_heuristic_run_root_reduced_cost to run the RINS, RENS and rootReducedCost heuristics have been added. These are true by default, but setting them to be false can accelerate the MIP solver on easy problems.

Added Highs_changeRowsBoundsByRange to C API, fixing #2296

Corrected docstrings for Highs_getReducedRow, motivated by #2312

LP file reader no longer fails when there is no objective section. Fix is #2316, but this exposes code quality issue #2318

Added a max scale factor (+1024) when scaling up coefficients in preprocessBaseInequality and postprocessCut. Fix is #2337

Corrected the bounds used in when strengthening coefficients in HPresolve::rowPresolve, fixing #1517

Fixed numerical error in highs/mip/HighsCliqueTable.cpp, closing #2320

Fixed bug in highs/mip/HighsFeasibilityJump.cpp, closing #2331

Tightened CMIR cuts, leading to small performance gain, closing #2333

Scaling the tolerance in forcing row reduction to avoid use of rows with small coefficients and bounds, closing #2290

Fixed bug when calculating a coefficient in one of the cuts in separateImpliedBounds in highs/mip/HighsImplications.cpp

Added CSECTION to the exceptions for keywords that are followed by text, and thus cannot be used as names of columns, RHS, ranges, bounds etc.

Introduced the following KKT error measures to HighsInfo: num_relative_primal_infeasibilities; max_relative_primal_infeasibility; num_relative_dual_infeasibilities; max_relative_dual_infeasibility; num_primal_residual_errors; max_primal_residual_error; num_dual_residual_errors; max_dual_residual_error; num_relative_primal_residual_errors; max_relative_primal_residual_error; num_relative_dual_residual_errors; max_relative_dual_residual_error; num_complementarity_violations; max_complementarity_violation; primal_dual_objective_error. The relative values are used to assess whether a solution deemed to be optimal by the first order LP solver cuPDLP-C or interior point solver IPX (without crossover) is truly acceptable. They also enable users to determine whether a solution corresponding to HighsModelStatus::kUnknown is acceptable to them as optimal. Also introduced options complementarity_tolerance used to assess whether the (relative) primal-dual objective error is acceptable, and kkt_tolerance which, if set to a value other than kDefaultKktTolerance = 1e-7 is used as the tolerance for all the KKT error measures. The HiGHS documentation has been updated to reflect the new options and HighsInfo data, and logging messages indicate when KKT error measures are not satisfied, despite the solver considering the LP solution to be optimal.

Added a max scale factor (+1024) when scaling up coefficients in preprocessBaseInequality and postprocessCut. Fix is #2337.

Renamed HighsOptions::pdlp_d_gap_tol to HighsOptions::pdlp_optimality_tolerance for consistency with IPM

Renamed HighsOptions::complementarity_tolerance to HighsOptions::optimality_tolerance for consistency with IPM and PDLP

v1.10.0

Build changes

Added code coverage report

Replaced command line parsing library with CLI11. Removed C++17 reference with cxxopts, which is no longer in HiGHS

Code changes

Any LP offset is communicated to the IPM solver, and used in logging and primal/dual objective calculations.

If there is a valid basis when Highs::run() is called, presolve isn't skipped unless the solver option is "simplex" or "choose" (when simplex will always be chosen if there is an advanced basis).

Added basis solve methods to highspy

Added methods to get primal/dual ray and dual unboundedness direction to highspy

When a presolved LP has model status kUnknown, rather than returning this to the user, it performs postsolve and then uses the basis to solve the original LP

Fixed bug in presolve when pointers stored in HighsMatrixSlice get invalidated when the coefficient matrix is reallocated (e.g. when non-zeros are added in HPresolve::addToMatrix)

Primal and dual residual tolerances - applied following IPM or PDLP solution - now documented as options

Highs::getCols (Highs::getRows) now runs in linear time if the internal constraint matrix is stored column-wise (row-wise). Added ensureColwise/Rowwise to the Highs class, the C API and highspy so that users can set the internal constraint matrix storage orientation

When columns and rows are deleted from the incumbent LP after a basic solution has been found, HiGHS no longer invalidates the basis. Now it maintains the basic and nonbasic status of the remaining variables and constraints. When the model is re-solved, this information is used to construct a starting basis.

