This paper is concerned with hierarchical control of stochastic manufacturing systems with machines whose capacity states are governed by a Markov process dependent on the rates of production. The objective is to choose production rates that minimize the total inventory/shortage and production...

This paper is concerned with the optimal production planning in a dynamic stochastic manufacturing system consisting of a single machine that is failure prone and facing a constant demand. The objective is to choose the rate of production over time in order to minimize the long-run average cost...

This paper presents an asymptotic analysis of a stochastic manufacturing system consisting of parallel machines subject to breakdown and repair and facing a constant demand, as the rates of change of the machine states approach infinity. This situation gives rise to a limiting problem in which...

Business environments change over time. They are cyclic, show seasonality or just evolve over time. This is certainly true for customer demand. As a result, stationary demand distributions are crude approximations of true customer behavior at best. Yet, most classical stochastic inventory models...

This paper is concerned with near-optimal control of manufacturing systems consisting of two unreliable machines in tandem and having the objective of minimizing the total discounted cost of inventories/shortages over an infinite horizon. Asymptotic optimal feedback controls are constructed with...

This paper presents an extension of earlier research on hierarchical control of stochastic manufacturing systems with long-run average cost in which a positive inventory deterioration/cancellation rate for each product is assumed. Here we drop the assumption of the positive inventory...

We consider the problem of production control in a single machine, single product, unreliable manufacturing system facing a constant demand d. The goal is to minimize the expected average (per unit time) inventory/backlog costs. Under heavy traffic condition, i.e., when the average production...

We develop a general filtering framework for the problem of estimating the state of a system whose dynamics is governed by a discrete-time Markov process. We describe applications to inventory control systems with partial observations. We introduce conditional distributions and unnormalized...