Open AccessA design of bi-objective optimization model palm refinery export supply chain network: a case study in Indonesia
Author(s) -
Mariani Sembiring,
Saut Sejati Hutapea,
Mohammadi Hadi,
Dini Wahyuni
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/801/1/012112
Subject(s) - refinery , palm oil , refining (metallurgy) , palm stearin , oil refinery , supply chain , profit (economics) , computer science , distribution (mathematics) , business , engineering , environmental science , economics , mathematics , marketing , waste management , agroforestry , chemistry , microeconomics , mathematical analysis
One of the important elements influencing the export development of these products is the export distribution network produced by refining palm oil. The challenge of export distribution of palm oil refining products to generate maximum profit with minimum distribution costs, among others, is high transportation costs, distant transportation / logistics destinations, variations in product types and allocation of the number of products that must be distributed to consumers (foreign markets). The purpose of this study is to maximize profits and minimize distribution costs from the export distribution network of Indonesian palm oil refining products. Multiple goal optimization model (multi objective optimization) with the completion of soft-computing techniques is needed to solve this problem in order to get optimum results with a short solution search time. The NSGA-II algorithm (non dominated sorting algorithm II) was chosen in the completion of the existing optimization model because of the characteristics of the distribution network of export products resulting from complex refining of palm oil. The scenario used for testing the optimization model is by using a system entity consisting of three types of Indonesian palm oil refining products (Stearin RBD, Olein and PFAD RBD).