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Dagstuhl Seminar 16081


( Feb 21 – Feb 26, 2016 )

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Scheduling is concerned with the allocation of scarce resources in order to best achieve some objective. The specific scarce resources, as well as the particular objectives to be optimized, differ from application to application, but typically involve assigning some type of job to a machine over time. The mathematical study of scheduling dates back to at least the 1950s, when operations research researchers studied problems related to managing activities in a factory. In this context, the scarce resources are typically machines used in the manufacturing process, and the jobs are the products. Computer systems researchers started studying scheduling in the 1960s during the development of operating systems. In this context the resources are mainly computer and network components, such as CPUs, memory, I/O devices, and communication links, whereas the jobs as programs that need to be run. Today, scheduling is intensively studied within the disciplines of mathematical programming and operations research, algorithmics and theoretical computer science. Scheduling continues to evolve as an active discipline, both expanding the scope of modeling, and broadening and deepening the techniques used to solve problems. An example of the former is that energy-related issues have recently been incorporated into many scheduling models, and an example of the latter is that scheduling has both used and contributed to some of the most important developments in approximation and online algorithms.

This is the fourth in a series of Dagstuhl Seminars on the topic of “Scheduling.” It aims to bring together leading experts and promising young researchers in the area of scheduling for presenting and discussing recent results, relevant new models and research trends. A major objective is to discuss important open problems, debate and explore future research directions, and foster new collaborations. The organization of the workshop will reflect these goals, with time devoted to longer, “tutorial-style” lectures, and sufficient unstructured time to allow serious research discussions to take place.

A particular focus of this seminar will lie on interactions between the mathematics and the application areas, both in academia and industry. Selected experts from related communities such as real-time scheduling, stochastic scheduling, supply-chains as well as research-oriented people from industry will contribute practice-relevant research questions.


This fourth meeting in a series of Dagstuhl "Scheduling" seminars had two major objectives. Firstly, it offered a forum for presenting recent scheduling results of high impact and new techniques which may be useful for solving important and long-standing open problems. The second major objective was to debate and explore future research directions, discuss important open problems, and foster new collaborations with a particular attention to interactions with application areas, both in academia and industry.

The organization of the meeting differed from the previous Dagstuhl "Scheduling" seminars by not inviting a different community to interact. Despite (or perhaps because of) the success of the cross-discipline events, there was an explicit desire to dedicate a seminar explicitly to recent advances and new research trends within the algorithmics/math programming scheduling community. This setting allowed for very high technical level talks and deep discussions on recent scheduling results, new techniques, and discussions on important open problems. The program included 15 invited main talks, 10 short spot-light talks, open problem sessions in the beginning of the week, and ample unstructured time for research and interaction. The overall atmosphere among the 45 participants was very interactive and oriented towards solving problems (also initiated by the few well-chosen application-driven talks) within new collaborations.

Copyright Nikhil Bansal, Nicole Megow, and Clifford Stein

  • Fidaa Abed (TU München, DE) [dblp]
  • Susanne Albers (TU München, DE) [dblp]
  • Antonios Antoniadis (MPI für Informatik - Saarbrücken, DE) [dblp]
  • Yossi Azar (Tel Aviv University, IL) [dblp]
  • Nikhil Bansal (TU Eindhoven, NL) [dblp]
  • Sanjoy Baruah (University of North Carolina at Chapel Hill, US) [dblp]
  • Vincenzo Bonifaci (CNR - Roma, IT) [dblp]
  • Niv Buchbinder (Tel Aviv University, IL) [dblp]
  • Marek Chrobak (University of California - Riverside, US) [dblp]
  • Bouke Cloostermans (TU Eindhoven, NL) [dblp]
  • Liliana Cucu-Grosjean (INRIA - Paris, FR) [dblp]
  • Robert Davis (University of York, GB) [dblp]
  • Suzanne Den Hertog (TU München, DE) [dblp]
  • Christoph Dürr (UPMC - Paris, FR) [dblp]
  • Thomas Erlebach (University of Leicester, GB) [dblp]
  • Anupam Gupta (Carnegie Mellon University, US) [dblp]
  • Magnús M. Halldórsson (Reykjavik University, IS) [dblp]
  • Sungjin Im (University of California - Merced, US) [dblp]
  • Klaus Jansen (Universität Kiel, DE) [dblp]
  • Christos Kalaitzis (EPFL Lausanne, CH) [dblp]
  • Samir Khuller (University of Maryland - College Park, US) [dblp]
  • Amit Kumar (Indian Inst. of Technology - New Dehli, IN) [dblp]
  • Retsef Levi (MIT - Camridge, US) [dblp]
  • Alberto Marchetti-Spaccamela (Sapienza University of Rome, IT) [dblp]
  • Monaldo Mastrolilli (IDSIA - Manno, CH) [dblp]
  • Nicole Megow (TU München, DE) [dblp]
  • Rolf H. Möhring (TU Berlin, DE) [dblp]
  • Benjamin J. Moseley (Washington University - St. Louis, US) [dblp]
  • Seffi Naor (Technion - Haifa, IL) [dblp]
  • Kirk Pruhs (University of Pittsburgh, US) [dblp]
  • Thomas Rothvoss (University of Washington - Seattle, US) [dblp]
  • Jiri Sgall (Charles University - Prague, CZ) [dblp]
  • Hadas Shachnai (Technion - Haifa, IL) [dblp]
  • David Shmoys (Cornell University, US) [dblp]
  • René Sitters (VU University of Amsterdam, NL) [dblp]
  • Frits C. R. Spieksma (KU Leuven, BE) [dblp]
  • Clifford Stein (Columbia University, US) [dblp]
  • Ola Svensson (EPFL - Lausanne, CH) [dblp]
  • Marc Uetz (University of Twente, NL) [dblp]
  • Rob van Stee (University of Leicester, GB) [dblp]
  • Jose Verschae (Pontifical Catholic University of Chile - Santiago, CL) [dblp]
  • Tjark Vredeveld (Maastricht University, NL) [dblp]
  • Andreas Wiese (MPI für Informatik - Saarbrücken, DE) [dblp]
  • Gerhard J. Woeginger (TU Eindhoven, NL) [dblp]
  • Prudence W. H. Wong (University of Liverpool, GB) [dblp]

Related Seminars
  • Dagstuhl Seminar 08071: Scheduling (2008-02-10 - 2008-02-15) (Details)
  • Dagstuhl Seminar 10071: Scheduling (2010-02-14 - 2010-02-19) (Details)
  • Dagstuhl Seminar 13111: Scheduling (2013-03-10 - 2013-03-15) (Details)
  • Dagstuhl Seminar 18101: Scheduling (2018-03-04 - 2018-03-09) (Details)
  • Dagstuhl Seminar 20081: Scheduling (2020-02-16 - 2020-02-21) (Details)
  • Dagstuhl Seminar 23061: Scheduling (2023-02-05 - 2023-02-10) (Details)
  • Dagstuhl Seminar 25121: Scheduling (2025-03-16 - 2025-03-21) (Details)

  • optimization / scheduling

  • Scheduling
  • Approximation Algorithms