Publication | Closed Access
Distributed Multi-Agent Optimization Based on an Exact Penalty Method with Equality and Inequality Constraints
17
Citations
10
References
2016
Year
Mathematical ProgrammingEngineeringDistributed Ai SystemMulti-agent LearningOperations ResearchDistributed CoordinationSystems EngineeringDistributed Problem SolvingOptimization ProtocolCombinatorial OptimizationMechanism DesignLinear OptimizationExact Penalty MethodInequality ConstraintsDistributed OptimizationDistributed Constraint OptimizationDistributed SystemsComputer ScienceMulti-agent Mechanism DesignMulti-agent Optimization
AbstractThis 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.Keywordsdistributed multi-agent optimizationnetworked systemsexact penalty methodequality and inequality constraints
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