We extend the linear programming (LP) model of deterministic supply-chain planning to take demand uncertainty and cash flows into account for the medium term. The resulting stochastic LP model is similar to that of Asset-Liability Management (ALM), for which the literature using stochastic...

This paper is concerned with finding an optimal inventory policy for a finite horizon, two-stage inventory model. In this model, products may be manufactured in two stages. The first stage uses raw material from an external supplier and the second stage uses raw material from defective items...

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...

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....

The goal programming (GP) is a well-known approach applied to multi-criteria decision making (M-DM). It has been used in many domains and the literature offers diverse extensions of this procedure. On the other hand, so far, some evident analogies between M-DM under certainty and scenario-based...

This paper introduces a flexible method based on dynamic programming to calculate the quantitative value of any approach to managing the innovation process. The quantification lets managers precisely compare the values of different approaches, and so identify those that are optimised for their...

This paper calls for a change in paradigm in lot sizing and scheduling. Traditionally, a discrete time scale is chosen to model lot sizing and scheduling. As an alternative, the so-called block planning concept is proposed which is based on a continuous representation of time. A mixed-integer...

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 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...