Purpose – The purpose of this paper is to describe a real-world system developed for a large food distribution company which requires forecasting demand for thousands of products across multiple warehouses. The number of different time series that the system must model and predict is on the order of 105. The study details the system's forecasting algorithm which efficiently handles several difficult requirements including the prediction of multiple time series, the need for a continuously self-updating model, and the desire to automatically identify and analyze various time series characteristics such as seasonal spikes and unprecedented events. Design/methodology/approach – The forecasting algorithm makes use of a hybrid model consisting o...
Demand forecasting is a crucial part of managing any supply chain network, since inaccurate forecast...
Nowadays artificial intelligence algorithms are capable to achieve impressive results with a reduce...
Intermittent time series forecasting is a challenging task which still needs particular attention of...
In most business forecasting applications, the decision-making need we have directs the frequency of...
We develop and exemplify application of new classes of dynamic models for time series of nonnegative...
Forecasting is one of the important tools in business environment because it assists in decision-mak...
Demand forecasting has been studied extensively because it serves as an input to other decision proc...
Time series forecasting plays an increasingly important role in modern business decisions. In today'...
Product forecasting is a critical function in the rapid turnover of goods and products through retai...
This paper reports the analysis of a forecasting problem based on time series. It is noted that the ...
This paper reports the analysis of a forecasting problem based on time series. It is noted that the ...
A new approach is proposed for forecasting a time series with multiple seasonal patterns. A state sp...
Forecasting demand is challenging. Various products exhibit different demand patterns. While demand ...
Part 12: Data Mining-ForecastingInternational audienceThe developed forecasting algorithm creates tr...
This paper reports the analysis of a forecasting problem based on time series. It is noted that the...
Demand forecasting is a crucial part of managing any supply chain network, since inaccurate forecast...
Nowadays artificial intelligence algorithms are capable to achieve impressive results with a reduce...
Intermittent time series forecasting is a challenging task which still needs particular attention of...
In most business forecasting applications, the decision-making need we have directs the frequency of...
We develop and exemplify application of new classes of dynamic models for time series of nonnegative...
Forecasting is one of the important tools in business environment because it assists in decision-mak...
Demand forecasting has been studied extensively because it serves as an input to other decision proc...
Time series forecasting plays an increasingly important role in modern business decisions. In today'...
Product forecasting is a critical function in the rapid turnover of goods and products through retai...
This paper reports the analysis of a forecasting problem based on time series. It is noted that the ...
This paper reports the analysis of a forecasting problem based on time series. It is noted that the ...
A new approach is proposed for forecasting a time series with multiple seasonal patterns. A state sp...
Forecasting demand is challenging. Various products exhibit different demand patterns. While demand ...
Part 12: Data Mining-ForecastingInternational audienceThe developed forecasting algorithm creates tr...
This paper reports the analysis of a forecasting problem based on time series. It is noted that the...
Demand forecasting is a crucial part of managing any supply chain network, since inaccurate forecast...
Nowadays artificial intelligence algorithms are capable to achieve impressive results with a reduce...
Intermittent time series forecasting is a challenging task which still needs particular attention of...