Multiagent System With Periodic and Event-Triggered Communications for Solving Distributed Resource Allocation Problem

This article mainly investigates how to reduce the communication cost in multiagent system (MAS) for distributed optimization. First, a continuous-time distributed optimization model based on MAS is proposed for resource allocation (RA) with periodic communication. All agents in the system do not ne...

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Vydané v:IEEE transactions on systems, man, and cybernetics. Systems Ročník 53; číslo 10; s. 1 - 12
Hlavní autori: Li, Kaixuan, Liu, Qingshan, Zeng, Zhigang
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: New York IEEE 01.10.2023
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:
Constraint modelling
Convergence
Costs
Distributed optimization
event-triggered communication
Linear programming
Multi-agent systems
multiagent system (MAS)
Multiagent systems
Optimization
Optimization models
Resource allocation
resource allocation (RA)
Resource management
Technological innovation
ISSN:2168-2216, 2168-2232
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Popis
Shrnutí:This article mainly investigates how to reduce the communication cost in multiagent system (MAS) for distributed optimization. First, a continuous-time distributed optimization model based on MAS is proposed for resource allocation (RA) with periodic communication. All agents in the system do not need to be in constant contact with their neighbors, but contact at set intervals. This will greatly reduce the communication consumption of the system. Second, to further reduce the communication cost, MAS with event-triggered communication is proposed based on periodic communication. It is proved that the system is convergent to an optimal solution of the investigated problem subject to bound and equality constraints. Finally, two examples with simulations are given to verify the performance of the proposed system.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:2168-2216
2168-2232
DOI:10.1109/TSMC.2023.3281903