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Pathfollowing methods in nonlinear optimization III: Lagrange multiplier embedding

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Abstract

This paper deals with Lagrange multiplier methods which are interpreted as pathfollowing methods. We investigate how successful these methods can be for solving “really nonconvex” problems. Singularity theory developed by Jongen-Jonker-Twilt will be used as a successful tool for providing an answer to this question. Certain modifications of the original Lagrange multiplier method extend the possibilities for solving nonlinear optimization problems, but in the worst case we have to find all connected components in the set of all generalized critical points. That is still an open problem.

This paper is a continuation of our research with respect to penalty methods (part I) and exact penalty methods (part II).

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References

  1. Bertsekas DP (1976) On penalty and multiplier methods for constrained minimization. SIAM J. Control and Optimization 14 2:216–235

    Google Scholar 

  2. Bertsekas DP (1982) Constrained optimization and Lagrange multiplier methods. Academic Press New York

    Google Scholar 

  3. Bertsekas DP (1982) Enlarging the region of convergence of Newton's method for constrained optimization. JOTA 36 2:221–251

    Google Scholar 

  4. Florenzano M et al (eds) (1993) Approximation and optimization II (Proceedings of the 2nd International Conference ‘Approximation and optimization in the Carribean’, Havana, Cuba. In: Brosowski B, Deutsch F, Guddat J (eds) ser approximation and optimization, Peter Lang Verlag Frankfurt aM Bern New York in preparation

    Google Scholar 

  5. Gfrerer H, Guddat J, Wacker Hj, Zulehner W (1985) Pathfollowing methods for Kuhn-Tucker curves by an active index set strategy. In: Bagchi A, Jongen HTh (eds) Systems and optimization, Lecture Notes in Control and Information Sciences 66, Springer-Verlag Berlin Heidelberg New York 111–131

    Google Scholar 

  6. Gollmer R, Guddat J, Guerra F, Nowack D, Rückmann J-J (1993) Pathfollowing methods in nonlinear optimization I: Penalty embedding. In: Guddat J et al (eds) Parametric optimization and related topics III, Peter Lang Verlag Frankfurt aM Bern New York 163–214

    Google Scholar 

  7. Dentcheva D, Gollmer R, Guddat J, Rückmann J-J (1993) Pathfollowing methods in nonlinear optimization II: Exact penalty embedding. In: Brosowski B, Deutsch F, Guddat J (eds) ser approximation and optimization, Peter Lang Verlag Frankfurt aM Bern New York in preparation

    Google Scholar 

  8. Guddat J, Guerra F, Jongen HTh (1990) Parametric optimization: Singularities, pathfollowing and jumps. BG Teubner, Stuttgart and John Wiley, Chichester

    Google Scholar 

  9. Guddat J, Jongen HTh, Rückmann J-J (1986) On stability and stationary points in nonlinear optimization. J. Austral Math Soc, Ser B 28:36–56

    Google Scholar 

  10. Guddat J, Rückmann J-J (1994) One-parametric optimization: Jumps in the set of generalized critical points. Control and Cybernetics 22:1/2

    Google Scholar 

  11. Günther P, Beyer K, Gottwald S, Wünsch V (1973) Grundkurs Analysis Teil 3 Teubner Verlagsgesellschaft Leipzig

    Google Scholar 

  12. Jongen HTh, Jonker P, Twilt F (1986) On one-parametric families of optimization problems: Equality constraints. JOTA 48:141–161

    Google Scholar 

  13. Jongen HTh, Jonker P, Twilt F (1986) Critical sets in parametric optimization. Math Programming 34:333–353

    Google Scholar 

  14. Kojima M, Hirabayashi R (1984) Continuous deformation of nonlinear programs. Math Progr Study 21:150–198

    Google Scholar 

  15. Di Pillo G, Grippo L (1986) An exact penalty function method with global convergence properties for nonlinear programming. Math Programming 36:1–18

    Google Scholar 

  16. Rückmann J-J, Tammer K (1992) On linear-quadratic perturbations in one-parametric nonlinear optimization. Systems Science 18 1:37–48

    Google Scholar 

  17. Wendler K (1993) Implementation of a pathfollowing procedure for solving nonlinear one-parametric optimization problems. In: Brosowski B et al (eds) Multicriteria decision Peter Lang Verlag Frankfurt aM Bern New York 139–163

    Google Scholar 

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This work was supported by the Deutsche Forschungsgemeinschaft under grant Gu 304/1-2.

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Dentcheva, D., Guddat, J., Rückmann, J.J. et al. Pathfollowing methods in nonlinear optimization III: Lagrange multiplier embedding. ZOR - Mathematical Methods of Operations Research 41, 127–152 (1995). https://doi.org/10.1007/BF01432651

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