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Pseudonormality and a Lagrange Multiplier Theory for Constrained Optimization

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Abstract

We consider optimization problems with equality, inequality, and abstract set constraints, and we explore various characteristics of the constraint set that imply the existence of Lagrange multipliers. We prove a generalized version of the Fritz–John theorem, and we introduce new and general conditions that extend and unify the major constraint qualifications. Among these conditions, two new properties, pseudonormality and quasinormality, emerge as central within the taxonomy of interesting constraint characteristics. In the case where there is no abstract set constraint, these properties provide the connecting link between the classical constraint qualifications and two distinct pathways to the existence of Lagrange multipliers: one involving the notion of quasiregularity and the Farkas lemma, and the other involving the use of exact penalty functions. The second pathway also applies in the general case where there is an abstract set constraint.

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References

  1. BAZARAA, M. S., SHERALI, H. D., and SHETTY, C. M., Nonlinear Programming Theory and Algorithms, 2nd Edition, Wiley, New York, NY, 1993.

    Google Scholar 

  2. ROCKAFELLAR, R. T., and WETS, R. J. B., Variational Analysis, Springer Verlag, Berlin, Germany, 1998.

    Google Scholar 

  3. MORDUKHOVICH, B. S., Maximum Principle in the Problem of Time-Optimal Response with Nonsmooth Constraints, Journal of Applied Mathematics and Mechanics, Vol. 40, pp. 960-969, 1976.

    Google Scholar 

  4. AUBIN, J. P., and FRANKOWSKA, H., Set-Valued Analysis, Birkhauser, Boston, Massachusetts, 1990.

    Google Scholar 

  5. BORWEIN, J. M., and LEWIS, A. S., Convex Analysis and Nonlinear Optimization, Springer Verlag, New York, NY, 2000.

    Google Scholar 

  6. BERTSEKAS, D. P., Nonlinear Programming, 2nd Edition, Athena Scientific, Belmont, Massachusetts, 1999.

    Google Scholar 

  7. HESTENES, M. R., Optimization Theory: The Finite-Dimensional Case, Wiley, New York, NY, 1975.

    Google Scholar 

  8. ROCKAFELLAR, R. T., Lagrange Multipliers and Optimality, SIAM Review, Vol. 35, pp. 183-238, 1993.

    Google Scholar 

  9. ABADIE, J., On the Kuhn-Tucker Theorem, Nonlinear Programming, Edited by J. Abadie, North Holland, Amsterdam, Holland, 1967.

    Google Scholar 

  10. ARROW, K. J., HURWICZ, L., and UZAWA, H., Constraint Qualifications in Maximization Problems, Naval Research Logistics Quarterly, Vol. 8, pp. 175-191, 1961.

    Google Scholar 

  11. MANGASARIAN, O. L., and Fromovitz, S., The Fritz John Necessary Optimality Conditions in the Presence of Equality and Inequality Constraints, Journal of Mathematical Analysis and Applications, Vol. 17, pp. 37-47, 1967.

    Google Scholar 

  12. PETERSON, D. W., A Review of Constraint Qualifications in Finite-Dimensional Spaces, SIAM Review, Vol. 15, pp. 639-654, 1973.

    Google Scholar 

  13. BONNANS, J. F., and SHAPIRO, A., Perturbation Analysis of Optimization Problems, Springer Verlag, New York, NY, 2000.

    Google Scholar 

  14. PIETRZYKOWSKI, T., An Exact Potential Method for Constrained Maxima, SIAM Journal on Numerical Analysis, Vol. 6, pp. 294-304, 1969.

    Google Scholar 

  15. ZANGWILL, W. I., Nonlinear Programming via Penalty Functions, Management Science, Vol. 13, pp. 344-358, 1967.

    Google Scholar 

  16. HAN, S. P., and MANGASARIAN, O. L., Exact Penalty Functions in Nonlinear Programming, Mathematical Programming, Vol. 17, pp. 251-269, 1979.

    Google Scholar 

  17. BAZARAA, M. S., and GOODE, J. J., Sufficient Conditions for a Globally Exact Penalty Function without Convexity, Mathematical Programming Studies, Vol. 19, pp. 1-15, 1982.

    Google Scholar 

  18. GUIGNARD, M., Generalized Kuhn-Tucker Conditions for Mathematical Programming Problems in a Banach Space, SIAM Journal on Control, Vol. 7, pp. 232-241, 1969.

    Google Scholar 

  19. GOULD, F. J., and TOLLE, J., A Necessary and Sufficient Condition for Constrained Optimization, SIAM Journal on Applied Mathematics, Vol. 20, pp. 164-172, 1971.

    Google Scholar 

  20. GOULD, F. J., and TOLLE, J., Geometry of Optimality Conditions and Constraint Qualifications, Mathematical Programming, Vol. 2, pp. 1-18. 1972.

    Google Scholar 

  21. CLARKE, F. H., A New Approach to Lagrange Multipliers, Mathematics of Operations Research, Vol. 1, pp. 165-174, 1976.

    Google Scholar 

  22. CLARKE, F. H., Optimization and Nonsmooth Analysis, Wiley, New York, NY, 1983.

    Google Scholar 

  23. JOHN, F., Extremum Problems with Inequalities as Subsidiary Conditions, Studies and Essays: Courant Anniversary Volume, Edited by K. O. Friedrichs, O. E. Neugebauer, and J. J. Stoker, Wiley-Interscience, New York, NY, pp. 187-204, 1948.

    Google Scholar 

  24. MCSHANE, E. J., The Lagrange Multiplier Rule, American Mathematical Monthly, Vol. 80, pp. 922-925, 1973.

    Google Scholar 

  25. BERTSEKAS, D. P., NEDIć, A., and OZDAGLAR, A. E., Convex Analysis and Optimization, Athena Scientific, Belmont, Massachusetts, 2002.

    Google Scholar 

  26. HIRIART-URRUTY, J. B., and LEMARECHAL, C., Convex Analysis and Minimization Algorithms, Vol. 1, Springer Verlag, Berlin, Germany, 1993.

    Google Scholar 

  27. SLATER, M., Lagrange Multipliers Revisited: A Contribution to Nonlinear Programming, Cowles Commission Discussion Paper, Mathematics, Vol. 403, 1950.

  28. ROCKAFELLAR, R. T., Convex Analysis, Princeton University Press, Princeton, New Jersey, 1970.

    Google Scholar 

  29. GAUVIN, J., A Necessary and Sufficient Condition to Have Bounded Multipliers in Convex Programming, Mathematical Programming, Vol. 12, pp. 136-138, 1977.

    Google Scholar 

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Bertsekas, D., Ozdaglar, A. Pseudonormality and a Lagrange Multiplier Theory for Constrained Optimization. Journal of Optimization Theory and Applications 114, 287–343 (2002). https://doi.org/10.1023/A:1016083601322

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