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

Inaki Maulida Hakim, Givanny Permata Sari, Aloysia Elva Ardina

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

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.

Original languageEnglish
Title of host publication2nd International Conference on Science, Mathematics, Environment, and Education
EditorsNurma Yunita Indriyanti, Murni Ramli, Farida Nurhasanah
PublisherAmerican Institute of Physics Inc.
ISBN (Electronic)9780735419452
DOIs
Publication statusPublished - 18 Dec 2019
Event2nd International Conference on Science, Mathematics, Environment, and Education, ICoSMEE 2019 - Surakarta, Indonesia
Duration: 26 Jul 201928 Jul 2019

Publication series

NameAIP Conference Proceedings
Volume2194
ISSN (Print)0094-243X
ISSN (Electronic)1551-7616

Conference

Conference2nd International Conference on Science, Mathematics, Environment, and Education, ICoSMEE 2019
Country/TerritoryIndonesia
CitySurakarta
Period26/07/1928/07/19

Keywords

  • Artificial Neural Network
  • Auto-Regressive Integrated Moving Average
  • demand forecasting
  • Lot-For-Lot
  • Material Requirement Planning
  • Mixed Integer Linear Programming
  • production planning

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