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.
Meet some of our Researchers
Afrouz Jabal Ameli
Our most recent peer reviewed publications
Solving Large-Scale Dynamic Vehicle Routing Problems with Stochastic RequestsEuropean Journal of Operational Research (2023)
Computational aspects of relaxation complexity: possibilities and limitationsMathematical Programming (2023)
An infinite class of Neumaier graphs and non-existence resultsJournal of Combinatorial Theory, Series A (2023)
Filling a Theater During the COVID-19 PandemicINFORMS Journal on Applied Analytics (2022)
In memoriam Gerhard WoegingerJournal of Scheduling (2022)