Networks and Optimization

Developing algorithmic methods to tackle complex optimization problems by combining techniques from mathematics and computer science, with applications in planning, scheduling and routing.

The leader of the group Networks and Optimization: Daniel Dadush

In today’s society, complex systems surround us. From transport and traffic, to behavioral economics and operations management, real-world applications often demand that we identify simple, optimal solutions among a huge set of possibilities. Our research group Networks and Optimization (N&O) does fundamental research to tackle such challenging optimization problems. 

We develop algorithmic methods to solve complex optimization problems efficiently. Our research provides efficient algorithms to some of the most challenging problems, for example, in planning, scheduling and routing. To come up with the best optimization algorithms, we combine and extend techniques from different disciplines in mathematics and computer science. 

N&O covers a broad spectrum of optimization aspects. Our expertise ranges from discrete to continuous optimization and applies to centralized and decentralized settings. We focus on both problem-specific methods and universal toolkits to solve different types of optimization problems. The key in our investigations is to understand and exploit combinatorial structures, such as graphs, networks, lattices and matroids. Our research is of high scientific impact and contributes to various fields.

In several cooperations with industry partners, the algorithmic techniques that we develop in our group have proven useful to solve complex real-world problems. We are always interested in new algorithmic challenges arising in real-world applications and are open to new cooperations.

Watch our group video to get a glimpse of our activities or read more information on the Networks and Optimization research group.

CWI's Network and Optimization research group video.

Video about our collaboration with ProRail (in Dutch)

Publications

All publications

Current projects with external funding

  • Smart Heuristic Problem Optimization
  • Algorithms for PAngenome Computational Analysis (ALPACA)
  • Constance van Eeden Fellowship (Constance van Eeden)
  • Mixed-Integer Non-Linear Optimisation Applications (MINOA)
  • Networks (Networks)
  • Networks COFUND postdocs (Networks COFUND postdocs)
  • New frontiers in numerical nonlinear algebra (None)
  • Optimization for and with Machine Learning (OPTIMAL)
  • Optimization for and with Machine Learning (OPTIMAL2)
  • Pan-genome Graph Algorithms and Data Integration (PANGAIA)
  • Polynomial Optimization, Efficiency through Moments and Algebra (POEMA)
  • Towards a Quantitative Theory of Integer Programming (QIP)