Journal of Optimization Theory and Applications

, Volume 12, Issue 6, pp 567–575 | Cite as

On the convergence of sequential minimization algorithms

  • R. W. H. Sargent
  • D. J. Sebastian
Article
First Online:

Abstract

This note discusses the conditions for convergence of algorithms for finding the minimum of a function of several variables which are based on solving a sequence of one-variable minimization problems. Theorems are given which contrast the weakest conditions for convergence of gradient-related algorithms with those for more general algorithms, including those which minimize in turn along a sequence of uniformly linearly independent search directions.

Keywords

Search Direction Convergent Subsequence Infinite Sequence North Holland Publishing Company Quasiconvex Function 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Copyright information

© Plenum Publishing Corporation 1973

Authors and Affiliations

  • R. W. H. Sargent
    • 1
  • D. J. Sebastian
    • 1
  1. 1.Department of Chemical Engineering and Chemical TechologyImperial CollegeLondonEngland

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