•  Gurobi Staff

Hi Wenbo,

We can use list comprehension as below:

[var for var in model.getVars() if "gamma" in var.VarName]
The above will iterate over all variables. To do it more efficiently such that only the variables $$\texttt{gamma}$$ are retrieved, we can do it like below:
names_to_retrieve = (f"gamma[{i},{j}]" for i in range(20) for j in range(2))[model.getVarByName(name) for name in names_to_retrieve]

Best regards,

Maliheh

•    Dear Maliheh,

I'm using Gurobi in Python and I'm trying to solve a model that have multiple optimal solution, with one binary and one continuous variable.

y=m.addVars(SC_id,vtype=GRB.BINARY,name='facility')x=m.addVars(PP_id,SC_id,lb=0,ub=1,vtype=GRB.CONTINUOUS,name='assignment')

Now, I want to retrieve decision variables for every optimal solution. I wrote a piece of code as following:

count=0for aa in range(m.SolCount):count+=1m.Params.SolutionNumber = aaprint("solution: ", count)for var in m.getVars():if var.xn > 0:if "assignment" in var.VarName:print ('%s %g' %(var.varName, var.xn))

and this is the results of my code:

solution: 1assignment[11,1] 1 assignment[12,1] 1 assignment[23,4] 0.6 ..

Now I want to save the [i,j] inside the brackets along with the value of assignment. Because right now I have them in terms of string. Since I want to compute Risk of each solution, I need to have value of decision variables for each solution. If I had one optimal solution, below code would work (R[i,j] was computed before). But now that I have multiple optimal solution, I do not know how to access the decision variables for each solution number.

A=0for i in PP_id:for j in SC_id:if x[i,j].x>0:A+=x[i,j].x*R[i,j]

•  Gurobi Staff

Hi Maedeh,

The simplest approach would be to manipulate the variable string names to retrieve the indices $$i$$ and $$j$$. You can modify the assignment variable names, $$\texttt{assignment[i,j]}$$ like below:

i, _, j = (    var.VarName.replace("assignment", "")    .replace("[", "")    .replace("]", "")    .partition(","))

A cleaner approach would be to use regular expressions like below, but the first approach is easier to understand.

import repattern = re.compile("assignment$((?P<i>\d+),(?P<j>\d+))$")i, j = pattern.match(var.VarName).groupdict().values()

Best regards,
Maliheh
•   Hi Maliheh,

Quick question, I wanted to know the value of some of my variables during the optimization using a callback function (where=MIPSOL). However, I get an error during the callback when I want to access the .X attribute of my variables. Is there any reason for that ? Any workaround ? Thank you.

•  Gurobi Staff

Hi Sophie,

You need to use the method Model.cbGetSolution(vars) to retrieve values from a new MIP solution. There is a clear example of how to do this at the bottom of the documentation page linked above that you can check.

Best regards,

Maliheh

•   Hi Maliheh,

I saw this solution but the problem is I want to only access specific variables by name and not by the variable object.I tried the following but I still get an error:

names_to_retrieve = (f"{name}[{i}]" for i in range(M))vars_obj = [model.getVarByName(name) for name in names_to_retrieve]vars_value = [model.cbGeSolution(var) for var in vars_ob]print("Name = {}, Objective value = {}".format(name, sum(vars_value))