DETERMINATION OF CRUDE OIL CARRIER SHIP ASSIGNMENT METHOD ON PT XYZ USING MIXED INTEGER LINEAR PROGRAMMING

• Main Author: RIFKY NOVANDI NIM 13414011 , MUHAMMAD
• Format: Final Project
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/29330
• Institution: Institut Teknologi Bandung

One of the most critical activities in a companies are the transportation system that occur in that company. Better analysis of this activity gives rise to better use of a system's resources, as well as control of the entire supply chain. This study aims to help PT XYZ as the oil company in Indonesia that is needs to schedule and optimize their transportation systems which are based on shipping. The research deals with a tankers scheduling problem of specialized vessels carrying crude oil products. In this study, the problem, that is tried to solve, is providing cost minimization in transporting the different characterized cargoes to determined ports by the ship fleets which contain different kind of ships. <br /> <br /> The problem consists of determining the set of cargoes in possibly routes that should be served by each vessel, the arrival, departure, and waiting times at each port, while minimizing total costs. A heterogeneous fleet transports the products from several loading ports to several discharging ports. Time windows are involved on the freight of vessel. Demand may be delivered by more than one vessel. The tankers scheduling problem is formulated as a mixed integer linear programming problem. It includes information and constraints about the demand, but also about the vessels, the vessel routes, and the ports and their restrictions. <br /> <br /> The reference model used in solving the problem is the Karaoglan Model (2007). In this study, the reference model was developed into a model to better suit the state of the system. Data processing with the model is done by using software LINGO 11. This is from a real-life problem with 22 vessels, 37 cargoes with 8 delivery destinations, and total demand load of 9340.44 milion barrels (MB). The optimal solution obtained by MILP solution model shows an improvement of 19% over company’s existing result. The results have shown that, the presented model that is refered from the literature, can be applied successfully in real word and gives nearly optimal solutions.