This paper considers optimal infinite horizon stochastic production planning problems with capacity and demand to be finite state Markov chains. The existence of the optimal feedback control is shown with the aid of viscosity solutions to the dynamic programming equations. Turnpike set concepts...

Focuses on a study which developed a framework for forecast and decision horizons. Definition of finite and infinite horizon stochastic optimization problems for a given forecast; Description of the general framework; Conditions for the existence of a solution horizon; Development of sufficient...

This paper considers an infinite horizon stochastic production planning problem with the constraint that production rate must be nonnegative. It is shown that an optimal feedback solution exists for the problem. Moreover, this solution is characterized and is then compared with the solution of...

This paper considers an infinite horizon stochastic production planning problem with demand assumed to be a continuous-time Markov chain. The problems with control (production) and state (inventory) constraints are treated. It is shown that a unique optimal feedback solution exists, after first...

This paper proposes a new methodology to solve partially observed inventory problems. Generally, these problems have infinite dimensional states that are conditional distribution of the inventory level. Our methodology involves linearizing the state transitions via unnormalized probabilities. It...

In this paper we explore whether the incorporation of systematic time series analyses and mathematical optimization procedures in the practical planning process has the potential to improve production program decisions. The cases of four German cash crop farms are investigated over six planning...

We provide results for an efficient analytical valuation of partial moments of the multivariate Gaussian distribution over convex polyhedrons to aid the solution, sensitivity analysis and structural analysis of a large number of two-stage resource acquisition and allocation problems. These...

This paper proposes a new methodology to solve partially observed inventory problems. Generally, these problems have infinitedimensional states that are conditional distribution of the inventory level. Our methodology involves linearizing the state transitions via unnormalized probabilities. It...

This paper considers the dynamic lot sizing problem of H. M. Wagner and T. M. Whitin with the assumption that the total cost of n setups is a concave nondecreasing function of n. Such setup costs could arise from the worker learning in setups and/or technological improvements in setup methods....

We are concerned with a discrete-time undiscounted dynamic lot size model in which demand and the production setup cost are constant for an initial few periods and the holding cost of inventory is an arbitrary nondecreasing function assumed to be stationary (i.e., explicitly independent of time)...