Solver-specific method for constructing a solver problem from a cobra.Model. This can be tuned for performance using kwargs
with pyglpk the parameters are set during the solve phase
Smart interface to optimization solver functions that will convert the cobra_model to a solver object, set the parameters, and try multiple methods to get an optimal solution before returning the solver object and a cobra.Solution (which is attached to cobra_model.solution)
cobra_model: a cobra.Model
returns a dict: {‘the_problem’: solver specific object, ‘the_solution’: cobra.Solution for the optimization problem’}
A performance tunable method for updating a model problem file
lp: a pyGLPK 0.3 problem
For pyGLPK it is necessary to provide the following parameters, if they are not provided then the default settings will be used: tolerance_optimality, tolerance_integer, lp_method, and objective_sense