Parameter-free proximal bundle methods with adaptive stepsizes for hybrid convex composite optimization problems

Renato D. C. Monteiro; Honghao Zhang

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arXiv · 2410.20751

Parameter-free proximal bundle methods with adaptive stepsizes for hybrid convex composite optimization problems

Renato D. C. Monteiro·Honghao Zhang

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Abstract

This paper develops a parameter-free adaptive proximal bundle method with two important features: 1) adaptive choice of variable prox stepsizes that "closely fits" the instance under consideration; and 2) adaptive criterion for making the occurrence of serious steps easier. Computational experiments show that our method performs substantially fewer consecutive null steps (i.e., a shorter cycle) while maintaining the number of serious steps under control. As a result, our method performs significantly less number of iterations than its counterparts based on a constant prox stepsize choice and a non-adaptive cycle termination criterion. Moreover, our method is very robust relative to the user-provided initial stepsize.

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BibTeX RIS

Renato D. C. Monteiro, Honghao Zhang. 2024-10-28. Parameter-free proximal bundle methods with adaptive stepsizes for hybrid convex composite optimization problems. https://arxiv.org/abs/2410.20751

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