Model proven infeasible by zero objective heuristic

Answered

Eunseok Kim

December 05, 2022 06:29

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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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• Official comment

  

  Simranjit Kaur

  • Gurobi Staff

  November 13, 2026 01:51

  This post is more than two years old. Some information may not be up to date. For current information, please check the Gurobi Documentation or Knowledge Base. If you need more help, please create a new post in the community forum, or try Gurobot, our chatbot interface offering instant, expert-level support.
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  Jaromił Najman

  • Gurobi Staff

  December 05, 2022 09:59

  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, 
  Jaromił

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