Outer approximation for convex MINLPs can cycle due to CQ failures or approximate solves, but extended cutting planes ensure finite convergence under weaker constraint qualification assumptions.
A Robbins-Monro type algorithm for computing global min- imizer of generalized conic functions
3 Pith papers cite this work. Polarity classification is still indexing.
3
Pith papers citing it
fields
math.OC 3verdicts
UNVERDICTED 3representative citing papers
Proposes two spectral conjugate gradient projection methods for monotone nonlinear equations, proving global convergence under monotonicity alone for the first variant without Lipschitz continuity.
Survey of taxicab distance mean functions with applications to geometric tomography and Maple implementations.
citing papers explorer
-
Separation, Constraint Qualifications, and Cycling in Outer Approximation
Outer approximation for convex MINLPs can cycle due to CQ failures or approximate solves, but extended cutting planes ensure finite convergence under weaker constraint qualification assumptions.
-
Spectral conjugate gradient projection methods for large-scale monotone equations without Lipschitz continuity
Proposes two spectral conjugate gradient projection methods for monotone nonlinear equations, proving global convergence under monotonicity alone for the first variant without Lipschitz continuity.