OPTIMIZATION OF OPERATIONAL COST OF NATIONAL FUEL OIL (BBM) DOWNSTREAM SUPPLY CHAIN NETWORK USING LINEAR PROGRAMMING APPROACH

• Main Author: Krisna, Cakrawala
• Format: Final Project
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/84096
• Institution: Institut Teknologi Bandung

Fuel oil is the most significant energy sources in Indonesia. In 2022, fuel oil dominated the total energy consumption by more than 477,82 barrel of oil equivalent (BOE). On the other hand, Indonesia’s fuel oil consumption has also experienced a positive trend over the past few years. The vast majority of fuel oil products is produced by PT X—a state-owned Indonesian oil & gas company that produces and sells various type of oil and gas products with 84.99% market share in Indonesia. The government of Indonesia has given a mandate that require PT X to comply the guaranteed availability of certain types of fuel in the country. Given the fact that PT X has 6 refinery units, 119 TBBMs, and more than 14296 customers (fuel station), PT X’s supply chain network is considered as one of the most complex supply chain network in the world. At the present, PT X’s supply chain network is not optimized due to high logistics cost that are caused by overcapacity of fuel oil jetties and inoptimal supply chain network configuration. Therefore, optimization of PT X’s supply chain network is needed to minimize the total downstream supply chain cost (supply, handling & storage, and distribution) and meet all demand from all customers. This research uses linear programming to optimize PT X’s national downstream supply chain network by minimizing the total supply, handling & storage, and distribution cost. The model decides the amount of fuel oil products supplied and distributed and the mode of transportation used to supply & distribute the products. The decision level of this research is focused on the tactical level. The solution is obtained by using Python programming language supported by PuLP library. This research will give an optimal cost for PT X’s fuel oil downstream supply chain network by minimizing the total cost per liter by 29.85% (547,872,056 USD).