@inproceedings{d718f891512e4063a6eab1c478182fd4,
title = "Solving specified-time distributed optimization problem with local inequality constraint based on penalty method",
abstract = "This paper focuses on solving distributed optimization problems with local nonlinear inequality constraints in a specified-time over undirected graph. Here, we present a distributed optimization algorithm with specified-time. It can be used for the multi-agent network to minimize the sum of local objective functions. The establishment of specified-time in the proposed algorithm is independent of initial conditions and algorithm parameters. This is a completely distributed algorithm, which only needs information interaction between adjacent agents to complete the specified-time optimization problem. The effectiveness of the proposed theory is demonstrated by an example of resource allocation.",
keywords = "Distributed optimization, Local inequality, Penalty function, Specified-time convergence",
author = "Yuquan Zhang and Chengxin Xian and Yu Zhao",
note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 3rd International Conference on Industrial Artificial Intelligence, IAI 2021 ; Conference date: 08-11-2021 Through 11-11-2021",
year = "2021",
doi = "10.1109/IAI53119.2021.9619230",
language = "英语",
series = "3rd International Conference on Industrial Artificial Intelligence, IAI 2021",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "3rd International Conference on Industrial Artificial Intelligence, IAI 2021",
}