Reputation: 115
I have programmed an algorithm that finds feasible points for mixed-integer convex optimization problems. Now I wish to compare it with the Feasibility Pump for mixed-integer nonlinear programms on a testbed from the MINLPlib library.
I have access to the BONMIN solver from the Coin OR project, where the Feasibility Pump is also implemented, via Pyomo. Here is a list of possible options for this solver.
My questions are
Are the following options correct to test (plain vanilla) feasibility pump?
opt = SolverFactory('bonmin')
opt.options['bonmin.algorithm'] = 'b-ifp' # Iterated Feasibility Pump as solver
opt.options['bonmin.pump_for_minlp'] = 'yes' # Is this needed?
opt.options['bonmin.solution_limit'] = '1' #For terminating after 1st feasible point
If not, any hint how to do it correctly is appreciated.
Upvotes: 0
Views: 224
Reputation: 1718
Pyomo calls Bonmin through the ASL (AMPL solver library) interface. Therefore, whatever options would work for AMPL should be the same ones that are appropriate here.
As for the iteration information, there are various ways of capturing the print output and parsing it to retrieve the desired information. The most straightforward way may be to pipe the output to a file and read it as part of a small post-processing script/function.
Upvotes: 1