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- Title
The Descent–Ascent Algorithm for DC Programming.
- Authors
D'Alessandro, Pietro; Gaudioso, Manlio; Giallombardo, Giovanni; Miglionico, Giovanna
- Abstract
We introduce a bundle method for the unconstrained minimization of nonsmooth difference-of-convex (DC) functions, and it is based on the calculation of a special type of descent direction called descent–ascent direction. The algorithm only requires evaluations of the minuend component function at each iterate, and it can be considered as a parsimonious bundle method as accumulation of information takes place only in case the descent–ascent direction does not provide a sufficient decrease. No line search is performed, and proximity control is pursued independent of whether the decrease in the objective function is achieved. Termination of the algorithm at a point satisfying a weak criticality condition is proved, and numerical results on a set of benchmark DC problems are reported. History: Accepted by Antonio Frangioni, Area Editor for Design & Analysis of Algorithms – Continuous. Supplemental Material: The software that supports the findings of this study is available within the paper and its Supplemental Information (https://pubsonline.informs.org/doi/suppl/10.1287/ijoc.2023.0142) as well as from the IJOC GitHub software repository (https://github.com/INFORMSJoC/2023.0142). The complete IJOC Software and Data Repository is available at https://informsjoc.github.io/.
- Subjects
DATA libraries; ALGORITHMS; NONSMOOTH optimization; CONVEX functions
- Publication
INFORMS Journal on Computing, 2024, Vol 36, Issue 2, p657
- ISSN
1091-9856
- Publication type
Article
- DOI
10.1287/ijoc.2023.0142