Combinatorial Optimization: finding an optimal solution from a finite set of solutions
Countless practical optimization problems are, in fact, combinatorial optimization problems: they have an optimal solution that needs to be found amongst a finite set of possible solutions. The aim of combinatorial optimization (CO) is to rapidly and efficiently find such an optimal solution.
CO is related to discrete mathematics, theoretical computer science, applied mathematics, operations research, algorithm theory and computational complexity theory and has important applications in several fields. These include scheduling, production planning, logistics, network design, communication and routing in networks, health care, artificial intelligence, machine learning, auction theory, and software engineering.
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Our most recent peer reviewed publications
The sport teams grouping problemAnnals of Operations Research (2019)
Revenue maximization in an optical router node using multiple wavelengths12th EAI International Conference on Performance Evaluation Methodologies and Tools, (VALUETOOLS 2019) (2019)
Asymptotics of symmetry in matroidsJournal of Combinatorial Theory. Series B (2019)
Revealed preference theory: an algorithmic outlookEuropean Journal of Operational Research (2019)
Scheduling a non-professional indoor football leagueAnnals of Operations Research (2019)