Fixed bugs in presolve

When running from the command line, changes to default option values are reported

Added callback to allow users to supply integer feasible solutions to the MIP solver during execution

Bug fix for primal heuristics in the MIP solver

Model status is set appropriately when a solver's claimed optimality doesn't satify the general HiGHS primal/dual feasibilily tolerances. Affects IPM without crossover and PDLP

Command line parsing now done with pure C++11 code

Added command line flags to read basis from and write basis to a file

Bug fixes in records of primal/dual rays

MPS read utility improved. Error logging is now less verbose; inability to handle USERCUTS section is properly logged

Implemented lifting for probing as described by Achterberg et al in Presolve Reductions in Mixed Integer Programming. INFORMS Journal on Computing 32(2):473-506 (2019). Not used by default, but option mip_lifting_for_probing allows it to be used with two levels of modification

Propagated updates from cuPDLP-C

Added GPU support for cuPDLP-C

v1.9.0

Build changes

Python: Source Distribution update, added to PyPI

Code changes

HiGHS now handles multiple linear objectives by either blending using weights, or performing lexicographic optimization: see https://ergo-code.github.io/HiGHS/stable/guide/further/#guide-multi-objective-optimization

Fixed minor bug in bound checking in presolve

Fixed bug in floor(HighsCDouble x) and ceil(HighsCDouble x) when argument is small

Added some sanity checks to Highs::writeLocalModel to prevent segfaults if called directly by a user

v1.8.1

Build changes

Added wheels for Python 3.13

Updated command line options and moved them out of the library and into the executable

Code changes

When primal infeasiblity is detected in presolve, no dual ray is available so, previously, the has_dual_ray parameter of Highs::getDualRay returned false and that was it. Now, if a null pointer is not passed for dual_ray_value, Highs::getDualRay will compute a dual ray - at the cost of solving the feasiblility LP without presolve. The same is now true for Highs::getPrimalRay. Highs::getDualUnboundednessDirection has been introduced to determine the product between the constraint matrix and the dual ray, forcing the calculation of the latter if necessary. Once a dual ray is known for the incumbent model in HiGHS, subsequent calls to Highs::getDualRay and Highs::getDualUnboundednessDirection will be vastly cheaper

The method Highs::getDualObjectiveValue now exitsts to compute the dual objective value, returning HighsStatus::kError if it is not possible.

The method Highs::getStandardFormLp now exists to return the incumbent LP in standard form - overlooking any integrality or Hessian. To determine the sizes of the vectors of data, the method is called without specifying pointers to the data arrays.

Added documentation on the use of presolve when solving an incumbent model, and clarifying the use of the method Highs::presolve.

HiGHS will now read a MIPLIB solution file

Added time limit check to HPresolve::strengthenInequalities

Added getColIntegrality to highspy

Now computing the primal-dual integral, reporting it, and making it available as HighsInfo::primal_dual_integral

Trivial primal heuristics "all zero", "all lower bound", "all upper bound", and "lock point" added to the MIP solver

v1.8.0

Code updates

We believe that the issue of HiGHS "hanging" when run on Windows with threads not equal to 1 has been fixed!

Added int64_t mip_total_lp_iterations to HighsCallbackDataOut and modified accessor function

Highs::writeSolution and Highs::writeBasis now being done via HighsIO logging, so can be redirected to logging callback.

Introduced const double kHighsUndefined as value of undefined values in a user solution. It's equal to kHighsInf

Added Highs::setSolution(const HighsInt num_entries, const HighsInt* index, const double* value); to allow a sparse primal solution to be defined. When a MIP is solved to do this, the value of (new) option mip_max_start_nodes is used for mip_max_nodes to avoid excessive cost

Added options write_presolved_model_to_file and write_presolved_model_file so that presolved model can be written via a command line option

Added Highs::feasibilityRelaxation to solve the problem of minimizing a (possibly weighted) sum of (allowable) infeasibilities in an LP/MIP.

Added Python utility examples/plot_highs_log.py (due to @Thell) to visualise progress of the MIP solver.

