Development mathematics model production planning of urea fertilizer to minimize production cost with mixed integer linear programming (MILP)

• Main Authors: Hakim, Inaki Maulida, Sari, Givanny Permata, Ardina, Aloysia Elva
• Format: Conference Proceeding
• Language: English
• Subjects: Artificial neural networks; Demand; Economic forecasting; Fertilizers; Food; Integer programming; Linear programming; Material requirements planning; Mixed integer; Production costs; Production planning; Ureas
• ISSN: 0094-243X; 1551-7616
• DOI: 10.1063/1.5139768

Food is a necessity that must be met at all times. As it is known that fertilizer is one of the main factors in the success of food security in Indonesia. Currently, the government is targeting food self-sufficiency in 2017 that requires harvesting capability at least twice a year in the area of paddy fields in Indonesia. To meet the fertilizer needs in Indonesia, the whole fertilizer industry must continue to improve its production. In the fertilizer industry studied, there is a problem in the production section, where the industry is not able to meet the demand for urea fertilizer which in fact is the industry’s flagship product. The inability to meet this demand resulted in insufficient revenue to be achieved. In this research, urea fertilizer production planning with Material Requirement Planning (MRP) method, Mixed Integer Linear Programming (MILP), and forecasting is planned. The results of this study indicate that the appropriate MRP method to be used as production planning in the fertilizer industry is Lot-For-Lot (LFL) and the most accurate demand forecasting method and according to the demand trend of urea is Artificial Neural Network (ANN). Furthermore, the total cost that is spent by the fertilizer industry is decreasing into Rp. 55.334.120,- or decreased by 5,15% from the previous one.