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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.

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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.

Research and development (R&D) is important for economic growth. Many countries therefore attempt to raise the investments in R&D. Increasingly important in this context are foreign direct investments in R&D, which on average constitute 24% of total business R&D investments in the EU15 (between 1995 and 2004). This paper focuses on the question: 'Which location factors are decisive for the attractiveness of foreign R&D investments?' The answer to this question is crucial in order to attract new foreign investments in R&D and to keep home-base R&D activities in a country or to expand them. Based on econometric analysis, we show in this paper that, besides the impact of human capital and value added of foreign affiliates, a country's stock of private R&D capital is an important location factor for international R&D activities. The interpretation of this result is twofold. First of all, it indicates that firms locate their R&D abroad to reap the benefits of knowledge-spillover effects. Secondly, we argue that the stock of private R&D capital embodies a so-called 'place-to-be effect'. This effect can be regarded as a signalling effect to firms: if the private R&D capital stock in a country is relatively large, framework conditions for research are in place and the innovative climate is likely to be excellent.internationalization of R&D, R&D location factors, R&D investment climate, foreign direct investment,

In this chapter we discuss a tactical optimisation problem that arises in a multistage distribution system where customer orders can be delivered from any stockpoint. A simple rule to allocate orders to locations is a break quantity rule, which routes large orders to higher-stage stockpoints and small orders to end-stockpoints. A so-called break quantity determines whether an order is small or large. We present a qualitative discussion on the implications of this rule for the marketing process, and a qualitative and quantitative analysis on the implications for the transportation and inventory costs. Furthermore, we present a case study for a company that implemented a break quantity rule. Finally, in the last section the main results are summarised.

In this paper we discuss a general framework for single component replacement models. This framework is based on the regenerative structure of these models and by using results from renewal theory a unified presentation of the discounted and average finite and infinite horizon cost models is given. Finally, some well-known replacement models are discussed, and making use of the previous results an easy derivation of their cost functions is presented.