Algorithms are an essential part of modern systems in science, industry, and society. We aim at designing and analyzing algorithms for problems from various contexts. It is not only important that an algorithm is correct – it also needs to be efficient, e.g., use (as) little (as possible) running time, a sufficiently small amount of computer memory, etc. Complexity theoretic techniques help to determine the efficiency that can be obtained.
Algorithms and Complexity
Our research ranges from applied research providing innovative algorithmic solutions for problems from different application contexts, including planning for industrial and societal applications. Moreover, we we aim to push and explore by fundamental studies the limits of efficient computation. Our current main research areas are:
- Algorithmic modelling and optimization, e.g., combinatorial optimization, planning, scheduling, advanced integer linear programming techniques
- Robust combinatorial optimization and simulation
- Graph and network algorithms, including the use of tree structures (e.g., treewidth), network applications
- Computational complexity, e.g., fixed parameter tractability and complexity, kernelization, exact algorithms
The Algorithms and Complexity group welcomes collaborations for joint research projects for studies with an algorithmic component, e.g., in logistics, public transportation, energy systems, network analysis. The group is associated to the focus area Complex Systems Studies of Utrecht University, and to the research school IPA ( Institute for Programming research and Algorithmics).