文献类型：期刊文献

英文题名：Asynchronous distributed algorithm for constrained optimization and its application

作者：Wang, Ting[1];Li, Zhongmei[1];Nie, Rong[1];Du, Wenli[1,2]

机构：[1]East China Univ Sci & Technol, Key Lab Smart Mfg Energy Chem Proc, Minist Educ, Shanghai 200237, Peoples R China;[2]East China Univ Sci & Technol, Engn Res Ctr Proc Syst Engn, Minist Educ, Shanghai 200237, Peoples R China

年份：2025

卷号：68

期号：6

外文期刊名：SCIENCE CHINA-TECHNOLOGICAL SCIENCES

收录：;EI(收录号：20251818339063);WOS:【SCI-EXPANDED(收录号:WOS:001479426700001)】；

基金：This work was supported by the National Key Research and Development Program of China (Grant No. 2022YFB3305900), the National Natural Science Foundation of China (Grant No. 61988101), Shanghai Committee of Science and Technology, China (Grant No. 22DZ1101500), and the Fundamental Research Funds for the Central Universities.

语种：英文

外文关键词：distributed optimization; inequality constraints; communication delay; gradient tracking; geometric convergence

摘要：This study focuses on the distributed convex optimization problem with local boundary constraints and multiple inequality constraints, specifically considering scenarios involving communication delays and inconsistent updates between nodes. To tackle the problem with guaranteed constraint satisfaction, a distributed asynchronous optimization algorithm is proposed based on the parameter projection method. Moreover, an asynchronous gradient tracking mechanism is employed to accelerate convergence. In the convergence analysis, an augmented synchronous system with virtual nodes is adopted to transform the delayed optimization problem into a problem without delays. Based on the generalized small gain theory, the proposed algorithm is proved to achieve a geometric convergence rate. Finally, numerical simulations and industrial experiments verify the effectiveness of the proposed algorithm.