Periodic control of intermittent demand items: theory and empirical analysis

Syntetos, Aris A.; Babaï, Mohamed Zied; Dallery, Yves; Teunter, Ruud H.

doi:10.1057/palgrave.jors.2602593

Cited by 39 publications

(19 citation statements)

References 29 publications

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“…Periodic formulations may hide the effects of delayed ordering, since delays shorter than the review period may not be effectively realised. It is important to note that periodic control situations where the lead time may be shorter than the average inter-demand interval have already been explored in the literature (Syntetos et al, 2009). …”

Section: Discussionmentioning

confidence: 99%

On the benefits of delayed ordering

Syntetos

Teunter

Babaï

et al. 2016

European Journal of Operational Research

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Practical experience and scientific research show that there is scope for improving the performance of inventory control systems by delaying a replenishment order that is otherwise triggered by generalised and all too often inappropriate assumptions. This paper presents the first analysis of the most commonly used continuous (s, S) policies with delayed ordering for inventory systems with compound demand. We analyse policies with a constant delay for all orders as well as more flexible policies where the delay depends on the order size. For both classes of policies and general demand processes, we derive optimality conditions for the corresponding delays. In a numerical study with Erlang distributed customer inter-arrival times, we compare the cost performance of the optimal policies with no delay, a constant delay and flexible delays. Sensitivity results provide insights into when the benefit of delaying orders is most pronounced, and when applying flexible delays is essential.

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Section: Discussionmentioning

confidence: 99%

On the benefits of delayed ordering

Syntetos

Teunter

Babaï

et al. 2016

European Journal of Operational Research

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“…Many distributions have been suggested to model the sizes of demand when demand occurs (Axsäter 2006), such as the geometric (Watson 1987, Johnston et al 2003, Chew and Johnson 2006, logarithmic (Syntetos and Boylan 2006), lognormal (Syntetos et al 2009a), etc. However, and as discussed in the next section, modeling for forecasting purposes is insensitive to such a distributional assumption.…”

Section: Research Relevancementioning

confidence: 99%

Forecasting of compound Erlang demand

Syntetos

Babaï

Luo

2015

Journal of the Operational Research Society

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Intermittent demand items dominate service and repair inventories in many industries and they are known to be the source of dramatic inefficiencies in the defense sector. However, research in forecasting such items has been limited. Previous work in this area has been developed upon the assumption of a Bernoulli or a Poisson demand arrival process. Nevertheless, intermittent demand patterns may often deviate from the memory-less assumption. In this work we extend analytically previous important results to model intermittent demand based on a compound Erlang process, and we provide a comprehensive categorisation scheme to be used for forecasting purposes. In a numerical investigation we assess the benefit of departing from the memory-less assumption and we provide insights into how the degree of determinism inherent in the process affects forecast accuracy. Operationalised suggestions are offered to managers and software manufacturers dealing with intermittent demand items.

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“…Extensions into the distribution of inventory costs are feasible and intuitively appealing (Luciano et al, 2003) and further work into the issue of the efficient computation of VaR would constitute an important addition to the current state of knowledge in the area of inventory control. Dataset #2 has been used in the studies conducted by Syntetos et al (2009a) and Teunter et al (2010) Dataset #3 has been used in the study conducted by Babai et al (2010). 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 …”

Section: Conclusion Implications and Further Researchmentioning

confidence: 99%