We use the penalty approach in order to study a large class of inequality-constrained minimization problems in Banach spaces. A penalty function is said to have the generalized exact penalty property if there is a penalty coefficient for which approximate solutions of the unconstrained penalized problem are close enough to approximate solutions of the corresponding constrained problem. In this paper we show that the generalized exact penalty property is stable under perturbations of cost functions, constraint functions and the right-hand side of constraints.

Contact details are reproduced from the original publication and may be historical.

Alexander J. Zaslavski

Department of Mathematics, Technion - Israel Institute of Technology, 32000 Haifa, Israel

ajzasl@tx.technion.ac.il
  1. A. Auslender: Penalty and barrier methods: a unified framework, SIAM J. Optim. 10 (1999) 211–230.https://doi.org/10.1137/S1052623497324825Google Scholar
  2. A. Auslender: Asymptotic analysis for penalty and barrier methods in variational inequalities, SIAM J. Control Optimization 37 (1999) 653–671.https://doi.org/10.1137/S0363012996310909Google Scholar
  3. D. Boukari, A. V. Fiacco: Survey of penalty, exact-penalty and multiplier methods from 1968 to 1993, Optimization 32 (1995) 301–334.https://doi.org/10.1080/02331939508844053Google Scholar
  4. J. V. Burke: An exact penalization viewpoint of constrained optimization, SIAM J. Control Optimization 29 (1991) 968–998.https://doi.org/10.1137/0329054Google Scholar
  5. F. H. Clarke: Optimization and Nonsmooth Analysis, Wiley, New York (1983).Google Scholar
  6. V. F. Demyanov, L. V. Vasiliev: Nondifferentiable Optimization, Optimization Software, New York (1985).https://doi.org/10.1007/978-3-662-12603-5Google Scholar
  7. G. Di Pillo, L. Grippo: Exact penalty functions in constrained optimization, SIAM J. Control Optimization 27 (1989) 1333–1360.https://doi.org/10.1137/0327068Google Scholar
  8. I. Ekeland: On the variational principle, J. Math. Anal. Appl. 47 (1974) 324–353.https://doi.org/10.1016/0022-247X(74)90025-0Google Scholar
  9. I. I. Eremin: The penalty method in convex programming, Sov. Math., Dokl. 8 (1966) 459–462.Google Scholar
  10. I. I. Eremin: The penalty method in convex programming, Cybernetics 3 (1971) 53–56.https://doi.org/10.1007/BF01071708Google Scholar
  11. J.-B. Hiriart-Urruty, C. Lemarechal: Convex Analysis and Minimization Algorithms, Springer, Berlin (1993).https://doi.org/10.1007/978-3-662-02796-7Google Scholar
  12. B. S. Mordukhovich: Variational Analysis and Generalized Differentiation, I: Basic Theory, II: Applications, Springer, Berlin (2006).https://doi.org/10.1007/3-540-31246-3Google Scholar
  13. W. I. Zangwill: Nonlinear programming via penalty functions, Management Sci. 13 (1967) 344–358.https://doi.org/10.1287/mnsc.13.5.344Google Scholar
  14. A. J. Zaslavski: A sufficient condition for exact penalty in constrained optimization, SIAM Journal Optim. 16 (2005) 250–262.https://doi.org/10.1137/040612294Google Scholar
  15. A. J. Zaslavski: Existence of approximate exact penalty in constrained optimization, Math. Oper. Res. 32 (2007) 484–495.https://doi.org/10.1287/moor.1060.0246Google Scholar

A. J. Zaslavski. “Existence of Exact Penalty and its Stability for Inequality-Constrained Optimization Problems.” Journal of Convex Analysis 16 (2009), No. 1, 261–276. https://doi.org/10.68381/jca16014