Bases: object
This class takes the constructed expression from MCPP_Visitor and
allows for MC methods to be performed on pyomo expressions.
__repn__(self): returns a display of an MC expression in the form:
F: [lower interval : upper interval ] [convex underestimator :
concave overestimator ] [ (convex subgradient) : (concave subgradient]
lower(self): returns a float of the lower interval bound that is valid
across the entire domain
upper(self): returns a float of the upper interval bound that is valid
across the entire domain
concave(self): returns a float of the concave overestimator at the
current value() of each variable.
convex(self): returns a float of the convex underestimator at the
current value() of each variable.
##Note: In order to describe the concave and convex relaxations over
the entire domain, it is necessary to use changePoint() to repeat the
calculation at different points.
subcc(self): returns a ComponentMap() that maps the pyomo variables
to the subgradients of the McCormick concave overestimators at the
current value() of each variable.
subcv(self): returns a ComponentMap() that maps the pyomo variables
to the subgradients of the McCormick convex underestimators at the
current value() of each variable.
def changePoint(self, var, point): updates the current value() on the
pyomo side and the current point on the MC++ side.
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__init__(expression, improved_var_bounds=None)[source]
Methods
__init__(expression[, improved_var_bounds])
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changePoint(var, point)
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concave()
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convex()
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lower()
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subcc()
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subcv()
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upper()
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warn_if_var_missing_value()
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Member Documentation