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Workshop

Workshop on Metaheuristics

Workshop Metaheuristics
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UiB

Hovedinnhold

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 - 09:30Registration and Welcome 
09:30 - 10:30The backpacker's guide to metaheuristicsKenneth Sörensen
10:30 - 10:45Short break 
10:45 - 11:45Diversification, Intensification, and Adaptive Large Neighborhood SearchLars Magnus Hvattum
11:45 - 12:30Lunch 

12:30 - 13:30

Competition 
13:30 - 14:30Deep Reinforcement Learning Hyperheuristic (DRLH)Jakob Kallestad
14:30 - 14:45Short break 
14:45 - 15:45DRLH for Truck and Drone Last Mile Delivery ProblemVegard Birkenes
15:45 - 16:00Closing 

 

The invited speakers

Kenneth Sörensen

Kenneth Sörensen
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Private
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
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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
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private
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
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private
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.