Prox-regularization methods for generalized fractional programming

Prox-regularization methods for generalized fractional programming

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Article ID: iaor19993121
Country: United States
Volume: 99
Issue: 3
Start Page Number: 691
End Page Number: 722
Publication Date: Dec 1998
Journal: Journal of Optimization Theory and Methods
Authors:
Abstract:

If a fractional program does not have a unique solution or the feasible set is unbounded, numerical difficulties can occur. By using a prox-regularization method that generates a sequence of auxiliary problems with unique solutions, these difficulties are avoided. Two regularization methods are introduced here. They are based on Dinkelbach-type algorithms for generalized fractional programming, but use a regularized parametric auxiliary problem. Convergence results and numerical examples are presented.

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