Abstract
We employ recent results about constraint nondegeneracy in variational conditions to design and justify a linearization algorithm for solving such problems. The algorithm solves a sequence of affine variational inequalities, but the variational condition itself need not be a variational inequality: that is, its underlying set need not be convex. However, that set must be given by systems of differentiable nonlinear equations with additional polyhedral constraints. We show that if the variational condition has a solution satisfying nondegeneracy and a standard regularity condition, and if the linearization algorithm is started sufficiently close to that solution, the algorithm will produce a well defined sequence that converges Q-superlinearly to the solution.
Similar content being viewed by others
References
Bonnans, J. F. and Shapiro, A. (2000), Perturbation Analysis of Optimization Problems, Springer Series in Operations Research, Springer, New York.
Facchinei, F. and Pang, J.-S. (2003), Finite-Dimensional Variational Inequalities and Complementarity Problems, Springer Series in Operations Research, Springer, New York, Published in two volumes, paginated continuously.
Ortega, J. M. and Rheinboldt, W. C. (1970), Iterative Solution of Nonlinear Equations in Several Variables, Academic Press, New York.
Pshenichnyj, B. N. (1994), The Linearization Method for Constrained Optimization, Springer Series in Computational Mathematics, Springer, Berlin. Translated by Stephen S. Wilson from the Russian original, Metod linearizatsii, Nauka, Moscow, 1983.
Robinson, S. M. (1972), A quadratically-convergent algorithm for general nonlinear programming problems, Mathematical Programming 3, 145–156.
Robinson, S. M. (1974), Perturbed Kuhn-Tucker points and rates of convergence for a class of nonlinear-programming algorithms, Mathematical Programming, 7, 1–16.
Robinson, S. M. (1984), Local structure of feasible sets in nonlinear programming, Part II: Nondegeneracy, Mathematical Programming Studies 22, 217–230.
Robinson, S. M. (2003), Constraint nondegeneracy in variational analysis, Mathematics of Operations Research 28, 201–232.
Rockafellar, R. T. (1970), Convex Analysis, Princeton University Press, Princeton, NJ.
Rockafellar, R. T. and Wets, R. J. (1998), Variational Analysis, Number 317 in Grundlehren der mathematischen Wissenschaften. Springer, Berlin.
Shapiro, A., Sensitivity analysis of generalized equations, Journal of Mathematical Sciences, Forthcoming.
Wilson, R. B. (1963), A Simplicial Method for Concave Programming, Doctoral dissertation, Graduate School of Business Administration, Harvard University, Boston, MA.
Author information
Authors and Affiliations
Rights and permissions
About this article
Cite this article
Robinson, S.M. A Linearization Method for Nondegenerate Variational Conditions. Journal of Global Optimization 28, 405–417 (2004). https://doi.org/10.1023/B:JOGO.0000026458.55147.46
Issue Date:
DOI: https://doi.org/10.1023/B:JOGO.0000026458.55147.46