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Demand Forecasting for Inventory Control

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Demand Forecasting for Inventory Control/ by Nick T. Thomopoulos.
作者:	Thomopoulos, Nick T.
面頁冊數:	XIII, 183 p. 28 illus. in color.online resource. :
Contained By:	Springer Nature eBook
標題:	Operations research. -
電子資源:	https://doi.org/10.1007/978-3-319-11976-2
ISBN:	9783319119762

Demand Forecasting for Inventory Control
Thomopoulos, Nick T.

Demand Forecasting for Inventory Control[electronic resource] /by Nick T. Thomopoulos. - 1st ed. 2015. - XIII, 183 p. 28 illus. in color.online resource.

Introduction -- Demand History -- Horizontal Forecasts -- Trend Forecasts -- Seasonal Forecasts -- Promotion Forecasts -- Multi SKU Forecasts -- Forecast Sensitivity -- Filtering Outliers -- Standard Normal and Truncated Normal Distributions -- Safety Stock -- Auxiliary Forecasts.

This book describes the methods used to forecast the demands at inventory holding locations. The methods are proven, practical and doable for most applications, and pertain to demand patterns that are horizontal, trending, seasonal, promotion and multi-sku. The forecasting methods include regression, moving averages, discounting, smoothing, two-stage forecasts, dampening forecasts, advance demand forecasts, initial forecasts, all time forecasts, top-down, bottom-up, raw and integer forecasts, Also described are demand history, demand profile, forecast error, coefficient of variation, forecast sensitivity and filtering outliers. The book shows how the forecasts with the standard normal, partial normal and truncated normal distributions are used to generate the safety stock for the availability and the percent fill customer service methods. The material presents topics that people want and should know in the work place. The presentation is easy to read for students and practitioners; there is little need to delve into difficult mathematical relationships, and numerical examples are presented throughout to guide the reader on applications. Practitioners will be able to apply the methods learned to the systems in their locations, and the typical worker will want the book on their bookshelf for reference. The potential market is vast. It includes everyone in professional organizations like APICS, DSI and INFORMS; MBA graduates, people in industry, and students in management science, business and industrial engineering.

ISBN: 9783319119762

Standard No.: 10.1007/978-3-319-11976-2doiSubjects--Topical Terms:

573517
Operations research.

LC Class. No.: HD30.23

Dewey Class. No.: 658.40301

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520 $a This book describes the methods used to forecast the demands at inventory holding locations. The methods are proven, practical and doable for most applications, and pertain to demand patterns that are horizontal, trending, seasonal, promotion and multi-sku. The forecasting methods include regression, moving averages, discounting, smoothing, two-stage forecasts, dampening forecasts, advance demand forecasts, initial forecasts, all time forecasts, top-down, bottom-up, raw and integer forecasts, Also described are demand history, demand profile, forecast error, coefficient of variation, forecast sensitivity and filtering outliers. The book shows how the forecasts with the standard normal, partial normal and truncated normal distributions are used to generate the safety stock for the availability and the percent fill customer service methods. The material presents topics that people want and should know in the work place. The presentation is easy to read for students and practitioners; there is little need to delve into difficult mathematical relationships, and numerical examples are presented throughout to guide the reader on applications. Practitioners will be able to apply the methods learned to the systems in their locations, and the typical worker will want the book on their bookshelf for reference. The potential market is vast. It includes everyone in professional organizations like APICS, DSI and INFORMS; MBA graduates, people in industry, and students in management science, business and industrial engineering.
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