Distributed Multi-Agent Optimization Based on an Exact Penalty Method with Equality and Inequality Constraints. Issue 4 (1st July 2016)

• Record Type: Journal Article
• Authors: Masubuchi, Izumi; Wada, Takayuki; Asai, Toru; Nguyen, Linh Thi Hoai; Ohta, Yuzo; Fujisaki, Yasumasa
• Is Part Of: SICE journal of control, measurement, and system integration. Volume 9:Issue 4(2016)
• Page Start: 179
• Page End: 186
• Publication Date: 2016-07-01
• Subjects: distributed multi-agent optimization -- networked systems -- exact penalty method -- equality and inequality constraints
• DOI: 10.9746/jcmsi.9.179
• Languages: English
• ISSNs: 1882-4889

Abstract

Abstract : This paper proposes a distributed multi-agent optimization protocol to minimize the average of objective functions of the agents in the network with satisfying equality and inequality constraints of each agent. The exact penalty method is adopted to obtain a linear distributed optimization protocol. The proposed protocol works only with the decision variables and does not need any additional variables. The proof of the consensus and convergence of the proposed protocol is provided as well as the boundedness under mild assumptions. The protocol is also illustrated by a numerical example.