Convergence of Bregman Peaceman–Rachford Splitting Method for Nonconvex Nonseparable Optimization  

作　　者：Peng-Jie Liu Jin-Bao Jian Bo He Xian-Zhen Jiang 

机构地区：[1]College of Mathematics and Physics,Guangxi Key Laboratory of Hybrid Computation and IC Design Analysis,Center for Applied Mathematics and Artificial Intelligence,Guangxi University for Nationalities,Nanning,530006,Guangxi,China [2]College of Mathematics and Information Science,Guangxi University,Nanning,530004,Guangxi,China [3]School of Mathematics,China University of Mining and Technology,Xuzhou,221116,Jiangsu,China

出　　处：《Journal of the Operations Research Society of China》2023年第4期707-733,共27页中国运筹学会会刊（英文）

基　　金：supported by the National Natural Science Foundation of China(No.12171106);the Natural Science Foundation of Guangxi Province(Nos.2020GXNSFDA238017 and 2018GXNSFFA281007).

摘　　要：This work is about a splitting method for solving a nonconvex nonseparable optimization problem with linear constraints,where the objective function consists of two separable functions and a coupled term.First,based on the ideas from Bregman distance and Peaceman–Rachford splitting method,the Bregman Peaceman–Rachford splitting method with different relaxation factors for the multiplier is proposed.Second,the global and strong convergence of the proposed algorithm are proved under general conditions including the region of the two relaxation factors as well as the crucial Kurdyka–Łojasiewicz property.Third,when the associated Kurdyka–Łojasiewicz property function has a special structure,the sublinear and linear convergence rates of the proposed algorithm are guaranteed.Furthermore,some preliminary numerical results are shown to indicate the effectiveness of the proposed algorithm.

关 键 词：Nonconvex nonseparable optimization Peaceman-Rachford splitting method Bregman distance Kurdyka-Łojasiewicz inequality Convergence rate 

分 类 号：O17[理学—数学]