JuMP model is feasible where gurobipy model is infeasible

回答済み

Josh Kirk

2023年07月05日 13:03 編集済み

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I am coming to gurobipy from JuMP (Julia) and having problems with feasibility.

 

I expect the following problem to be feasible but gurobi states it is not

```python

T = np.array([[ 0, -10, -10],

[ 0, 10, 30]])

As = np.array([

[-1,1],

[1,-1],

])

nc, nt = T.shape

nl = As.shape[0]

m = gp.Model()

D = m.addMVar(shape=(nc, nt), name="D")

gamma =m.addMVar(shape=(nc, nt), name="gamma", lb = -GRB.INFINITY, ub = 0)

Q = m.addMVar(shape=(nl, nt), name="Q", lb=0, ub = GRB.INFINITY)

m.addConstr(As@Q == T + D)

m.addConstr(gamma <= D, name= "D exceeds gamma")

m.setObjective(gp.quicksum(-gamma[i,t] for i in range(nc) for t in range(nt)), GRB.MINIMIZE)

m.optimize()

```

 

I have tried computing the IIS and relaxing feasibility but I have not found this helpful. Normally I would doubt myself but the equivalent problem in JuMP solves with the expected solution of 20 

```julia

using JuMP, Gurobi

T= [

0 -10 -10

0 10 30

]

As= [

-1 1

1 -1

]

nc, nt = size(T)

nl = size(As,1)

m =Model(Gurobi.Optimizer)

@variable(m, D[1:nc, 1:nt])

@variable(m, gamma[1:nc, 1:nt] ≤ 0)

@variable(m, 0≤ Q[1:nl, 1:nt])

@constraint(m, As*Q .== T+D)

@constraint(m, gamma .≤ D)

@objective(m, Min, -sum(gamma))

optimize!(m)

```

 

JuMP is a high level package which then uses MathOptInterface.jl to interact with Gurobi.jl. I know they do some things under the hood to keep JuMP high-level, but I wouldn't expect that to make the problem feasible. 

 

I expect I am using gurobi.py incorrectly. 

 

Thanks,

Josh

関連

• Infeasible
• Julia
• Wrong Result

0

• 正式なコメント

  

  Simranjit Kaur

  • Gurobi Staff

  2026年11月13日 01:41

  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.
• 

  Marika Karbstein

  • Gurobi Staff

  2023年07月05日 14:26

  Hi Josh,

  Using gurobipy the default lower bounds for the variables are 0, see Model.addMVar().
  If you change the lower bound for the D variables to -Infinity, the model becomes feasible.

  Cheers,
  Marika

  1
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  Josh Kirk

  2023年07月05日 15:01

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  Marika,

  Thank you. A very silly mistake as I had realised this for gamma.

  Josh

  0

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