Description

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.

 

Video about our collaboration with ProRail (in Dutch)

 

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Vacancies

No vacancies currently.

News

Jie Li and Sophie Huiberts selected to participate in the 7th Heidelberg Laureate Forum

Jie Li and Sophie Huiberts selected to participate in the 7th Heidelberg Laureate Forum

Jie Li from the DIS group and Sophie Huiberts from the N&O group have been selected to participate in the 7th Heidelberg Laureate Forum (HLF). The annual HLF event selects a small group of 200 most qualified Young Researchers worldwide to meet pre-eminent scientists from the fields of mathematics and computer science.

Jie Li and Sophie Huiberts selected to participate in the 7th Heidelberg Laureate Forum - Read More…

Current events

Dutch Seminar on Optimization (online series) with Andreas Wiese (VU Amsterdam)

  • 2022-01-27T16:00:00+01:00
  • 2022-01-27T17:00:00+01:00
January 27 Thursday

Start: 2022-01-27 16:00:00+01:00 End: 2022-01-27 17:00:00+01:00

Online seminar

The Dutch Seminar on Optimization is an initiative to bring together researchers from the Netherlands and beyond, with topics that are centered around Optimization in a broad sense. We would like to invite all researchers, especially also PhD students, who are working on related topics to join the events. 

Speaker: Andreas Wiese (VU Amsterdam) 

Title:

A PTAS for the Unsplittable Flow on a Path problem
(joint work with Fabrizio Grandoni and Tobias Mömke)

Abstract:

In the Unsplittable Flow on a Path problem (UFP) we are given a path with edge capacities, and a set of tasks where each task is characterized by a subpath, a demand, and a weight. The goal is to select a subset of tasks of maximum total weight such that the total demand of the selected tasks using each edge $e$ is at most the capacity of $e$. The problem admits a QPTAS. After a long sequence of improvements, the currently best known polynomial time approximation algorithm for UFP has an approximation ratio of $1+\frac{1}{e+1}+\eps < 1.269$. It has been an open question whether this problem admits a PTAS.
In this talk, we present a polynomial time $(1+\eps)$-approximation algorithm for UFP.

The lecture will be given online. Please visit the website for more information and the zoom link. 

 

Members

Associated Members

Publications

Current projects with external funding

  • Smart Heuristic Problem Optimization ()
  • Mixed-Integer Non-Linear Optimisation Applications (MINOA)
  • New frontiers in numerical nonlinear algebra (None)
  • Optimization for and with Machine Learning (OPTIMAL)
  • Polynomial Optimization, Efficiency through Moments and Algebra (POEMA)
  • Towards a Quantitative Theory of Integer Programming (QIP)

Related partners

  • Alma Mater Studiorum-Universita di Bologna
  • Alpen-Adria-Universität Klagenfurt
  • CNR Pisa
  • CNRS
  • Dassault Systèmes B.V.
  • IBM
  • INRIA
  • Rheinische Friedrich-Wilhelmus Universitaet Bonn
  • Technische Universität Dortmund
  • Tilburg University
  • Tromsø, Norway
  • Universita degli Studi di Firenze
  • Universität Konstanz
  • University of Birmingham
  • Universiteit van Tilburg