Nonmonotone Proximal Gradient Method for Composite Multiobjective Optimization Problems
Abstract In this paper, we introduce proximal gradient methods with non-monotone Armijo line search rule of both kinds, max-type and average-type, to solve composite multiobjective optimization problems (CMOP). Moreover, the convergence analysis is given, and we show that all accumulation points of a sequence generated by both of the two kinds of nonmonotone proximal gradient methods are Pareto stationary points of (CMOP). Finally, we present numerical experiments illustrating the practical performance of these methods
Authors
- Elisabeth Köbis (ORCID: https://orcid.org/0000-0003-3842-4522)
- Jianwen Peng (ORCID: https://orcid.org/0009-0004-2391-3731)
- Hua Long Sun
Institutions
- Chongqing Normal University (CN)
- Norwegian University of Science and Technology (NO)
Publication Details
- Journal
- Journal of Optimization Theory and Applications
- Published
- 2025-04-16
- DOI
- https://doi.org/10.1007/s10957-025-02667-8
- Primary Topic
- Advanced Multi-Objective Optimization Algorithms
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Norges Teknisk-Naturvitenskapelige Universitet
- National Natural Science Foundation of China
- St. Olavs Hospital Universitetssykehuset i Trondheim