Center of Data Science, Energy Informatics and Optimization group at the Department of Informatics join forces to host an exciting event starting in January 2026, leading up to a Workshop with a final competition on 10 February in 2026.
The workshop
The worskshop will be in Nygårdsgaten 5, Bergen. Registration for the Workshop is open.
Program
09:00 - 09:30 | Registration and Welcome | |
09:30 - 10:30 | The backpacker's guide to metaheuristics | Kenneth Sörensen | |
10:30 - 10:45 | Short break | |
10:45 - 11:45 | Diversification, Intensification, and Adaptive Large Neighborhood Search | Lars Magnus Hvattum | |
11:45 - 12:30 | Lunch | |
12:30 - 13:30 | Competition | |
13:30 - 14:30 | Deep Reinforcement Learning Hyperheuristic (DRLH) | Jakob Kallestad | |
14:30 - 14:45 | Short break | |
14:45 - 15:45 | DRLH for Truck and Drone Last Mile Delivery Problem | Vegard Birkenes | |
15:45 - 16:00 | Closing | |
The invited speakers
Kenneth Sörensen
is a Professor at the University of Antwerp, where he leads the ANT/OR operations research group and is recognized as a world-leading expert in the application and development of advanced optimization methods, particularly metaheuristics. He has published influential research on the foundations and scientific principles of metaheuristics, including the widely cited “Metaheuristics — the metaphor exposed” and historical surveys of the field. Beyond his research, Sörensen has played a central role in building the global metaheuristics community: he was a founder and is a long-time coordinator of EU/ME, the EURO Working Group on Metaheuristics, the largest international platform for researchers in metaheuristic optimization, and contributes actively through editorial and organizational leadership in the field.
Lars Magnus Hvattum
Lars Magnus Hvattum is Professor of Quantitative Logistics at Molde University College and an internationally recognized expert in combinatorial optimization, metaheuristics, and logistics planning. His research has made influential contributions to the design, analysis, and empirical evaluation of metaheuristic algorithms, particularly for adaptive large neighborhood search. Hvattum is widely known for his rigorous, data-driven approach to understanding metaheuristic performance and for bridging methodological insight with practical decision support in transportation and logistics. He is an active and respected member of the international metaheuristics community, contributing through highly cited publications, long-standing collaborations, and sustained involvement in leading conferences and research initiatives in optimization.
Jakob Kallestad
Jakob Kallestad is a data scientist at Equinor working with applied AI across machine learning, generative AI, and AI agents. His work centers on taking AI solutions from concept to production, as well as helping shape the direction of the company’s AI strategy. He holds a master’s degree in machine learning, focused on bridging reinforcement learning and combinatorial optimization through metaheuristic approaches.
Vegard Birkenes
Vegard Birkenes holds a Master’s degree in Machine Learning from the University of Bergen, where his thesis focused on the truck–drone optimization problem, comparing a metaheuristic algorithm with a machine learning approach. He currently works as a developer at Itera, with a focus on backend development and generative AI.
