Abstract— The objective in this research is to study of the decision support system for customer demand forecasting and inventory management of perishable goods. In the present, the company is very competitive. Many companies try to save the cost of production. In addition, the inventory management is important to decrease the cost too. There are many spoiled food businesses in Thailand. Because of Thailand is an agricultural country. The forecasting model is created to apply in planning the quantity of goods to the warehouse for the lowest volume of storage. A wholesale and retail sale of pork chop at Bungkan province is tested in this research. The training sets are the volumes of pork chop in the past 350 days for the forecasting model. The experiment results found that the single exponential smoothing algorithm is higher than the adaptive-response-rate single exponential smoothing algorithm and the Holt’s two-parameter linear exponential smoothing algorithm. Then the single exponential smoothing algorithm is selected to create the decision support system for customer demand forecasting and inventory management of perishable goods (DSS_DF&IM) model. In addition, this model can make profit more than the old system that this model gives equal 120,320 Baht while the old system is 99,950 Baht. Moreover, the DSS_DF&IM model can decrease inventory balance more than the old system that is 224 kilograms.

Index Terms— Electronic file, instructions, preparing paper , template

Cite: Prapai Sridama and Chopaka Siribut, "Decision Support System for Customer Demand Forecasting and Inventory Management of Perishable Goods" Journal of Advanced Management Science, Vol. 6, No. 1, pp. 8-12, March 2018. doi: 10.18178/joams.6.1.8-12