highs: wrong optimization result with presolve since highs v1.14.0

[maurerle]

Version Checks (indicate both or one)

• I have confirmed this bug exists on the lastest release of Linopy.

• I have confirmed this bug exists on the current master branch of Linopy.

Issue Description

optimizing:

minimize 2x + y
s. t. 2*x0 + y0 >= 10
with x binary
and 9 <= y

should result in y=10 and x=0 but results (as with HiGHS 1.11) - but gives the wrong result with HiGHS 1.14 and linopy.

Besides downgrading, it helps to disable presolve (m.solve(solver_name='highs', presolve= "off")).

Running HiGHS 1.14.0 (git hash: 7df0786): Copyright (c) 2026 under MIT licence terms
MIP linopy-problem-hu0mxzpo has 1 row; 2 cols; 2 nonzeros; 1 integer variables (1 binary)
Coefficient ranges:
 Matrix [1e+00, 2e+00]
 Cost [1e+00, 2e+00]
 Bound [1e+00, 9e+00]
 RHS [1e+01, 1e+01]
Presolving model
1 rows, 1 cols, 1 nonzeros 0s
0 rows, 0 cols, 0 nonzeros 0s
Presolve reductions: rows 0(-1); columns 0(-2); nonzeros 0(-2) - Reduced to empty
Presolve: Optimal

Src: B => Branching; C => Central rounding; F => Feasibility pump; H => Heuristic;
 I => Shifting; J => Feasibility jump; L => Sub-MIP; P => Empty MIP; R => Randomized rounding;
 S => Solve LP; T => Evaluate node; U => Unbounded; X => User solution; Y => HiGHS solution;
 Z => ZI Round; l => Trivial lower; p => Trivial point; u => Trivial upper; z => Trivial zero

 Nodes | B&B Tree | Objective Bounds | Dynamic Constraints | Work 
Src Proc. InQueue | Leaves Expl. | BestBound BestSol Gap | Cuts InLp Confl. | LpIters Time

 0 0 0 0.00% 11 11 0.00% 0 0 0 0 0.0s

Solving report
 Model linopy-problem-hu0mxzpo
 Status Optimal
 Primal bound 11
 Dual bound 11
 Gap 0% (tolerance: 0.01%)
 P-D integral 0
 Solution status feasible
 11 (objective)
 0 (bound viol.)
 0 (int. viol.)
 0 (row viol.)
 Timing 0.00
 Max sub-MIP depth 0
 Nodes 0
 Repair LPs 0
 LP iterations 0
Status: ok
Objective: 11.0
x0: 1.0
y0: 9.0

Reproducible Example

import linopy

# 1. Initialize the model
m = linopy.Model()

# 2. Define Variables
# x0 is binary, y0 has a lower bound of 9
x0 = m.add_variables(binary=True, name='x0')
y0 = m.add_variables(lower=9, name='y0')

# 3. Add Constraints
m.add_constraints(2*x0 + y0 >= 10, name='c0')

# 4. Set Objective (Minimize 2*x0 + y0)
m.add_objective(2*x0 + y0)

# 5. Solve using HiGHS
m.solve(solver_name='highs')

# 6. Display Results
print(f"Status: {m.status}")
print(f"Objective: {m.objective.value}")
print(f"x0: {x0.solution.item()}")
print(f"y0: {y0.solution.item()}")

Expected Behavior

Running HiGHS 1.11.0 (git hash: 364c83a): Copyright (c) 2025 HiGHS under MIT licence terms
MIP linopy-problem-5rmiip7y has 1 rows; 2 cols; 2 nonzeros; 1 integer variables (1 binary)
Coefficient ranges:
 Matrix [1e+00, 2e+00]
 Cost [1e+00, 2e+00]
 Bound [1e+00, 9e+00]
 RHS [1e+01, 1e+01]
Presolving model
0 rows, 1 cols, 0 nonzeros 0s
0 rows, 0 cols, 0 nonzeros 0s
Presolve: Optimal

Src: B => Branching; C => Central rounding; F => Feasibility pump; J => Feasibility jump;
 H => Heuristic; L => Sub-MIP; P => Empty MIP; R => Randomized rounding; Z => ZI Round;
 I => Shifting; S => Solve LP; T => Evaluate node; U => Unbounded; X => User solution;
 z => Trivial zero; l => Trivial lower; u => Trivial upper; p => Trivial point

 Nodes | B&B Tree | Objective Bounds | Dynamic Constraints | Work 
Src Proc. InQueue | Leaves Expl. | BestBound BestSol Gap | Cuts InLp Confl. | LpIters Time

 0 0 0 0.00% 10 10 0.00% 0 0 0 0 0.0s

Solving report
 Model linopy-problem-5rmiip7y
 Status Optimal
...
Status: ok
Objective: 10.0
x0: 0.0
y0: 10.0

Installed Versions

Details

Replace this line.

[odow]

Previously reported (and already fixed) upstream: ERGO-Code/HiGHS#2957

Until the next release, your options are: disable presolve, or use v1.13.