Functional Inequalities in the Absence of Convexity and Lower Semicontinuity with Applications to Optimization

In this paper we extend some results in [Dinh, Goberna, Lopez, and Volle, Set-Valued Var. Anal., to appear] to the setting of functional inequalities when the standard assumptions of convexity and lower semicontinuity of the involved mappings are absent. This extension is achieved under certain condition relative to the second conjugate of the involved functions. The main result of this paper, Theorem 1, is applied to derive some subdifferential calculus rules and different generalizations of the Farkas lemma for nonconvex systems, as well as some optimality conditions and duality theory for infinite nonconvex optimization problems. Several examples are given to illustrate the significance of the main results and also to point out the potential of their applications to get various extensions of Farkas-type results and to the study of other classes of problems such as variational inequalities and equilibrium models.

[1]  R. Horst,et al.  Global Optimization: Deterministic Approaches , 1992 .

[2]  P. Hansen,et al.  Essays and surveys in global optimization , 2005 .

[3]  Jean-Jacques Strodiot,et al.  Duality and optimality conditions for generalized equilibrium problems involving DC functions , 2010, J. Glob. Optim..

[4]  Vaithilingam Jeyakumar,et al.  New Sequential Lagrange Multiplier Conditions Characterizing Optimality without Constraint Qualification for Convex Programs , 2003, SIAM J. Optim..

[5]  V. Jeyakumar,et al.  Farkas Lemma: Generalizations , 2009, Encyclopedia of Optimization.

[6]  M. Volle,et al.  Convex Inequalities Without Constraint Qualification nor Closedness Condition, and Their Applications in Optimization , 2010 .

[7]  Kung Fu Ng,et al.  Constraint Qualifications for Extended Farkas's Lemmas and Lagrangian Dualities in Convex Infinite Programming , 2009, SIAM J. Optim..

[8]  I. Singer,et al.  A Fenchel-Rockafellar type duality theorem for maximization , 1979, Bulletin of the Australian Mathematical Society.

[9]  Elijah Polak,et al.  Semi-Infinite Optimization , 1997 .

[10]  M. Volle,et al.  On the subdifferential of the supremum of an arbitrary family of extended real-valued functions , 2011 .

[11]  C. Zălinescu Convex analysis in general vector spaces , 2002 .

[12]  T. T. A. Nghia,et al.  Farkas-type results and duality for DC programs with convex constraints , 2007 .

[13]  Vladimir Soloviov,et al.  Duality for nonconvex optimization and its applications , 1993 .

[14]  Jane J. Ye,et al.  Exact Penalization and Necessary Optimality Conditions for Generalized Bilevel Programming Problems , 1997, SIAM J. Optim..

[15]  Jean-Paul Penot,et al.  Subdifferential Calculus Without Qualification Assumptions , 1996 .

[16]  Stephen P. Boyd,et al.  Convex Optimization , 2004, Algorithms and Theory of Computation Handbook.

[17]  Miguel A. Goberna,et al.  From linear to convex systems: consistency, Farkas' Lemma and applications , 2006 .

[18]  Radu Ioan Bot,et al.  Some new Farkas-type results for inequality systems with DC functions , 2007, J. Glob. Optim..

[19]  Le Thi Hoai An,et al.  The DC (Difference of Convex Functions) Programming and DCA Revisited with DC Models of Real World Nonconvex Optimization Problems , 2005, Ann. Oper. Res..

[20]  Vaithilingam Jeyakumar,et al.  Characterizing global optimality for DC optimization problems under convex inequality constraints , 1996, J. Glob. Optim..

[21]  Zhi-You Wu,et al.  Liberating the Subgradient Optimality Conditions from Constraint Qualifications , 2006, J. Glob. Optim..

[22]  Lionel Thibault,et al.  Sequential Convex Subdifferential Calculus and Sequential Lagrange Multipliers , 1997 .

[23]  Vaithilingam Jeyakumar,et al.  Inequality systems and global optimization , 1996 .

[24]  J. Toland Duality in nonconvex optimization , 1978 .

[25]  Vaithilingam Jeyakumar,et al.  Sequential Lagrangian Conditions for Convex Programs with Applications to Semidefinite Programming , 2005 .

[26]  V. Jeyakumar,et al.  Characterizing Set Containments Involving Infinite Convex Constraints and Reverse-Convex Constraints , 2002, SIAM J. Optim..

[27]  M. A. López-Cerdá,et al.  Linear Semi-Infinite Optimization , 1998 .

[28]  Sorin-Mihai Grad,et al.  Generalized Moreau–Rockafellar results for composed convex functions , 2009 .

[29]  Constantin Zalinescu,et al.  Subdifferential Calculus Rules in Convex Analysis: A Unifying Approach Via Pointwise Supremum Functions , 2008, SIAM J. Optim..

[30]  A. Banerjee Convex Analysis and Optimization , 2006 .

[31]  Lionel Thibault,et al.  A Generalized Sequential Formula for Subdifferentials of Sums of Convex Functions Defined on Banach Spaces , 1995 .

[32]  J. Penot,et al.  Semi-continuous mappings in general topology , 1982 .

[33]  Radu Ioan Bot,et al.  SEQUENTIAL OPTIMALITY CONDITIONS IN CONVEX PROGRAMMING VIA PERTURBATION APPROACH , 2007 .

[34]  Jean-Paul Penot,et al.  Unilateral Analysis and Duality , 2005 .

[35]  V. H. Nguyen,et al.  On Nash–Cournot oligopolistic market equilibrium models with concave cost functions , 2008, J. Glob. Optim..

[36]  Alberto Seeger,et al.  Subdifferential calculus without qualification conditions, using approximate subdifferentials: a survey , 1995 .

[37]  R. Phelps,et al.  Subdifferential Calculus Using ϵ-Subdifferentials , 1993 .