Model proven infeasible by zero objective heuristic
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Hello, I have found that Gurobi claims the model is infeasible with the following message (Note that I'm solving a minimization problem):
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Gurobi Optimizer version 9.5.2 build v9.5.2rc0 (win64)
Thread count: 4 physical cores, 8 logical processors, using up to 8 threads
Optimize a model with 50551 rows, 61582 columns and 166156 nonzeros
Model fingerprint: 0x6c7938d8
Model has 12936 general constraints
Variable types: 61582 continuous, 0 integer (0 binary)
Coefficient statistics:
Matrix range [1e-03, 5e+04]
Objective range [7e+01, 7e+04]
Bounds range [2e+04, 6e+05]
RHS range [2e-04, 1e+03]
Variable types: 86914 continuous, 26412 integer (25872 binary)
Deterministic concurrent LP optimizer: primal and dual simplex
Showing first log only...
Concurrent spin time: 0.00s
Solved with dual simplex
Root relaxation: objective 6.932182e+07, 39985 iterations, 2.02 seconds (0.98 work units)
Nodes | Current Node | Objective Bounds | Work
Expl Unexpl | Obj Depth IntInf | Incumbent BestBd Gap | It/Node Time
0 0 6.9322e+07 0 4001 - 6.9322e+07 - - 2s
0 0 6.9322e+07 0 4001 - 6.9322e+07 - - 6s
Model proven infeasible by zero objective heuristic
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Could you explain what "Model proven infeasible by zero objective heuristic" means? and any alternative/ideas to resolve this issue?
Best,
Eunseok Kim
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Gurobi Staff
Hi Eunseok Kim,
The zero objective heuristic sets the objective function to \(0\) and solves a feasibility problem. Gurobi has proven the feasibility problem to be infeasible which proves the original model to be infeasible.
For how to deal with infeasibility please refer to How do I determine why my model is infeasible?
Given the size of your model, I would first try to reduce the size to make it easier to analyze.Best regards,
Jaromił0 -
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