| Name of speakers | Mabel C. Chou, Sun Qinghe, Li Wei |
| Schedule | 6 October 2023, 10am – 11.30am |
| Venue | Hon Sui Sen Memorial Library, Seminar Room 4-7 |
| Zoom link | https://nus-sg.zoom.us/meeting/register/tZAlcu2pqzkvHNA_ldzyBArQnujX1H_xk8Tr |
| Title of talk | Data driven bunker procurement planning: working with the maritime industry |
| Abstract | In this presentation, we will recount our journey collaborating with the maritime industry, discussing the challenges we encountered and elucidating how we transformed these challenges into gratifying experiences and impactful contributions. We will use our work on bunker procurement decisions with a global container shipping company as an example to illustrate the impact we made and the lessons we learned.
Bunker refueling decisions in international shipping are crucial operational choices. Each ship acts like a movable storage unit navigating through diverse markets, procuring bunker fuels from different ports to sustain its voyage. This involves grappling with challenges posed by varying bunker fuel prices over time and locations. To tackle this challenge, we propose data-driven structure-prescriptive (SP) approaches that combine the strengths of modern machine learning with the insights from traditional OR modeling and optimization. Instead of predicting future marine fuel prices, our approach directly learns the optimal refueling policy from data and adapts refueling decisions to the current market conditions, including fuel prices, crude oil price, NYSE index, etc. Our focus lies in leveraging the well-established understanding that the optimal refueling decision adheres to a state-dependent base-stock refueling policy. This decision depends on factors such as the port of call, fuel tank capacity, market conditions, and is finite-valued, depending on the vessel’s schedule and voyage. We provide a practical framework to incorporate these structural properties into data-driven decision-making for bunker refueling operations. The proposed SP approaches successfully recovered the “true” optimal refueling policy in synthetic simulations. Moreover, our experiments unveiled that incorporating more structural properties into the learning process significantly improved the out-of-sample (OOS) performance. In the case study, we compared our proposed SP approach with the firm’s existing operation, resulting in a noteworthy reduction of fuel expenses, which amounts to approximately 2.52 million USD per year in savings for a fleet of six ships. In addition, to facilitate our collaboration with industry, we propose an eXplainable multi-stage bunker procurement planning (X-BPP) framework for the maritime industry. In this presentation, we will showcase this framework, discuss its performance, and share the lessons we learn in implementing the system. |
| About the speakers | Mabel C. Chou is an associate professor in the Analytics and Operations department at National University of Singapore (NUS). She received the B.Sc. degree in mathematics from National Taiwan University, the M.Sc. degree in mathematics and Ph.D. degree in industrial engineering and management sciences from Northwestern University. Her research focuses on production scheduling and supply chain analysis. Her current research interest is in the application of optimization tools and business analytics for engineering, service, and supply chain management problems. She is an associate editor for Operations Research, a senior editor for Production and Operations Management and an associate editor for Pacific Journal of Optimization. She has also consulted for companies such as GSK, Caterpillar, P&G, SIA Engineering Company, National University Hospital, Tan Tock Seng Hospital, Lenovo, Supreme Components International, etc.
Sun Qinghe is an Assistant Professor at the Department of Logistics and Maritime Studies (LMS), PolyU Business School. Her research combines data with optimization to provide insights into risk management within supply chain systems, particularly within the maritime logistics sector. Qinghe received her Ph.D. in Operations Research from the National University of Singapore (NUS) in 2022, jointly advised by Mabel Chou and Qiang Meng, and her B.Sc. in Maritime Studies from Nanyang Technological University (NTU), Singapore. Li Wei is a Research Fellow at the National University of Singapore’s Institute of Operations Research and Analytics, jointly advised by Mabel C. Chou and Chen Ying. He has a broad interest in model development for Financial Forecasting-related problems and his research is often motivated by industry initiatives. He obtained his Ph.D. in Computational Finance from the Norwegian University of Science and Technology before joining NUS. |
