John E. Boylan - Intermittent Demand Forecasting

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INTERMITTENT DEMAND FORECASTING
The first text to focus on the methods and approaches of intermittent, rather than fast, demand forecasting
Intermittent Demand Forecasting No prior knowledge of intermittent demand forecasting or inventory management is assumed in this book. The key formulae are accompanied by worked examples to show how they can be implemented in practice. For those wishing to understand the theory in more depth, technical notes are provided at the end of each chapter, as well as an extensive and up-to-date collection of references for further study. Software developments are reviewed, to give an appreciation of the current state of the art in commercial and open source software.
“Intermittent demand forecasting may seem like a specialized area but actually is at the center of sustainability efforts to consume less and to waste less. Boylan and Syntetos have done a superb job in showing how improvements in inventory management are pivotal in achieving this. Their book covers both the theory and practice of intermittent demand forecasting and my prediction is that it will fast become the bible of the field.” —
, Professor, University of Nicosia, and Director, Institute for the Future and the Makridakis Open Forecasting Center (MOFC).
“We have been able to support our clients by adopting many of the ideas discussed in this excellent book, and implementing them in our software. I am sure that these ideas will be equally helpful for other supply chain software vendors and for companies wanting to update and upgrade their capabilities in forecasting and inventory management.”—
, VP, Research and Development, Blue Yonder.
“As product variants proliferate and the pace of business quickens, more and more items have intermittent demand. Boylan and Syntetos have long been leaders in extending forecasting and inventory methods to accommodate this new reality. Their book gathers and clarifies decades of research in this area, and explains how practitioners can exploit this knowledge to make their operations more efficient and effective.”—
, Professor Emeritus, Rensselaer Polytechnic Institute.

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Figure 23 Continuous review and policies for unit sized - фото 93

Figure 2.3 Continuous review картинка 94and картинка 95policies for unit sized transactions.

When the inventory position drops to (exactly) the order point ( картинка 96), then an order for a fixed quantity картинка 97is placed or, equivalently, enough is ordered to raise the inventory position up to the OUT level картинка 98. Note that, at the time of ordering, the inventory position always equals the stock on hand because there are no pending receipts from the supplier(s). Once the order is placed, the inventory position increases to картинка 99(stock on hand) + картинка 100(stock on order) (= картинка 101) and decreases thereafter in exactly the same way as the stock on hand. The quantity ordered is received after the lead time ( картинка 102), at which point in time the inventory position equals again the stock on hand.

The problem is to find the optimal values of the control parameters картинка 103and картинка 104. (See Technical Note 2.5for discussion of equivalence with картинка 105optimisation.) Optimality here refers to a solution that has been explicitly developed based on minimising the total inventory cost (Ordering cost + Holding cost + Backorder cost). In theory, optimisation of the two control parameters, картинка 106and картинка 107, should occur in parallel recognising that cost interactions exist between them. Alternatively, the parallel optimisation may be for картинка 108and картинка 109(rather than картинка 110and картинка 111) (see, for example, Wagner 1975). In practice, though, in our experience, a separate (independent) optimisation of these parameters is the norm because of its relative simplicity. Further arguments in support of this approach relate to its near‐optimal behaviour (Porteus 1985).

2.5.2 Periodic Review Systems

In periodic review systems, the inventory decision rules most usually take the form of a картинка 112or картинка 113policy, the former being the one to be discussed in more detail in this book. Under the regime of both policies, after every картинка 114periods (constant inventory review interval) enough is ordered to raise the inventory position up to the ‘order‐up‐to level’, картинка 115. The difference between the two policies is that the картинка 116policy requires the inventory position to be less than or equal to картинка 117(or in certain cases strictly less than картинка 118) before an order is placed. Therefore, the картинка 119policy always results in higher ordering costs because even a unit‐sized transaction during the review interval will trigger a replenishment requisition, whilst the картинка 120policy will place an order only if the cumulative demand, over the review interval, exceeds some minimum level. The картинка 121can be viewed as the periodic implementation of the картинка 122system because the картинка 123reduces to for Figure 24 Periodic review - фото 124for Figure 24 Periodic review policy In Figure - фото 125.

Figure 24 Periodic review policy In Figure 24 we show graphically the - фото 126

Figure 2.4 Periodic review картинка 127policy.

In Figure 2.4, we show graphically the operation of the картинка 128policy. For ease of presentation, we assume that no stockouts occur (i.e. backordered demand does not need to be accounted for). We further assume that the review interval is shorter than the lead time (as is typically the case in practice in wholesaling), i.e. картинка 129. In particular, we assume that картинка 130.

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