Finite Convergence of the Partial Inverse Algorithm

In Refs. 1-2, Lefebvre and Michelot proved the finite convergence of the partial inverse algorithm applied to a polyhedral convex function by means of some suitable tools of convex analysis. They obtained their result under some assumptions on the primal and dual solution sets. The aim of this note...

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Bibliographic Details
Published in:Journal of optimization theory and applications Vol. 95; no. 3; pp. 693 - 699
Main Author: Daldoul, M.
Format: Journal Article
Language:English
Published: New York, NY Springer 01.12.1997
Springer Nature B.V
Subjects:
Applied sciences
Exact sciences and technology
Operational research and scientific management
Operational research. Management science
Optimization. Search problems
Subdifferential
Primal dual method
Convex function
Proximal point method
Algorithm
Optimization
Convergence
ISSN:0022-3239, 1573-2878
Online Access:Get full text
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Summary:In Refs. 1-2, Lefebvre and Michelot proved the finite convergence of the partial inverse algorithm applied to a polyhedral convex function by means of some suitable tools of convex analysis. They obtained their result under some assumptions on the primal and dual solution sets. The aim of this note is to show that the proof can be extended to remove the nasty assumption on the dual solution set. The result is in conformity with the proof given in Ref. 3, which has been obtained using the concept of folding.
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ISSN:0022-3239
1573-2878
DOI:10.1023/A:1022634208371