Proximal point type algorithms for solving multiobjective optimization problems beyond convexity
Abstract
We implement proximal point type algorithms for finding an efficient point for nonconvex multiobjective optimization problems in which the objective functions are quasiconvex and satisfy a prox-convexity assumption. Our proposed algorithms combine the proximal point method for the minimization problem with the infeasible projection method for variational inequalities and their generate iterative sequences that converges to efficient solution points of the multiobjective optimization problem under mild assumptions. Furthermore, we also propose accelerated versions of the proposed algorithms by adding an inertial term and we established the nonasymptotic O(1k) convergence rate, too. Numerical illustrations shows the practical usability of the proposed algorithms.
Fields of Study & Subjects
Optimization and Variational Analysis
Advanced Multi-Objective Optimization Algorithms
Advanced Optimization Algorithms Research
Publication details
- Journal / source
- Optimization
- Publisher
- Informa UK Limited
- Volume
- 75
- Issue
- 3
- Pages
- 589–614
- Publication date
- 10 February 2026
- Language
- EN