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An Implementable Proximal Extragradient Method for Structured Fractional Programming

  • Jiajun Hao
  • , Hongjin He*
  • , Liangshao Hou
  • *Corresponding author for this work

Research output: Contribution to journalJournal articlepeer-review

Abstract

A class of structured fractional programming is studied, where the numerator of the objective function consists of the sum of a nonsmooth function and a smooth function, while the denominator is a convex function. To solve this class of problems, the implementable proximal extragradient algorithm (IPEM) and its variant with linesearch (IPEM-L) are proposed. First, the fractional structure is handled using Dinkelbach’s method. Then, the extended extragradient method is applied to solve the resulting subproblems. By incorporating parameter updates, the proposed algorithms are formulated. A practical linesearch is further introduced to enhance efficiency of the IPEM. Under certain assumptions, both subsequential and whole sequence convergence are established, with the latter relying on the Kurdyka-Łojasiewicz (KŁ) property. Finally, numerical experiments on some synthetic and real datasets demonstrate the competitiveness of the proposed algorithms.

Original languageEnglish
Article number35
Number of pages33
JournalJournal of Optimization Theory and Applications
Volume207
Issue number2
Early online date31 Jul 2025
DOIs
Publication statusPublished - Nov 2025

User-Defined Keywords

  • Structured fractional programming
  • Extragradient method
  • Kurdyka-Ł ojasiewicz property
  • Proximal gradient method
  • Matrix completion

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