Distributed Random Convex Programming via Constraints Consensus

@article{Carlone2012DistributedRC,
  title={Distributed Random Convex Programming via Constraints Consensus},
  author={Luca Carlone and Vaibhav Srivastava and Francesco Bullo and Giuseppe Carlo Calafiore},
  journal={SIAM J. Control and Optimization},
  year={2012},
  volume={52},
  pages={629-662}
}
This paper discusses distributed approaches for the solution of random convex programs (RCP). RCPs are convex optimization problems with a (usually large) number N of randomly extracted constraints; they arise in several applicative areas, especially in the context of decision under uncertainty, see [2],[3]. We here consider a setup in which instances of the random constraints (the scenario) are not held by a single centralized processing unit, but are distributed among different nodes of a… CONTINUE READING

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References

Publications referenced by this paper.
SHOWING 1-10 OF 31 REFERENCES

Random Convex Programs

  • SIAM Journal on Optimization
  • 2010
VIEW 10 EXCERPTS

CVX: MATLAB Software for Disciplined Convex Programming

M. Grant, S. Boyd
  • Version 2.0, http://cvxr.com/cvx
  • 2013
VIEW 1 EXCERPT

A distributed algorithm for random convex programming

  • International Conference on NETwork Games, Control and Optimization (NetGCooP 2011)
  • 2011
VIEW 3 EXCERPTS