gurobipy.GurobiError: Constraint has no bool value (are you trying "lb <= expr <= ub"?)
Answered
Hi, I am new with Gurobi. I have faced some problems recently when programming my models. It would be grateful if get your professional advice.Thanks.
An error occurred after running the following code：
TS_i = model.addVars(n, vtype=GRB.INTEGER, name="TS_i")
TE_i = model.addVars(n, vtype=GRB.INTEGER, name="TE_i")
lambda_i_p = {}
for i in V:
for p in P:
lambda_i_p[i, p] = model.addVar(vtype=GRB.CONTINUOUS, name=f"lambda_i_p_{i}_{p}")
# Create constraints to represent the relationship between lambda_ip and TE_i, TS_i
for i in V:
for p in P:
if TS_i[i] <= p and p<= TE_i[i]:
model.addConstr(lambda_i_p[i, p]* (TE_i[i] - TS_i[i] + 1)== D_i[i] , name=f"constraint_lambda_ip_{i}_{p}")
Here is the details about the error：
Traceback (most recent call last):
File "D:\pythonproject\lib\site-packages\IPython\core\interactiveshell.py", line 3505, in run_code
exec(code_obj, self.user_global_ns, self.user_ns)
File "<ipython-input-2-55c84a859894>", line 1, in <module>
runfile('D:\\PyCharm Pro 2023.2\\pythonProject\\9.5 test大规模+双目标.py', wdir='D:\\PyCharm Pro 2023.2\\pythonProject')
File "D:\PyCharm Pro 2023.2\plugins\python\helpers\pydev\_pydev_bundle\pydev_umd.py", line 198, in runfile
pydev_imports.execfile(filename, global_vars, local_vars) # execute the script
File "D:\PyCharm Pro 2023.2\plugins\python\helpers\pydev\_pydev_imps\_pydev_execfile.py", line 18, in execfile
exec(compile(contents+"\n", file, 'exec'), glob, loc)
File "D:\PyCharm Pro 2023.2\pythonProject\9.5 test大规模+双目标.py", line 112, in <module>
if TS_i[i] <= p and p<= TE_i[i]:
File "src\gurobipy\tempconstr.pxi", line 57, in gurobipy.TempConstr.__bool__
gurobipy.GurobiError: Constraint has no bool value (are you trying "lb <= expr <= ub"?)
I think the problem should occur in this line of code.
if TS_i[i] <= p and p<= TE_i[i]:
because TS_i andTE_i here is thedecision variable , but I don’t know how to modify it.
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Hi Qiuyan,
It is not possible to use Gurobi variable objects in if-clauses because there is no value associated with them to be used in comparison. The reason for the error you see is well-explained in the article Constraint has no bool value (are you trying "lb <= expr <= ub"?). Please check the cause number 3).
I assume you would like to model the following constraint:
\[\mbox{if}~~ TS_i \leq p ~\mbox{and}~ TE_i \geq p \rightarrow \lambda_{ip} (TE_i - TS_i + 1) = D_i \]
To implement the above constraint, you need to use three binary auxiliary variables to model the relationships below:
- \(\mbox{if}~~ TS_i \leq p \rightarrow x_i = 1 \)
- \(\mbox{if}~~ TE_i \geq p \rightarrow y_i = 1 \)
- \(\mbox{if}~~ x_i = 1 ~\mbox{and}~ y_i= 1 \rightarrow z_i = 1 \)
- \(\mbox{if}~~ z_i = 1 \rightarrow \lambda_{ip} (TE_i - TS_i + 1) = D_i \)
You can use Gurobi Python APIs for the Indicator constraint to implement the above relationships.
Best regards,
Maliheh
1 -
Hello，Maliheh,Thanks for your advice,it's helpful.I tried to modeling the constraint using the method above.However, the value of variable: lambda_i_p[i, p] all become 0.And I check the code，I think the problem may still lie in this section of the code.Which part do you think the problem occurred?
# Define the lambda_i_p derived variables
lambda_i_p = {}
for i in V:
for p in P:
lambda_i_p[i, p] = model.addVar(vtype=GRB.CONTINUOUS, name=f"lambda_i_p_{i}_{p}")
# Add auxiliary variables x, y, and z
x = {}
y = {}
z = {}
for i in V:
for p in P:
x[i, p] = model.addVar(vtype=GRB.BINARY, name=f"x_{i}{p}")
y[i, p] = model.addVar(vtype=GRB.BINARY, name=f"y_{i}{p}")
z[i, p] = model.addVar(vtype=GRB.BINARY, name=f"z_{i}{p}")
# Add constraints: x[i]=1 if and only if TS_i[i] <= p
# Add constraints: y[i]=1 if and only if TE_i[i] >= p
# Add constraints: z[i]=1 if and only if x[i]=1 and y[i]=1
# Add constraint: lambda_i_p[i, p] * (TE_i[i] - TS_i[i] + 1) == D_i[i] when z[i]=1 holds
for i in V:
for p in P:
model.addConstr((x[i, p] == 1) >> (TS_i[i] <= p), name=f"constraint_x_{i}_{p}")
model.addConstr((y[i, p] == 1) >> (p <= TE_i[i]), name=f"constraint_y_{i}_{p}")
model.addConstr(z[i, p] == x[i, p] * y[i, p], name=f"constraint_z_{i}{p}")
model.addConstr(lambda_i_p[i, p] * (TE_i[i] - TS_i[i] + 1) == D_i[i] * z[i, p], name=f"constraint_lambda_ip_{i}_{p}")0 -
Do you get an error? Or do you mean that having all \(\lambda_{ip}\) assigned to 0 is not what you expect to see in the optimal solution?
Please note that you have modelled different relationships. In your implementation version below, if \(z_i = 0\), the expression \(\lambda_{ip}(TE_i - TS_i +1)\) must be 0 then. However, in the constraint \(\mbox{if}~ z_i = 1 ~ \rightarrow ~ \lambda_{ip} (TE_i - TS_i +1) = D_i\), we do not impose any constraint on the value of \(\lambda_{ip} (TE_i - TS_i +1)\) if \(z_i = 0\).
model.addConstr(lambda_i_p[i, p] * (TE_i[i] - TS_i[i] + 1) == D_i[i] * z[i, p], name=f"constraint_lambda_ip_{i}_{p}")
The same is true for all the other constraints you have implemented.
- The constraint \(\mbox{if}~~ TS_i \leq p \rightarrow x_i = 1 \) is different from the constraint \(\mbox{if}~~ x_i = 1 \rightarrow TS_i \leq p \). To model the former relationship using Gurobi Python API for indicator constraints, you can implement its equivalent logical contrapositive in the form \(\mbox{if}~~ x_i \neq 1 \rightarrow TS_i \nleq p \) which is \(\mbox{if}~~ x_i = 0 \rightarrow TS_i \geq p + \epsilon \).
- The constraint \(\mbox{if}~~ TE_i \geq p \rightarrow y_i = 1 \) is different from the constraint \(\mbox{if}~~ y _i = 1 \rightarrow TE_i \geq p\) (see above).
- The constraint \(\mbox{if}~~ x_i = 1 ~\mbox{and}~ y_i= 1 \rightarrow z_i = 1 \) is different from \(z_i = x_i y_i\). In the former version, we are not imposing any constraint on the value of \(z_i\) if, for example, \(x_i = 0\) and \(y_i = 1\).
Best regards,
Maliheh
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