DMCA
1 Distributed Abstract Optimization via Constraints Consensus: Theory and Applications
BibTeX
@MISC{Bullo_1distributed,
author = {Francesco Bullo},
title = {1 Distributed Abstract Optimization via Constraints Consensus: Theory and Applications},
year = {}
}
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Abstract
Abstract—Distributed abstract programs are a novel class of distributed optimization problems where (i) the number of variables is much smaller than the number of constraints and optimization programs are a generalization of linear programs that captures numerous geometric optimization problems. We propose novel constraints consensus algorithms for distributed abstract programs with guaranteed finite-time convergence to a programs and exchanging the solutions among neighboring processors. The proposed algorithms are appropriate for networks with weak time-dependent connectivity requirements and tight memory constraints. We show how the constraints consensus algorithms may be applied to suitable target localization and formation control problems. Index Terms—Distributed optimization, linear programs, consensus algorithms, target localization, formation control. I.
Keyphrases
distributed abstract optimization constraint consensus linear program suitable target localization index term abstract distributed abstract program weak time-dependent connectivity requirement novel constraint consensus algorithm guaranteed finite-time convergence neighboring processor consensus algorithm novel class distributed optimization problem numerous geometric optimization problem target localization abstract program tight memory constraint optimization program formation control formation control problem
