Hostname: page-component-78c5997874-lj6df Total loading time: 0 Render date: 2024-11-14T16:48:07.905Z Has data issue: false hasContentIssue false

Minimal approximate Hessians for continuously Gâteaux differentiable functions

Published online by Cambridge University Press:  17 February 2009

Hongxu Li
Affiliation:
Department of Mathematics, Sichuan University, Chengdu, Sichuan 610064, P. R. China; e-mail: Hoxuli@sohu.com.
Falun Huang
Affiliation:
Department of Mathematics, Sichuan University, Chengdu, Sichuan 610064, P. R. China; e-mail: Hoxuli@sohu.com.
Rights & Permissions [Opens in a new window]

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.

In this paper, we investigate minimal (weak) approximate Hessians, and completely answer the open questions raised by V. Jeyakumar and X. Q. Yang. As applications, we first give a generalised Taylor's expansion in terms of a minimal weak approximate Hessian. Then we characterise the convexity of a continuously Gâteaux differentiable function. Finally some necessary and sufficient optimality conditions are presented.

Type
Research Article
Copyright
Copyright © Australian Mathematical Society 2004

References

[1]Ben-Tal, A. and Zowe, J., “A unified theory of first and second order conditions for extremum problems in topological vector spaces”, Math. Programming Study 19 (1982) 3976.CrossRefGoogle Scholar
[2]Burke, J. V., “Second-order necessary and sufficient conditions for convex composite NDO”, Math. Programming 38 (1987) 287302.CrossRefGoogle Scholar
[3]Burke, J. V. and Poliquin, R. A., “Optimality conditions for nonfinite-valued convex composite functions”, Math. Programming Ser. B 57 (1992) 103120.CrossRefGoogle Scholar
[4]Chan, W. L., Huang, L. R. and Ng, K. F., “On generalized second-order derivatives and Taylor expansions in nonsmooth optimization”, SIAM J. Control Optim. 32 (1994) 591611.CrossRefGoogle Scholar
[5]Chaney, R. W., “Second-order directional derivatives for nonsmooth functions”, J. Math. Anal. Appl. 128 (1987) 495511.CrossRefGoogle Scholar
[6]Clarke, F. H., Optimization and nonsmooth analysis (Wiley-Interscience, New York, 1983).Google Scholar
[7]Cominetti, R. and Correa, R., “A generalized second-order derivative in nonsmooth optimization”, SIAM J. Control and Optim. 28 (1990) 789809.CrossRefGoogle Scholar
[8]Correa, R., Jofre, A. and Thibault, L., “Characterization of lower semi-continuous convex functions”, Proc. Amer. Math. Soc. 116 (1992) 6772.CrossRefGoogle Scholar
[9]Fiacco, A. V., “Second-order sufficient conditions for weak and strict constrained minima”, SIAM J. Appl. Math. 16 (1968) 105108.CrossRefGoogle Scholar
[10]Fletcher, R., Practical methods of optimization 16 (John Wiley, New York, 1987).Google Scholar
[11]Hiriart-Urruty, J. B., Strodiot, J. J. and Hein Nguyen, V., “Generalized Hessian matrix and second-order optimality conditions for problems with C 1.1 data”, Appl. Math. Optim. 11 (1984) 4356.CrossRefGoogle Scholar
[12]Ioffe, A. D., “Necessary and sufficient conditions for a local minimum. Part 3: Second-order conditions and augmented duality”, SIAM J. Control Optim. 17 (1979) 266288.CrossRefGoogle Scholar
[13]Jeyakumar, V. and Yang, X. Q., “Convex composite minimization with C 1.1 functions”, J. Optim. Theory Appl. 86 (1995) 631648.CrossRefGoogle Scholar
[14]Jeyakumar, V. and Yang, X. Q., “Approximate generalized Hessians and Taylor's expansions for continuously Gâteaux differentiable functions”, Non. Anal. T. M. A. 36 (1999) 353368.CrossRefGoogle Scholar
[15]Kawasaki, H., “An envelope-like effect of infinitely many inequality constrains on second-order necessary conditions for minimization problems”, Math. Programming 41 (1988) 7396.CrossRefGoogle Scholar
[16]Michel, P. and Penot, J.-P., “A generalized derivative for calm and stable functions”, Differential Integral Equations 5 (1992) 433454.CrossRefGoogle Scholar
[17]Pales, Z. and Zeidan, V., “Generalized Hessian for C 1.1 functions in infinite dimensional normed spaces”, Math. Programming 74 (1996) 5978.CrossRefGoogle Scholar
[18]Qi, L., “Superlinearly convergent approximate Newton methods for LC 1 optimization problems”, Math. Programming 64 (1994) 277294.CrossRefGoogle Scholar
[19]Rockafellar, R. T., “First-and second-order epidifferentiability in nonlinear programming”, Trans. Amer Math. Soc. 307 (1988) 75108.CrossRefGoogle Scholar
[20]Rockafellar, R. T., “Second-order optimality conditions in nonlinear programming obtained by way of eipi-derivatives”, Math. Oper. Res. 14 (1989) 462484.CrossRefGoogle Scholar
[21]Yang, X. Q., “Generalized second-order characterizations of convex functions”, J. Optim. Theory Appl. 82 (1994) 173180.CrossRefGoogle Scholar
[22]Yang, X. Q., “Second-order conditions in C 1.1 optimization with applications”, Numer. Fund. Anal. Optim. 14 (1993) 621632.CrossRefGoogle Scholar
[23]Yang, X. Q. and Jeyakumar, V., “Generalized second-order directional derivatives and optimization with C 1.1functions”, Optimization 26 (1992) 165185.CrossRefGoogle Scholar