Analysis of controlling reducing bunker cost in shipping transportation : bunkering port call optimisation (Part 1)

• Main Authors: Yang, Cen, Shen, Nan, Tang, Xingyan
• Other Authors: Chew Ah Seng, David
• Format: Final Year Project
• Language: English
• Published: 2009
• Subjects: DRNTU::Engineering::Maritime studies::Maritime management and business
• Online Access: http://hdl.handle.net/10356/15861
• Institution: Nanyang Technological University

The project aims to develop a basic decision making tool to help operations managers to manage and reduce bunkering-related costs when planning each voyage. To be more specific, the purpose is to find out which ports to bunker at when the itinerary is being planned and how much bunker to take up at each port, in order to achieve the lowest daily costs related to bunkering. That should be most cost-effective way of bunkering. After introduction and literature review, this project would first give some background information, regarding the importance of bunker cost management, factors determining bunker fuel prices, and bunker price differentials. All these would enhance the appreciation of how essential it is to choose which ports to bunker at. Then, a very essential task is to select the typical routes commonly taken up by both bulk carriers and tankers based on certain criteria. One route would be selected from each of the six indices contained in the Baltic Exchange Indices. Third, linear programming is applied to set up a formula to calculate the minimum daily bunkering-related costs. The inputs or independent variables include but not limited to bunker prices at different bunkering ports, bunkering port call expenses, turnaround time, and canal transit tolls if needed. The decision variables are the optimal quantities of IFO and MDO to be lifted at the selected bunkering ports. Next, an essential task is to collect information regarding the prices of bunker at different major bunkering ports, canal transit tariffs, and other relevant data. The fifth step is to substitute the information collected in the fourth step for the variables in the formula to run the linear programming one by one for the six routes. This would produce the most cost-effective bunkering ports on each route. Further, factors other than costs would be explored in order for operators to make a well-grounded decision regarding bunkering port selection. Lastly, some additional issues would be discussed. BIMCO website would be used to research into the standard and clearly-worded formats of Bunker Escalation Clause and Bunker Deviation Clause.