文献类型：期刊文献

英文题名：Distributed Constrained Optimization with Uncoordinated Step Sizes: A Case Study on Ethylene Plant

作者：Liu, Bing[1]; Li, Zhongmei[1]; Du, Wenli[2]

机构：[1] School of Information Science and Engineering, East China University of Science and Technology, Shanghai, China; [2] Engineering Research Center of Process System Engineering, Ministry of Education East China University of Science and Technology, Shanghai, China

年份：2024

起止页码：431

外文期刊名：Proceedings - 2024 China Automation Congress, CAC 2024

收录：EI(收录号：20251118057617)

语种：英文

外文关键词：Convex optimization - Global optimization - Optimization algorithms - Shape optimization - Structural optimization - Topology

摘要：This paper investigates an uncoordinated step sizes distributed optimization algorithm based on an undirected topology network structure, which can handle distributed optimization problems with inequality constraints and heterogeneity (losing the global clock) by only communicating with neighboring nodes. Firstly, an "Adapt-Then-Combine Distributed Inexact Gradient tracking subject to Inequality Constraints (ATC-DIGing-IC)" algorithm is proposed for μ-strongly convex and l-smooth objective functions. Using the "Adapt-Then-Combine (ATC)" framework and the gradient information tracking structure, the flexibility and fastness of the algorithm can be guaranteed under the uncoordinated step size. Then, a parameter projection technique is introduced to handle the inequality constraints without introducing additional auxiliary variables. Subsequently, the convergence results of the algorithm and the bounds on the uncoordinated step sizes are theoretically analyzed. Finally, the algorithm is applied to a plant-wide separation production process of an ethylene plant, and the experimental results show that the proposed algorithm requires a shorter optimization time than the existing methods. ? 2024 IEEE.