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2020 | OriginalPaper | Chapter

Adaptive Descent Splitting Method for Decomposable Optimization Problems

Authors : Igor Konnov, Olga Pinyagina

Published in: Mathematical Optimization Theory and Operations Research

Publisher: Springer International Publishing

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Abstract

We suggest a modified descent splitting method for optimization problems having a special decomposable structure. The proposed modification maintains the basic convergence properties but enables one to reduce computational efforts per iteration and to provide computations in a distributed manner. On the one hand, it consists in component-wise choice of descent directions together with a special threshold control. On the other hand, it involves a simple adaptive step-size choice, which takes into account the problem behavior along the iteration sequence. Preliminary computational tests confirm the efficiency of the proposed modification.

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previous chapter On Solving the Quadratic Sum-of-Ratios Problems
next chapter Convergence Analysis of Penalty Decomposition Algorithm for Cardinality Constrained Convex Optimization in Hilbert Spaces
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Metadata
Title
Adaptive Descent Splitting Method for Decomposable Optimization Problems
Authors
Igor Konnov
Olga Pinyagina
Copyright Year
2020
Book
Mathematical Optimization Theory and Operations Research

Print ISBN: 978-3-030-49987-7

Electronic ISBN: 978-3-030-49988-4

Copyright Year: 2020

DOI
https://doi.org/10.1007/978-3-030-49988-4_9

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