Ergodic Control in Stochastic Manufacturing Systems with Constant Demand

Ergodic Boundary/point Control of Stochastic Semilinear Systems

A controlled Markov process in a Hilbert space and an ergodic cost functional are given for a control problem that is solved where the process is a solution of a parameter-dependent semilinear stochastic differential equation and the control can occur only on the boundary or at discrete points in the domain. The linear term of the semilinear differential equation is the infinitesimal generator ...

Stochastic extension of cellular manufacturing systems: a queuing-based analysis

Clustering parts and machines into part families and machine cells is a major decision in the design of cellular manufacturing systems which is defined as cell formation. This paper presents a non-linear mixed integer programming model to design cellular manufacturing systems which assumes that the arrival rate of parts into cells and machine service rate are stochastic parameters and descri...

Stochastic Manufacturing & Service Systems

Manufacturing and service systems typically have random components affecting their behavior such as the demand for products and services. Much of the focus will be given on understanding and applying quantitative methods that are useful in analyzing, designing, and operating stochastic systems. We will additionally present applications of these methods for understanding, managing and reducing v...

Optimal capacity expansion for multi-product, multi-machine manufacturing systems with stochastic demand

We consider a discrete-time capacity expansion problem involving multiple product families, multiple machine types, and nonstationary stochastic demand. Capacity expansion decisions are made to strike an optimal balance between investment costs and lost sales costs. Motivated by current practices in the semiconductor and other high-tech industries, we assume that only minimal amounts of finishe...

Stochastic inventory control with partial demand observability