Added minimal documentation of solvers and how simplex variants can be run

Methods receiving matrix data where only small values are explicit zeros (so removed internally) are now silent and return HighsStatus::kOk (since internal matrix is exact)

Now multiplying by pre-computed reciprocals rather than performing divisions in loops in simplex solver: LP performance improvement ~2.5%

Primal and dual residuals after IPM and cuPDLP-C are checked, and corrections applied to row solution and column duals

Highs::passModelName added to allow name to be given to the incumbent model

Memory leaks in cuPDLP-C fixed

Bug fixed in MIP presolve

v1.7.2

Build changes

The python wrapper highspy is now available for aarch64 on manylinux
This allows highs to be run through Python on AWS arm64

Bug fix for fortran on macOS

Code changes

The accessor function Highs_getCallbackDataOutItem in the C API means
that pdlp_iteration_count can be moved back to where it was inserted
into the HighsCallbackDataOut struct in v1.7.0, which broke the C
API. This fixes #1812

Some duplicate code has been eliminated from the MIP solver, and
modifications made to eliminate compiler warnings

Declaration of the (deprecated) method char* highsCompilationDate()
has been corrected

Fixed bug when describing integrality status during the human-readable solution write

v1.7.1

Version 1.7.1 of HiGHS contains several updates

Build changes

HiGHS on nixpkgs

HiGHS now has a flake.nix to build the binary, allowing nix users to try it out.

Python build update

On PyPI, highspy is now available as v1.7.1, bringing the Python and C++ versions of HiGHS into line.

Windows versions

Fixed version info of shared library
Added version info to executable

Code changes

Inserting pdlp_iteration_count into the struct HighsCallbackDataOut (for v1.7.0) breaks the C API, so it has been moved to the end of the struct, and an accessor function Highs_getCallbackDataOutItem has been added.

References to the compilation date have been removed from the build and code of HiGHS, so that binaries for the same version compiled on different days are identical. Methods to print compilation dates are deprecated.

setBasis has been added to highspy.

writePresolvedModel has been added, allowing the presolved model to be exported as a file.

The saved MIP solution pool is now populated with the optimal solution when presolve reduces a MIP to empty.

There is now a logging message and error return when a user-supplied solution or basis is rejected due to the size of any vector being incompatible with the dimensions of the incumbent model.

Memory allocation errors in presolve are caught and Highs::run() returns HighsStatus::kError with model_status_ = HighsModelStatus::kMemoryLimit.

QP solver logging is now neater and quieter.

Any Hessian for the incumbent model is modified with zero entries when adding columns to the model, and rows/columns are removed when columns are deleted from the model.

The has been a minor bug fix in the MIP presolve

QP solver will now hot start given a basis and solution

v1.7.0

Version 1.7.0 of HiGHS contains several new developments.

HiGHS now offers the exciting new first order LP solver (cuPDLP-c). Ours is currently only a serial CPU implementation, so performance isn't spectacular, but we aim to offer the GPU implementation in due course. To run PDLP, choose the option solver=pdlp. Note that there is currently no time-out available for PDLP, and the termination criteria for cuPDLP-c may mean that the HiGHS optimality conditions are not satisfied. See README.md .

The HiGHS interior point solver now allows analytic centre calculations to be performed. This is done by setting the HiGHS option run_centring to be true. Other new options allow the centring calculations to be controlled.

When Highs::run() is called, ranges of the matrix, costs, bounds and RHS are reported, together with advice on setting the new HiGHS options user_cost_scale and used_bound_scale if there are extreme values.

After solving an LP, the method Highs::getIllConditioning tries (in an approach similar to that used by Gurobi) to identify constraints or basic variables that contribute most to ill-conditioning of the basis matrix.

Logging from the interior point solver is now consistent with logging from the simplex and MIP solvers.

The Python interface has been updated, with several overlooked methods having been added

Considerable modifications and fixes have been added to the build system, in particular for Python. highspy is no longer built with meson, rather a combination of setuptools and cmake.

Bugs in the QP and MIP solvers have been fixed

Thanks are due to due to @fwesselm @feldmeier and @Coloquinte

v1.6.0

Added logging, improving solution and interrupt callbacks to C++ and C for a single user-defined callback method. Specifically

• New logging callback consistent with new callback method. Old logging callback is deprecated
• Callback when MIP logging takes place
• Callback when MIP solver finds an improving integer feasible solution
• Interrupt callbacks for simplex, interior point and MIP solvers

Added the use of the objective_target option to terminate the MIP solver when an integer feasible solution at least as good as this value has been found.

Bug fixes