The paper is concerned with fully nonlinear second order Hamilton{Jacobi{Bellman{ Isaacs equations of elliptic type in separable Hilbert spaces which have unbounded rst and second order terms. The viscosity solution approach is adapted to the equations under consideration and the existence and uniqueness of viscosity solutions is proved. A stochastic optimal control problem driven by a paraboli...

We consider a stochastic control model driven by a fractional Brownian motion. This model is a formal approximation to a queueing network with an ON-OFF input process. We study stochastic control problems associated with the long-run average cost, the infinite horizon discounted cost, and the finite horizon cost. In addition, we find a solution to a constrained minimization problem as an applic...

Decomposition and Monte Carlo sampling-based algorithms hold much promise for solving stochastic programs with many scenarios. A critical component of such algorithms is a stopping criterion to ensure the quality of the solution. In this paper, we develop a stopping rule theory for a class of algorithms that estimate bounds on the optimal objective function value by sampling. We provide rules f...

We consider a stochastic control model driven by a fractional Brownian motion. This model is a formal approximation to a queueing network with an ON–OFF input process. We study stochastic control problems associated with the long-run average cost, the infinite-horizondiscounted cost, and thefinite-horizon cost. In addition, wefind a solution to a constrained minimization problem as an applicati...

We give a unique classical solution to initial value problem for a system of partial differential equations for the densities of components of one dimensional incompressible fluid mixture driven by evaporation. Motivated by the known fact that the solution appears as an infinite particle limit of stochastic ranking processes, which is a simple stochastic model of time evolutions of e.g., Amazon...

We consider the solution of stochastic dynamic programs using sample path estimates. Applying the theory of large deviations, we derive probability error bounds associated with the convergence of the estimated optimal policy to the true optimal policy, for finite horizon problems. These bounds decay at an exponential rate, in contrast with the usual canonical (inverse) square root rate associat...

Descriptive simulation finds the performance measure of a system, given a particular value for the input parameters. Inverse simulation reverses this and attempts to find the controllable input parameters required to achieve a particular performance measure. This paper proposes using a ‘stochastic approximation’ to estimate the necessary design parameters within a range of desired accuracy. The...

In this paper, a stochastic predator-prey system with Holling II functional response is studied. First, we show that there is a unique positive solution to the system for any given positive initial value. Then, stochastically bounded of the positive solution to the stochastic system is derived. Moreover, sufficient conditions for global asymptotic stability are also established. In the end, som...

The aim of seismic inversion is mapping all of the subsurface structures from seismic data. Due to the band-limited nature of the seismic data, it is difficult to find a unique solution for seismic inversion. Deterministic methods of seismic inversion are based on try and error techniques and provide a smooth map of elastic properties, while stochastic methods produce high-resolution maps of el...