Combinatorial Optimization

  • PO Box 513, Department of Mathematics and Computer Science

    5600 MB Eindhoven


  • Groene Loper 5, MetaForum

    5612 AP Eindhoven



Introductie / missie

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

Over de organisatie

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

The aim of combinatorial optimization (CO) is to rapidly and efficiently find such an optimal solution.

Vingerafdruk Duik in de onderzoeksthema's waar Combinatorial Optimization actief is. Deze onderwerplabels komen voort uit het werk van deze leden van de organisatie. Samen vormen ze een unieke vingerafdruk.

Matroid Rekenkunde
Approximation algorithms Engineering en materiaalwetenschappen
Polynomials Engineering en materiaalwetenschappen
Graph in graph theory Rekenkunde
Scheduling Engineering en materiaalwetenschappen
Coloring Engineering en materiaalwetenschappen
Approximation Algorithms Rekenkunde
Exponential time Rekenkunde

Netwerk Recente externe samenwerking op landenniveau. Duik in de details door op de stippen te klikken.

Onderzoeksoutput 1988 2020

44 Downloads (Pure)

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 blz., 104866.

Onderzoeksoutput: Bijdrage aan tijdschriftTijdschriftartikelAcademicpeer review

Classification Tree
Column Generation
Decision trees
Linear programming
Integer Linear Programming

Practical Combinatorial Optimization

Spieksma, F. C. R., 21 feb 2020, (Geaccepteerd/In druk) Eindhoven: Technische Universiteit Eindhoven.

Onderzoeksoutput: Boek/rapportInaugurale redeProfessioneel

2 Citaties (Scopus)

The transportation problem with conflicts

Ficker, A. M. C., Spieksma, F. C. R. & Woeginger, G. J., 2020, In : Annals of Operations Research.

Onderzoeksoutput: Bijdrage aan tijdschriftTijdschriftartikelAcademicpeer review

Transportation problem
Approximation algorithms


Algorithms for coping with uncertainty and intractability

N. Bansal (Ontvanger), 2013

Prijs: ERCConsolidatorWetenschappelijk

Combinatorial optimization
Approximation algorithms
Computer science
Optimum design

Faster algorithms in computer science

Jesper Nederlof (Ontvanger), 2019

Prijs: ERCStartingWetenschappelijk

Computer science
Computational complexity

NWO Vici Award : Continuous Methods in Discrete Optimization

N. Bansal (Ontvanger), 2018

Prijs: NWOViciWetenschappelijk

Discrete Optimization
Computer Science
Stable Polynomials


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

Auteur: Reusken, E., 28 okt 2019

Begeleider: Buchin, K. A. (Afstudeerdocent 1), Spieksma, F. C. (Afstudeerdocent 2), Kowalczyk, D. (Afstudeerdocent 2), van de Ven, M. (Externe persoon) (Externe coach) & de Wit, L. (Externe persoon) (Externe coach)

Scriptie/masterproef: Master

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

Auteur: Blom, D. A., 31 aug 2017

Begeleider: Pendavingh, R. (Afstudeerdocent 1)

Scriptie/masterproef: Bachelor


Automated typesetting: the mathematics of beautiful texts

Auteur: Roordink, J., 15 aug 2019

Begeleider: Hurkens, C. (Afstudeerdocent 1)

Scriptie/masterproef: Bachelor