Liberating the Subgradient Optimality Conditions from Constraint Qualifications
作者： V. Jeyakumar , Z. Y. Wu , G. M. Lee , N. Dinh
DOI: 10.1007/S10898-006-9003-6
关键词: Subgradient method 、 Conic section 、 Optimization problem 、 Mathematics 、 Mathematical optimization 、 Convex optimization 、 Duality (mathematics)
摘要: In convex optimization the significance of constraint qualifications is evidenced by simple duality theory, and elegant subgradient optimality conditions which completely characterize a minimizer. However, do not always hold even for finite dimensional problems frequently fail infinite problems. present work we take broader view allowing them to depend on sequence ?-subgradients at minimizer then letting in limit. Liberating this way permits us obtain complete characterization without qualification. As an easy consequence these results conic We derive applying powerful combination conjugate analysis ?-subdifferential calculus. Numerical examples are discussed illustrate sequential conditions.
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