Self-Scaling Variable Metric (SSVM) Algorithms

Shmuel S. Oren
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Shmuel S. Oren: Xerox Corporation, Palo Alto, California and Stanford University

Management Science, 1974, vol. 20, issue 5, 863-874

Abstract: This part of the paper introduces some possible implementations of Self-Scaling Variable Metric algorithms based on the theory presented in Part I. These implementations are analyzed theoretically and discussed qualitatively. A special class of SSVM algorithms is introduced, which has the additional property of being invariant under scaling of the objective function or of the variables. Experimental results are provided for a particular case of this class. This case has been tested in comparison to the DFP algorithm on a variety of functions with up to 50 variables. The results indicate that the new method has substantial advantage for functions with a large number of variables.

Date: 1974
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Persistent link: https://EconPapers.repec.org/RePEc:inm:ormnsc:v:20:y:1974:i:5:p:863-874

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