Two-stage stochastic optimization problems with stochastic ordering constraints on the recourse
AbstractWe consider two-stage risk-averse stochastic optimization problems with a stochastic ordering constraint on the recourse function. Two new characterizations of the increasing convex order relation are provided. They are based on conditional expectations and on integrated quantile functions: a counterpart of the Lorenz function. We propose two decomposition methods to solve the problems and prove their convergence. Our methods exploit the decomposition structure of the risk-neutral two-stage problems and construct successive approximations of the stochastic ordering constraints. Numerical results confirm the efficiency of the methods.
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Bibliographic InfoArticle provided by Elsevier in its journal European Journal of Operational Research.
Volume (Year): 219 (2012)
Issue (Month): 1 ()
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Web page: http://www.elsevier.com/locate/eor
Increasing convex order; Stochastic dominance; Decomposition methods; Lorenz curve; Survival function; Stochastic programming;
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