Abstract
We address the problem of solving a continuously differentiable nonlinear system of equations under the condition of calmness. This property, also called upper Lipschitz-continuity in the literature, can be described by a local error bound and is being widely used as a regularity condition in optimization. Indeed, it is known to be significantly weaker than classic regularity assumptions that imply that solutions are isolated. We prove that under this condition, the rank of the Jacobian of the function that defines the system of equations must be locally constant on the solution set. In addition, we prove that locally, the solution set must be a differentiable manifold. Our results are illustrated by examples and discussed in terms of their theoretical relevance and algorithmic implications.
Similar content being viewed by others
References
Dan H., Yamashita N., Fukushima M.: Convergence properties of the inexact Levenberg–Marquardt method under local error bound conditions. Optim. Methods Softw. 17, 605–626 (2002)
Demmel J.W.: Applied Numerical Linear Algebra. SIAM, Philadelphia (1997)
Fan J., Pan J.: Inexact Levenberg–Marquardt method for nonlinear equations. Discret. Contin. Dyn. Syst. Ser. B 4, 1223–1232 (2004)
Fan J., Yuan Y.: On the quadratic convergence of the Levenberg–Marquardt method without nonsingularity assumption. Computing 74, 23–39 (2005)
Fischer A.: Local behavior of an iterative framework for generalized equations with nonisolated solutions. Math. Program. 94, 91–124 (2002)
Fischer A., Shukla P.K.: A Levenberg–Marquardt algorithm for unconstrained multicriteria optimization. Oper. Res. Lett. 36, 643–646 (2008)
Fischer A., Shukla P.K., Wang M.: On the inexactness level of robust Levenberg–Marquardt methods. Optimization 59, 273–287 (2010)
Hoffman A.J.: On approximate solutions of systems of linear inequalities. J. Res. Natl. Bureau Stand. 49, 263–265 (1952)
Izmailov A.F., Solodov M.V.: Karush–Kuhn–Tucker systems: regularity conditions, error bounds and a class of Newton-type methods. Math. Program. 95, 631–650 (2003)
Kanzow C., Yamashita N., Fukushima M.: Levenberg–Marquardt methods with strong local convergence properties for solving nonlinear equations with convex constraints. J. Comput. Appl. Math. 172, 375–397 (2004)
Levenberg K.: A method for the solution of certain non-linear problems in least squares. Q. Appl. Math. 2, 164–168 (1944)
Marquardt D.W.: An algorithm for least-squares estimation of nonlinear parameters. J. Soc. Ind. Appl. Math. 11, 431–441 (1963)
Robinson S.M.: Generalized equations and their solutions, part II: applications to nonlinear programming. Math. Program. 19, 200–221 (1982)
Rockafellar R.T., Wets R.J.-B.: Variational Analysis. Springer, Berlin (1998)
Spivak M.: A Comprehensive Introduction to Differential Geometry, vol. 1. Publish or Perish, Berkeley (1979)
Yamashita N., Fukushima M.: On the rate of convergence of the Levenberg–Marquardt method. Computing 15(Suppl.), 239–249 (2001)
Zhang J.-L.: On the convergence properties of the Levenberg–Marquardt method. Optimization 52, 739–756 (2003)
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Behling, R., Iusem, A. The effect of calmness on the solution set of systems of nonlinear equations. Math. Program. 137, 155–165 (2013). https://doi.org/10.1007/s10107-011-0486-7
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10107-011-0486-7