A study of Liu-Storey conjugate gradient methods for vector optimization

作者：

Highlights：

• This work presents a study of Liu-Storey nonlinear conjugate gradient methods to solve vector optimization problems.

• We test our proposed algorithms on a set of problems taken from the multiobjective optimization literature.

• The Liu-Storey nonlinear conjugate gradient methods are efficient to find critical Pareto points.

摘要

•This work presents a study of Liu-Storey nonlinear conjugate gradient methods to solve vector optimization problems.•We test our proposed algorithms on a set of problems taken from the multiobjective optimization literature.•The Liu-Storey nonlinear conjugate gradient methods are efficient to find critical Pareto points.

论文关键词：Vector optimization,Conjugate gradient methods,Global convergence,Pareto efficiency

论文评审过程：Received 20 July 2021, Revised 30 November 2021, Accepted 16 March 2022, Available online 27 March 2022, Version of Record 27 March 2022.

论文官网地址：https://doi.org/10.1016/j.amc.2022.127099