C Rajendran

We consider a static divergent two-stage supply chain with one distributor and many retailers. The unsatisfied demands at the retailers' end are treated as lost sales, whereas the unsatisfied demand is assumed to be backlogged at the distributor. The distributor uses an inventory rationing mechanism to distribute the available on-hand inventory among the retailers, when the sum of demands from the retailers is greater than the on-hand inventory at the distributor. The present study aims at determining the best installation inventory control-policy or order-policy parameters such as the base-stock levels and review periods, and inventory rationing quantities, with the objective of minimizing the total supply chain costs (TSCC) consisting of holding costs, shortage costs and review costs in the supply chain over a finite planning horizon. An exact solution procedure involving a mathematical programming model is developed to determine the optimum TSCC, base-stock levels, review periods and inventory rationing quantities (in the class of periodic review, order-up-to S policy) for the supply chain model under study. On account of the computational complexity involved in optimally solving problems over a large finite time horizon, a genetic algorithm (GA) based heuristic methodology is presented. © 2010 Elsevier Ltd.

This paper addresses the development of an inventory control mechanism and inventory rationing policies in a static divergent two-stage supply chain consisting of one single distributor and several retailers. The unsatisfied demand is assumed to be backlogged at both distributor's and retailers' ends. In the case of shortage at distributor, the available stock on hand is rationed among the retailers. Most of the studies in the literature treat ordering costs as negligible and assume the review period to be one unit of time. However, if there is a significant cost associated with the order placement, then the review period can be greater than one time unit. Hence, in this study, we consider ordering costs for retailers, and present a mathematical programming model which can give optimal base-stock levels and review periods and inventory rationing (in the class of periodic review, order-up-to S policy). A genetic algorithm-based heuristic algorithm is also presented for solving problems with a large time horizon. © 2010 Inderscience Enterprises Ltd.

A critical problem often faced by distribution centres that hold finished-good inventory is inventory rationing. A rationing problem arises when the available resources cannot satisfy all demand, indicating a shortage at the distribution centre. We consider a divergent two-stage supply chain with one distributor and four retailers. Retailers face external demand, and they in turn place the replenishment demand to the distributor. The unsatisfied demand is assumed to be backlogged at both distributor's and retailer's ends. Our study focuses on determining a rationing policy and base-stock levels (assuming order-up-to level policy), where the available stock at the distributor is rationed among the successors (i.e. retailers) in case of shortage, with the objective of minimising total holding and backlog costs in the supply chain. We present a mathematical programming model, which can give optimal solutions in the class of base-stock policy, and a genetic algorithm-based heuristic methodology for determining the base-stock levels and rationing fractions. Copyright © 2010 Inderscience Enterprises Ltd.