ARIMA models to forecast demand in fresh supply chains. (25th May 2011)

• Record Type: Journal Article
• Authors: Shukla, Manish; Jharkharia, Sanjay
• Is Part Of: International journal of operational research. Volume 11:Number 1(2011)
• Page Start: 1
• Page End: 18
• Publication Date: 2011-05-25
• Subjects: agriculture -- ARIMA models -- autoregressive integrated moving average models -- demand forecasting -- supply chain -- time series; Operations research -- Periodicals; 003.05
• Languages: English
• ISSNs: 1745-7645

Abstract

This paper presents the application of autoregressive integrated moving average (ARIMA) models to forecast the demand of fresh produce (fruits and vegetables) on a daily basis. Models were built using 25 months sales data of onion from Ahmedabad market in India. Results show that the model can be used to forecast the demand with mean absolute percentage error (MAPE) of 43.14%. This error is within the acceptable limit for fruits and vegetable markets with highly fluctuating demand pattern. The model was validated taking sales data for the same commodity from a different vegetable market. The proposed forecasting model can be used to assist the farmers in determining the volume of daily harvesting for fruits and vegetables.