GLOBALLY CONVERGENT NEWTON METHODS FOR CONSTRAINED OPTIMIZATION USING DIFFERENTIABLE EXACT PENALTY FUNCTIONS.

Research output: Contribution to journalConference articlepeer-review

1 Scopus citations

Abstract

Consideration is given to Newton's method for solving the system of necessary optimality conditions of optimization problems with equality and inequality constraints. The principal drawbacks of the method are the need for a good starting point, the inability to distinguish between local maxima and local minima, and when inequality constraints are present, the necessity to solve a quadratic programming problem at each interaction. It is shown that all these drawbacks can be overcome to a great extent without sacrificing the superlinear convergence rate by making use of exact differentiable penalty functions introduced by G. Di Pillo and L. Grippo.

Original languageEnglish (US)
Pages (from-to)234-238
Number of pages5
JournalProceedings of the IEEE Conference on Decision and Control
Volume1
StatePublished - 1980
Externally publishedYes
EventUnknown conference - Albuquerque, NM
Duration: Dec 10 1980Dec 12 1980

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Modeling and Simulation
  • Control and Optimization

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