Role of hybrid forecasting techniques for transportation planning of broiler meat under uncertain demand in thailand

摘要

One of numerous problems experiencing in supply chain management is the demand. Most demands areappeared in terms of uncertainty. The broiler meat industry is inevitably encountering the same problem. In thisresearch, hybrid forecasting model of ARIMA and Support Vector Machine (SVMs) are developed to forecastbroiler meat export. In addition, ARIMA, SVMs, and Moving Average (MA) are chosen for comparing theforecasting efficiency. All the forecasting models are tested and validated using the data of Brazil’s export,Canada’s export, and Thailand’s export. The hybrid model provides accuracy of the forecasted values that are98.71%, 97.50%, and 93.01%, respectively. In addition, the hybrid model presents the least error of all MAE,RMSE, and MAPE comparing with other forecasting models. As forecasted data are applied to transportationplanning, the mean absolute percentage error (MAPE) of optimal value of forecasted value and actual value is14.53%. The hybrid forecasting model shows an ability to reduce risk of total cost of transportation when broilermeat export is forecasted by using MA(2), MA(3), ARIMA, and SVM are 50.59%, 60.18%, 68.01%, and 46.55%,respectively. The results indicate that the developed forecasting model is recommended to broiler meatindustries’ supply chain decision.