In this paper an inventory model with several demand classes, prioritised according to importance, is analysed. We consider a lot-for-lot or S , 1; S i n v entory model with lost sales. For each demand class there is a critical stock level at and below which demand from that class is not satis ed from stock on hand. In this way stock is retained to meet demand from higher priority demand classes. A set of such critical levels determines the stocking policy. F or Poisson demand and a generally distributed lead time we derive expressions for the service levels for each demand class and the average total cost per unit time. E cient solution methods for obtaining optimal policies, with and without service level constraints, are presented. Numerical experiments in which the solution methods are tested demonstrate that signi cant cost reductions can be achieved by distinguishing between demand classes.
In this chapter we discuss inventory systems where several demand classes may be distinguished. In particular, we focus on single-location inventory systems and we analyse the use of a so-called critical level policy. With this policy some inventory is reserved for high-priority demand. A n umber of practical examples where several demand classes naturally arise are presented, and the implications and modelling of the critical level policy in distribution systems are discussed. Finally, a n o verview of the literature on inventory systems with several demand classes is given.
In most multi-item inventory systems, the ordering costs consist of a major cost and a minor cost for each item included. Applying for every individual item a cyclic inventory policy, where the cycle length is a multiple of some basic cycle time, reduces the major ordering costs. An ecient algorithm to determine the optimal policy of this type is discussed in this paper. It is shown that this algorithm can be used for deterministic multi-item inventory problems, with general cost rate functions and possibly service level constraints, of which the well-known joint replenishment problem is a special case. Some useful results in determining the optimal control parameters are derived, and worked out for piecewise linear cost rate functions. Numerical results for this case show that the algorithm signicantly outperforms other solution methods, both in the quality of the solution as in the running time.
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