Combinatorial Optimization

  • PO Box 513, Department of Mathematics and Computer Science

    5600 MB Eindhoven

    Netherlands

  • Groene Loper 5, MetaForum

    5612 AP Eindhoven

    Netherlands

Organization profile

Introduction / mission

The Combinatorial Optimization group investigates the structure and relationship between different problems, in order to design efficient and effective algorithms for solving them.

Highlighted phrase

Combinatorial Optimization: finding an optimal solution from a finite set of solutions

Organisational profile

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.

The Combinatorial Optimization (CO) group at Eindhoven University of Technology (TU/e) focuses on the analysis and solution of discrete algorithmic problems that are computationally difficult. The group investigates the structure of such problems, analyzes the relations between different problems, and uses this knowledge to design efficient and effective algorithms for solving them. We study both exact and heuristic algorithms. The Group is also interested in combinatorial optimization problems where the input is revealed only gradually, or where there is uncertainty in the parameters, leading to online, stochastic or robust solution methods.

Combinatorial Optimization develops theoretic results, for instance in graph theory and matroids, and apply these to real-world situations. Typical application areas are scheduling, production planning, logistics, network design, communication and routing in networks, and health care. The Group cooperates with KU Leuven, CWI (National Research Institute for Mathematics and Computer Science) and DIAMANT (Discrete, Interactive and Algorithmic Mathematics, Algebra and Number Theory, Dutch mathematics cluster).

Research focuses on:

  • polyhedral techniques
  • local search methods
  • performance guarantee for approximation algorithms
  • online route planning
  • scheduling
  • matroid structure and visualization
  • network problems

Fingerprint Dive into the research topics where Combinatorial Optimization is active. These topic labels come from the works of this organisation's members. Together they form a unique fingerprint.

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    Research Output

    Column generation based heuristic for learning classification trees

    Firat, M., Crognier, G., Gabor, A. F., Hurkens, C. A. J. & Zhang, Y., Apr 2020, In : Computers & Operations Research. 116, 11 p., 104866.

    Research output: Contribution to journalArticleAcademicpeer-review

  • 49 Downloads (Pure)

    Practical combinatorial optimization

    Spieksma, F. C. R., 21 Feb 2020, Eindhoven: Technische Universiteit Eindhoven. 28 p.

    Research output: Book/ReportInaugural speechProfessional

    Open Access
    File

    The multi-league sports scheduling problem, or how to schedule thousands of matches

    Davari, M., Goossens, D., Beliën, J., Lambers, R. & Spieksma, F. C. R., Mar 2020, In : Operations Research Letters. 48, 2, p. 180-187 8 p.

    Research output: Contribution to journalArticleAcademicpeer-review

  • Prizes

    Algorithms for coping with uncertainty and intractability

    N. Bansal (Recipient), 2013

    Prize: ERCConsolidatorScientific

  • Faster algorithms in computer science

    Jesper Nederlof (Recipient), 2019

    Prize: ERCStartingScientific

  • NWO Vici Award : Continuous Methods in Discrete Optimization

    N. Bansal (Recipient), 2018

    Prize: NWOViciScientific

  • Student theses

    Algorithms for parallel machine scheduling with a sequence dependent cost function: application in a printed circuit board assembly production environment

    Author: Reusken, E., 28 Oct 2019

    Supervisor: Buchin, K. A. (Supervisor 1), Spieksma, F. C. (Supervisor 2), Kowalczyk, D. (Supervisor 2), van de Ven, M. (External person) (External coach) & de Wit, L. (External person) (External coach)

    Student thesis: Master

    Analysis of an algorithm for finding perfect matching in k-regular bipartite graphs

    Author: Blom, D. A., 31 Aug 2017

    Supervisor: Pendavingh, R. (Supervisor 1)

    Student thesis: Bachelor

    File

    Automated typesetting: the mathematics of beautiful texts

    Author: Roordink, J., 15 Aug 2019

    Supervisor: Hurkens, C. (Supervisor 1)

    Student thesis: Bachelor

    File