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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10 Chapter 11Figure 11.1 Customer demand and forecasting.Figure 11.2 Categorisation of non‐normal demand patterns.Figure 11.3 Categorisation based on sources of demand characteristics.Figure 11.4 Categorisation by mean square error: SES (issue points, картинка 39) vs. C...Figure 11.5 Categorisation by mean square error: SES vs. SBA.

11 Chapter 12Figure 12.1 Maintenance generated demand and forecasting.Figure 12.2 Life cycle stages.Figure 12.3 TSB and Croston forecasts.Figure 12.4 Forecasting in context.Figure 12.5 Inventory‐forecasting interactions.

12 Chapter 13Figure 13.1 Intermittent series.Figure 13.2 Cumulative frequency percentages: three‐month overlapping blocks...Figure 13.3 Proportional reduction in variance of CDF estimates by using OB ...Figure 13.4 Cumulative frequency percentages (OB, NOB, and bootstrap).

13 Chapter 14Figure 14.1 Demand transitions from one period to the next.

Guide

1 Cover

2 Table of Contents

3 Begin Reading

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Intermittent Demand Forecasting

Context, Methods and Applications

John E. Boylan

Lancaster University

Lancaster, UK

Aris A. Syntetos

Cardiff University

Cardiff, UK

This edition first published 2021 2021 John Wiley Sons Ltd All rights - фото 40

This edition first published 2021

© 2021 John Wiley & Sons Ltd

All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording or otherwise, except as permitted by law. Advice on how to obtain permission to reuse material from this title is available at http://www.wiley.com/go/permissions.

The right of John E. Boyan and Aris A. Syntetos to be identified as the authors of this work has been asserted in accordance with law.

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