Combinatorial Optimisation

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

Combinatorial optimisation is concerned with finding optimal solutions within discrete and very-large domains, and has been a major research area in OR for more than 50 years. Combinatorial optimisation problems are extremely important due to their wide range of real-world applications, the complexity of decision-making, the need for effective management and efficient resource allocation, the potential for innovation and advancements, and their relevance to sustainability-related challenges.

Most of the combinatorial optimisation problems belong to the class of NP-hard problems, and often require the development of tailored solution methods to cope with very high computational complexity.
Contributions in this stream will focus on advances in modelling approaches and solution techniques to tackle efficiently combinatorial optimisation problems, including exact algorithms, metaheuristics and matheuristics. The problems addressed will range from classical problems, such as knapsack, optimisation on graphs and network flows, facility location, scheduling, travelling salesman problem, vehicle routing problems, Steiner trees, set covering, maximum clique, cutting and packing, to more application-oriented combinatorial challenges, including in machine learning, cybersecurity, healthcare, smart-cities and computational biology.

The stream will also welcome contributions showcasing new applications of already known combinatorial optimisation problems.


Antonino Sgalambro

Antonino Sgalambro, Leeds University Business School