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Distributed primal–dual interior-point methods for solving tree-structured coupled convex problems using message-passing
39
Citations
27
References
2016
Year
Numerical AnalysisDistributed AlgorithmEngineeringParallel Problem SolvingDistributed AlgorithmsDistributed OptimizationConvex OptimizationChordal SparsityComputational ComplexityDistributed Problem SolvingComputer ScienceInherent Tree StructureLinear ProgrammingParallel ComputingPrimal–dual Interior-point MethodsVariational Inequalities
In this paper, we propose a distributed algorithm for solving coupled problems with chordal sparsity or an inherent tree structure which relies on primal–dual interior-point methods. We achieve this by distributing the computations at each iteration, using message-passing. In comparison to existing distributed algorithms for solving such problems, this algorithm requires far fewer iterations to converge to a solution with high accuracy. Furthermore, it is possible to compute an upper-bound for the number of required iterations which, unlike existing methods, only depends on the coupling structure in the problem. We illustrate the performance of our proposed method using a set of numerical examples.
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