This paper reviews inventory models with multiple supply options and discusses their contribution to supply chain management. After discussing strategic aspects of supplier competition and the role of operational flexibility in global sourcing, inventory models which use several suppliers in order to avoid or reduce the effects of shortage situations are outlined. Further, related inventory pro...

JDMS, Volume 2, Issue 2, April 2005 Pages 87–100 © 2005 The Society for Modeling and Simulation International Traditional multi-echelon inventory and readiness-based models have not fully examined the ability of effective transportation utilization to reduce cost, delay times, and improve readiness in the overall military logistics network. In this paper, we develop a simulation-based methodolo...

A centralized multi-echelon, multi-product supply chain network is presented in a multi-period setting with products that show varying demand against price. An important consideration in such complex supply chains is to maintain system performance at high levels for varying demands that may be sensitive to product price. In order to examine the price-centric behavior of the customers, the conce...

Nowadays, Companies have to deal with an uncertain demand which is more difficult to handle when it has a non-stationary pattern. Simultaneous decrease of customer service and increase of stock costs are the most significant effects of such demand uncertainty. To deal with this issue, inventory optimization models must be adapted to cover a multi-echelon network structure and to consider altern...

We consider the problem of minimizing the overall cost of a supply chain, over a possibility long horizon, under demand uncertainly which is known only crudely. Under such circumstances, the method of choice is Robust Optimization, in particular the Affinely Adjustable Robust Counterpart (AARC) method which leads to tractable deterministic optimization problems. The latter is due to a recent re...

Stochastic inventory control in multi-echelon systems poses hard problems in optimisation under uncertainty. Stochastic programming can solve small instances optimally, and approximately solve large instances via scenario reduction techniques, but it cannot handle arbitrary nonlinear constraints or other nonstandard features. Simulation optimisation is an alternative approach that has recently ...

We analyze a multistage inventory system with limited production capacity facing stochastic demands. Each node follows a periodic-review base-stock policy for echelon inventory: in each period, each node attempts to produce enough material to restore cumulative downstream inventory to a fixed target level. We develop approximations to the key measures of interest (average inventories, average b...

We consider a two-stage serial inventory system whose cost structure exhibits economies of scale in both stages. In the system, stage 1 faces Poisson demand and replenishes its inventory from stage 2, and the latter stage in turn orders from an outside supplier with unlimited stock. Each shipment, either to stage 2 or to stage 1, incurs a fixed setup cost. We derive important properties for a g...

Model predictive control (MPC) is presented as a robust, flexible decision framework for dynamically managing inventories and satisfying customer demand in demand networks. In this paper, a formulation and the benefits of an MPC-based, control-oriented tactical inventory management system meaningful to the semiconductor industry are presented via two significant examples. The translation of ava...