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SIAMJO
2008
99views more  SIAMJO 2008»
13 years 5 months ago
The Exact Feasibility of Randomized Solutions of Uncertain Convex Programs
Many optimization problems are naturally delivered in an uncertain framework, and one would like to exercise prudence against the uncertainty elements present in the problem. In pr...
Marco C. Campi, Simone Garatti
AUTOMATICA
2007
72views more  AUTOMATICA 2007»
13 years 5 months ago
A probabilistic analytic center cutting plane method for feasibility of uncertain LMIs
ust control problems can be formulated in abstract form as convex feasibility programs, where one seeks a solution x that satisfies a set of inequalities of the form F . = {f (x,...
Giuseppe C. Calafiore, Fabrizio Dabbene
EOR
2006
103views more  EOR 2006»
13 years 5 months ago
Exact solutions to a class of stochastic generalized assignment problems
This paper deals with a stochastic Generalized Assignment Problem with recourse. Only a random subset of the given set of jobs will require to be actually processed. An assignment...
Maria Albareda-Sambola, Maarten H. van der Vlerk, ...
CDC
2008
IEEE
145views Control Systems» more  CDC 2008»
14 years 3 days ago
Parameter estimation with expected and residual-at-risk criteria
In this paper we study a class of uncertain linear estimation problems in which the data are affected by random uncertainty. In this setting, we consider two estimation criteria,...
Giuseppe Carlo Calafiore, Ufuk Topcu, Laurent El G...
MP
2002
110views more  MP 2002»
13 years 5 months ago
Robust optimization - methodology and applications
Abstract. Robust Optimization (RO) is a modeling methodology, combined with computational tools, to process optimization problems in which the data are uncertain and is only known ...
Aharon Ben-Tal, Arkadi Nemirovski