Work

Delayed Star Subgradient Methods for Constrained Nondifferentiable Quasi-Convex Optimization

Year: 2025

Type: article

Abstract: In this work, we consider the problem of minimizing a quasi-convex function over a nonempty closed convex constrained set. In order to approximate a solution of the considered problem, we propose delayed star subgradient methods. The main feature of the proposed methods is that it allows us to use the stale star subgradients when updating the next iteration rather than computing the new star subgradient in every iteration. We subsequently investigate the convergence results of sequences generated by the proposed methods. Finally, we present some numerical experiments on the Cobb–Douglas production efficiency problem to illustrate the effectiveness of the proposed method.

Source: Algorithms

DOI: 10.3390/a18080469

Authors: Ontima Pankoon, Nimit Nimana

Institution: Khon Kaen University

Language: English

Topic: Optimization and Variational Analysis

Subfield: Computational Theory and Mathematics

Field: Computer Science

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $1,930

Funder: Khon Kaen University