Service-oriented decisions on inventory levels in the case of incomplete demand information
- PDF / 810,085 Bytes
- 14 Pages / 595.276 x 790.866 pts Page_size
- 62 Downloads / 144 Views
ORIGINAL PAPER
Service-oriented decisions on inventory levels in the case of incomplete demand information Katrien Ramaekers • Gerrit K. Janssens
Received: 26 September 2011 / Accepted: 20 March 2012 / Published online: 7 April 2012 Springer-Verlag 2012
Abstract New products without historical demand information or slow-moving items with little such information cause difficulties in defining inventory management policies facing demand uncertainty. The classical approach using the Normal distribution for describing the random demand during lead time might lead to a degraded level of customer service. But the choice for other types of distributions is also no option, so it is realistic that the full functional form of the distribution is unknown, but the decision-maker has some but not incomplete information on the demand distribution during lead time. As the distribution is only partially specified, several distributions satisfy the known information. Customer service measures therefore also take values in an interval between a lower and an upper bound. In this paper, upper and lower bounds are determined for two performance measures: the number of stock-out units and the stock-out probability per replenishment cycle, given incomplete information about the demand distribution, that is only the first two moments and the range, are known. Based on these results, the optimal inventory level given the desired maximum number of stock-out units or the desired maximum stock-out probability is calculated for the case where only the first two moments are known. The results of our approach are compared to the more traditional approach where a Normal distribution of demand during lead time is assumed. Comparisons with the Gamma, Uniform and symmetric triangular distribution are made. Furthermore, the K. Ramaekers G. K. Janssens (&) Transportation Research Institute, Hasselt University, Wetenschapspark 5 bus 6, 3590 Diepenbeek, Belgium e-mail: [email protected] K. Ramaekers e-mail: [email protected]
robustness of our bounds to uncertainty in the parameters is tested. Keywords Inventory management Performance measures Incomplete information Demand distribution
1 Introduction Uncertainty in inventory systems may be due to suppliers or customers. On the suppliers’ side, uncertainty (such as lead time, yield and quality) asks for corrective action. Decisions on lot sizing with uncertain yield are important especially in production/manufacturing systems (e.g. [24]). Uncertainty, which is attributable to customers, relates especially to demand. If insufficient inventory is held, a stock-out may occur leading to shortage costs or customer service degradation. As shortage costs are usually high in relation to holding costs, companies hold additional inventory, above their forecasted needs, to add a margin of safety. Some decision models combine both the uncertainty of yield and demand (e.g. [12]). Determination of an inventory replenishment policy, of the quantities to order, of the review period is t
Data Loading...
