This paper deals with an impulsive stochastic fuzzy cellular neural networks with both time-varying and infinite distributed delays. Based on M-matrix theory and stochastic analysis technique, a sufficient condition is obtained to ensure the existence, uniqueness, and global exponential p−stability of the equilibrium point for the addressed impulsive stochastic fuzzy cellular neural network wit...

General automata are considered with respect to normal-ization over semirings. Possibilistic automata are deened as normal pessimistic fuzzy automata. Possibilistic automata are analogous to stochas-tic automata where stochastic (+=) semirings are replaced by possi-bilistic (_=^) semirings; but where stochastic automata must be normal, fuzzy automata may be (resulting in possibilistic automata)...

We present an algorithm for solving stochastic integer programming problems with recourse, based on a dual decomposition scheme and La-grangian relaxation. The approach can be applied to multi-stage problems with mixed-integer variables in each time stage. Numerical experience is presented for some two-stage test problems.

In this paper we consider the expected value function of a stochastic simple recourse program with random technology matrix and integer variables in the second stage. Due to its separability the analysis is straightforward. Conditions for finiteness, continuity, Lipschitz continuity and differentiability are derived by conditioning upon the technology matrix. The corresponding results for a fix...

We investigate the quality of solutions obtained from sample-average approximations to two-stage stochastic linear programs with recourse. We use a recently developed software tool executing on a computational grid to solve many large instances of these problems, allowing us to obtain high-quality solutions and to verify optimality and near-optimality of the computed solutions in various ways.

In this paper, we consider a new formulation for stochastic mathematical programs with complementarity constraints and recourse. We show that the new formulation is equivalent to a smooth semi-infinite program. Then, we propose a Monte Carlo sampling and penalty method for solving the problem. Comprehensive convergence analysis and numerical examples are included as well.

In this paper, the approximate controllability of impulsive linear fuzzy stochastic differential equations with nonlocal conditions in Banach space is studied. By using the Banach fixed point theorems, stochastic analysis, fuzzy process and fuzzy solution, some sufficient conditions are given for the approximate controllability of the system.

In this paper, the author presents a model to measure the superiority and inferiority of fuzzy numbers/fuzzy stochastic variables. Then, the new measures are used to convert the fuzzy (stochastic) linear program into the corresponding deterministic linear program. Numerical examples are provided to illustrate the effectiveness of the proposed method. 2006 Elsevier Inc. All rights reserved.

A general strong law of large numbers for stochastic programs is established. It is shown that solutions and approximate solutions may not be consistent with the strong law in general, but consistency holds locally, or when the decision space is compact. An additional integrability condition implies the uniform consistency of approximate solutions. The results are applied in the context of line...