Combinatorial Optimisation

This stream aims to bring researchers, practitioners, and experts in the field of combinatorial optimisations to exchange ideas, showcase their latest research, discuss challenges, explore new opportunities in the field, and foster collaborations. 

Combinatorial optimisation has been a major research area in OR for more than 50 years. Combinatorial optimisation problems are important due to their wide range of real-world applications, the complexity of decision-making, the need for effective management and decision support, the potential for innovation and advancements, and their relevance to sustainability-related challenges.  

This stream focuses on advances in modelling approaches to solve combinatorial optimisation problems, including exact algorithms, heuristics and metaheuristics. The problems addressed can range from classical problems, such as scheduling, travelling salesman problem, vehicle routing problems, facility location, Steiner trees, set covering, maximum clique, cutting and packing, to more applications areas such as machine learning, cybersecurity, healthcare, smart cities and computational biology.


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Thu Dang, Lancaster University

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Burak Boyaci, Lancaster University