Find multiple solutions using pyomo and gurobi

Question

I am solving a MILP using Gurobi and Pyomo. I would like to obtain as many optimal solutions as possible. Here is what I have so far:

opt = SolverFactory('gurobi_persistent')
n_of_s = 10
opt.set_instance(model)
opt.set_gurobi_param('PoolSolutions', n_of_s)
opt.set_gurobi_param('PoolSearchMode', 2)
opt.solve(model, tee=True)
opt.set_gurobi_param('SolutionNumber',2) 
model.pprint()

At some point Gurobi displays Solution count 3: 5000 5000 5000. However, when trying to access the value of optimal variables, I can only access one solution.

I have tried using the Xn attribute, but Gurobi states AttributeError: '_GeneralVarData' object has no attribute 'Xn'.

Answer 1

Yes, you can. For example, with Pyomo package, the gurobi solver is selected using the following code:

opt = SolverFactory("gurobi", solver_io='python')
opt.options["NonConvex"] = 2
opt.options['MIPGap'] = 0.01
opt.options['SolCount'] = 2

results = opt.solve(model, load_solutions=True, tee=True)

The attributes of gurobi solver can be visited by using opt._solver_model. For example, you can see the number of solutions by calling its attribute of 'SolCount' as opt._solver_model.SolCount. Similarly, you can access the multiple solutions by using its attribute Xn in the same way as using "Gurobi" directly. For example, you can access all the solutions in this way:

xs=[]
for s in range(opt._solver_model.SolCount):
   opt._solver_model.params.SolutionNumber = s
   x=opt._solver_model.getAttr("Xn")
   xs.append(x)

Similarly, you can access all gurobi solver's attributes. BTW, you can read the code under pyomo package to see how pyomo visits gurobi solver in the directory of ...\Lib\site-packages\pyomo\solvers\plugins\solvers\gurobi_direct.py. Hope it helps.