Quadratic stochastic progr ms (QSP) with recourse ca be formulate s nonlinear co ve progr mming probl ms. By attaching a Larange ultiplier vector to the nonlinear convex program, we rewrite the problem as a ystem of nonsmooth equations. We co sid a Newton-like method for solving he system and establish global c nverg nce a d l c superlinear co vergence of the method. Several methods f r special...

In the paper we consider fuzzy stochastic integral equations using the methods of stochastic inclusions. The idea is to consider an associated martingale problem and its solutions in order to obtain a solution to the fuzzy stochastic equation.

This paper describes the robust output feedback ∞ H fuzzy control design for a class of nonlinear stochastic systems. The system dynamic is modelled by type ô It − stochastic differential equations. For general nonlinear stochastic systems, the ∞ H ontrol can be obtained by solving a second-order nonlinear Hamilton-Jacobi inequality. In general, it is difficult to solve the second-order nonline...

A stochastic version of a concentrator location problem is dealt with in which traffic demand at each terminal location is uncertain. The concentrator location problem is defined as to determine the following: (i) the numbers and locations of concentators that are to be open, and (ii) the allocation of terminals to concentrator sites. The problem is formulated as a stochastic multi-stage intege...

In this paper an alternative approach to solve uncertain Stochastic Differential Equation (SDE) is proposed. This uncertainty occurs due to the involved parameters in system and these are considered as Triangular Fuzzy Numbers (TFN). Here the proposed fuzzy arithmetic in [2] is used as a tool to handle Fuzzy Stochastic Differential Equation (FSDE). In particular, a system of Ito stochastic diff...

In the development of a speech understanding system, the recourse to stochastic techniques can greatly reduce the need for human expertise. A known disadvantage is that stochastic models require large annotated training corpora in order to reliably estimate model parameters. Manual semantic annotation of such corpora is tedious, expensive, and subject to inconsistencies. In order to decrease th...

In this paper, stochastic programming problems are viewed as parametric programs with respect to the probability distributions of the random coefficients. General results on quantitative stability in parametric optimization are used to study distribution sensitivity of stochastic programs. For recourse and chance constrained models quantitative continuity results for optimal values and optimal ...

SETSTOCH is a tool for linking Algebraic Modeling Languages (AMLs) with Specialized Stochastic Programming Solvers (SSPSs). Its main role is to retrieve from the AML a dynamically ordered core model (baseline scenario) that is then sent automatically to the SSPS. The user is then able to take full advantage of speci c SSPS features. The current implementation of SETSTOCH enables to access the S...