Essential intersection and approximation results for robust optimization. Hess, C., Seri, R., & Choirat, C. Journal of Nonlinear and Convex Analysis, 15(5):979 – 1002, 2014.
Essential intersection and approximation results for robust optimization [link]Paper  abstract   bibtex   
We examine the concept of essential intersection of a random set in the framework of robust optimization programs and ergodic theory. Using a recent extension of Birkhoff’s Ergodic Theorem developed by the present authors, it is shown that essential intersection can be represented as the countable intersection of random sets involving an asymptotically mean stationary transformation. This is applied to the approximation of a robust optimization program by a sequence of simpler programs with only a finite number of constraints. We also discuss some formulations of robust optimization programs that have appeared in the literature and we make them more precise, especially from the probabilistic point of view. We show that the essential intersection appears naturally in the correct formulation.
@Article{Hess2014,
  Title =	 {Essential intersection and approximation results for
                  robust optimization},
  Author =	 {Hess, C. and Seri, R. and Choirat, C.},
  Journal =	 {Journal of Nonlinear and Convex Analysis},
  Year =	 2014,
  Number =	 5,
  Pages =	 {979 -- 1002},
  Volume =	 15,
  Abstract =	 {We examine the concept of essential intersection of
                  a random set in the framework of robust optimization
                  programs and ergodic theory. Using a recent
                  extension of Birkhoff’s Ergodic Theorem developed by
                  the present authors, it is shown that essential
                  intersection can be represented as the countable
                  intersection of random sets involving an
                  asymptotically mean stationary transformation. This
                  is applied to the approximation of a robust
                  optimization program by a sequence of simpler
                  programs with only a finite number of
                  constraints. We also discuss some formulations of
                  robust optimization programs that have appeared in
                  the literature and we make them more precise,
                  especially from the probabilistic point of view. We
                  show that the essential intersection appears
                  naturally in the correct formulation.},
  Url =
                  {http://www.ybook.co.jp/online2/opjnca/vol15/p979.html}
}

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