Abstract
In this paper we present a simple dual condition for the convex subdifferential sum formula. We show that if are proper lower semi-continuous convex functions then for each whenever is weak closed, where denotes the epigraph of the conjugate function of This dual closure condition, which is shown to be weaker than the well known primal interior point like conditions, is completely characterized by the subdifferential sum formula in the case where and are sublinear. It also provides a simple global condition for the strong conical hull intersection property (CHIP), which is a key regularity condition in the study of constrained interpolation and approximation problems. The subdifferential sum formula is then used to derive necessary and sufficient optimality conditions for a general cone-constrained convex optimization problem under a much weaker dual constraint qualification, and to obtain a generalized Clarke-Ekeland dual least action principle.
References
- H. Attouch, H. Brézis: Duality for the sum of convex functions in general Banach spaces, in: Aspects of Mathematics and its Applications, J. A. Barroso (ed.), North Holland, Amsterdam (1986) 125–133.https://doi.org/10.1016/S0924-6509(09)70252-1Google Scholar
- H. Attouch, M. Théra: A general duality principle for the sum of two operators, J. Convex Analysis 3(1) (1996) 1–24.https://doi.org/10.68381/jca03001Google Scholar
- H. H. Bauschke, J. M. Borwein, W. Li: Strong conical hull intersection property, bounded linear regularity, Jameson’s property (G), and error bounds in convex optimization, Math. Progr. 86 (1999) 135–160.https://doi.org/10.1007/s101070050083Google Scholar
- H. H. Bauschke, J. M. Borwein, P. Tseng: Bounded linear regularity, strong CHIP, and CHIP are distinct properties, J. Convex Analysis 7(2) (2000) 395–412.https://doi.org/10.68381/jca07020Google Scholar
- R. S. Burachik, V. Jeyakumar: A simple closure condition for the normal cone intersection formula, Applied Mathematics Preprint, University of New South Wales, Sydney, Australia. To appear in Proc. Amer. Math. Soc..Google Scholar
- F. Clarke: Optimization and Nonsmooth Analysis, SIAM Classics in Applied Mathematics, Holland (1990).https://doi.org/10.1137/1.9781611971309Google Scholar
- F. Clarke, I. Ekeland: Hamiltonian trajectories having prescribed minimal period, Comm. Pure Appl. Math. 33(2) (1980) 103–116.https://doi.org/10.1002/cpa.3160330202Google Scholar
- F. Deutsch: The role of conical hull intersection property in convex optimization and approximation, in: Approximation Theory IX, C. K. Chui, L. L. Schumaker (eds.), Vanderbilt University Press, Nashville (1998).Google Scholar
- F. Deutsch, W. Li, J. Swetits: Fenchel duality and the strong conical hull intersection property, J. Optim. Theory Appl. 102 (1999) 681–695.https://doi.org/10.1023/A:1022658308898Google Scholar
- I. Ekeland, R. Temam: Convex Analysis and Variational Problems, North Holland, Amsterdam (1976).Google Scholar
- J.-B. Hiriart-Urruty, R. R. Phelps: Subdifferential calculus using ε-subdifferentials, J. Funct. Anal. 118 (1993) 154–166.https://doi.org/10.1006/jfan.1993.1141Google Scholar
- V. Jeyakumar: Duality and infinite dimensional optimization, Nonlinear Anal. 15 (1990) 1111–1122.https://doi.org/10.1016/0362-546X(90)90047-KGoogle Scholar
- V. Jeyakumar, G. M. Lee, N. Dinh: New sequential Lagrange multiplier conditions characterizing optimality without constraint qualifications for convex programs, SIAM J. Optim. 14(2) (2003) 534–547.https://doi.org/10.1137/S1052623402417699Google Scholar
- V. Jeyakumar, G. M. Lee, N. Dinh: A new closed cone constraint qualification for convex optimization, Applied Mathematics Research Report AMR04/6, University of New South Wales, submitted for publication.Google Scholar
- V. Jeyakumar, A. M. Rubinov, B. M. Glover, Y. Ishizuka: Inequality systems and global optimization, J. Math. Anal. Appl. 202 (1996) 900–919.https://doi.org/10.1006/jmaa.1996.0353Google Scholar
- V. Jeyakumar, H. Wolkowicz: Generalizations of Slater’s constraint qualification for infinite convex programs, Math. Progr. 57(1) (1992) 85–102.https://doi.org/10.1007/BF01581074Google Scholar
- C. Li, X. Jin: Nonlinearly constrained best approximation in Hilbert spaces: The strong CHIP, and the basic constraint qualification, SIAM J. Optim. 13(1) (2002) 228–239.https://doi.org/10.1137/S1052623401385600Google Scholar
- K. F. Ng, W. Song: Fenchel duality in infinite-dimensional setting and its applications, Nonlinear Anal. 25 (2003) 845–858.https://doi.org/10.1016/j.na.2003.07.008Google Scholar
- T. Strömberg: The operation of infimal convolution, Diss. Math. 352 (1996) 1–61.Google Scholar
- L. Thibault: Sequential convex subdifferential calculus and sequential Lagrange multipliers, SIAM J. Control Optim. 35(4) (1997) 1434–1444.https://doi.org/10.1137/S0363012995287714Google Scholar
- L. Thibault: A generalized sequential formula for subdifferentials of sums of convex functions defined on Banach spaces, in: Recent Developments in Optimization (Dijon, 1994), Lecture Notes in Econom. and Math. Systems 429, Springer, Berlin (1995) 340–345.https://doi.org/10.1007/978-3-642-46823-0_25Google Scholar
- J. van Tiel: Convex Analysis: An Introductory Text, John Wiley and Sons, Belfast (1984).Google Scholar
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Published by Heldermann Verlag, 2005. Rights now held by Banach Press LLC.
