Forecasting intermittent demand by hyperbolic-exponential smoothing
نویسندگان
چکیده
منابع مشابه
Forecasting Intermittent Demand by Hyperbolic-Exponential Smoothing
Croston’s method is generally viewed as superior to exponential smoothing when demand is intermittent, but it has the drawbacks of bias and an inability to deal with obsolescence, in which an item’s demand ceases altogether. Several variants have been reported, some of which are unbiased on certain types of demand, but only one recent variant addresses the problem of obsolescence. We describe a...
متن کاملShort-term electricity demand forecasting using double seasonal exponential smoothing
This paper considers univariate online electricity demand forecasting for lead times from a half-hour-ahead to a day-ahead. A time series of demand recorded at half-hourly intervals contains more than one seasonal pattern. A within-day seasonal cycle is apparent from the similarity of the demand profile from one day to the next, and a within-week seasonal cycle is evident when one compares the ...
متن کاملForecasting Intermittent Demand by Markov Chain Model
The inventory control of the products which have intermittent demand is essential for many organizations since these items have a low lead time demand but a high price. Since the intermittent demand pattern is irregular, the estimation of the lead time demand is challenging. A modified Markov chain model (MMCM) has been proposed for modeling and estimating intermittent demand data, motivated by...
متن کاملMethods for Intermittent Demand Forecasting
Intermittent demand or ID (also known as sporadic demand) comes about when a product experiences several periods of zero demand. Often in these situations, when demand occurs it is small, and sometimes highly variable in size. ID is often experienced in industries such as aviation, automotive, defence and manufacturing; it also typically occurs with products nearing the end of their life cycle....
متن کاملForecasting with exponential smoothing methods and bootstrap
The Boot.EXPOS procedure is an algorithm that combines the use of exponential smoothing methods with the bootstrap methodology for obtaining forecasts. In previous works the authors have studied and analyzed the interaction between these two methodologies. The initial sketch of the procedure was developed, modified and evaluated until its final form designated as Boot.EXPOS.
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: International Journal of Forecasting
سال: 2014
ISSN: 0169-2070
DOI: 10.1016/j.ijforecast.2014.01.006