compute_optimal_bounds

(function from pyomo.gdp.plugins.partition_disjuncts)

pyomo.gdp.plugins.partition_disjuncts.compute_optimal_bounds(expr, global_constraints, opt)

Returns a tuple (LB, UB) where LB and UB are the results of minimizing and maximizing expr over the variable bounds and the constraints on the global_constraints block. Note that if expr is nonlinear, even if one of the min and max problems is convex, the other won’t be!

Arguments:

exprExpressionBase

The subexpression whose bounds we will return

global_constraintsBlockData

A Block which contains the global Constraints and Vars of the original model

optSolverBase

A configured Solver object to use to minimize and maximize expr over the set defined by global_constraints. Note that if expr is nonlinear, opt will need to be capable of optimizing nonconvex problems.