Decomposition-Invariant Pairwise Frank-Wolfe Algorithm for Constrained Multiobjective Optimization

Fuente: arXiv
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Autores principales: Fan, Zhuoxin, Tang, Liping
Formato: Preprint
Publicado: 2024
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author Fan, Zhuoxin
Tang, Liping
author_facet Fan, Zhuoxin
Tang, Liping
contents Recently the away-step Frank-Wolfe algoritm for constrained multiobjective optimization has been shown linear convergence rate over a polytope which is generated by finite points set. In this paper we design a decomposition-invariant pairwise frank-wolfe algorithm for multiobjective optimization that the feasible region is an arbitrary bounded polytope. We prove it has linear convergence rate of the whole sequence to a pareto optimal solution under strongly convexity without other assumptions.
format Preprint
id arxiv_https___arxiv_org_abs_2409_04671
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Decomposition-Invariant Pairwise Frank-Wolfe Algorithm for Constrained Multiobjective Optimization
Fan, Zhuoxin
Tang, Liping
Optimization and Control
49M05, 65K05, 90C29
Recently the away-step Frank-Wolfe algoritm for constrained multiobjective optimization has been shown linear convergence rate over a polytope which is generated by finite points set. In this paper we design a decomposition-invariant pairwise frank-wolfe algorithm for multiobjective optimization that the feasible region is an arbitrary bounded polytope. We prove it has linear convergence rate of the whole sequence to a pareto optimal solution under strongly convexity without other assumptions.
title Decomposition-Invariant Pairwise Frank-Wolfe Algorithm for Constrained Multiobjective Optimization
topic Optimization and Control
49M05, 65K05, 90C29
url https://arxiv.org/abs/2409.04671