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Dagstuhl Seminar 09041

Hybrid and Robust Approaches to Multiobjective Optimization

( Jan 18 – Jan 23, 2009 )

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The seminar “Hybrid and Robust Approaches to Multiobjective Optimization” was a sequel to two previous Dagstuhl seminars (04461 in 2004 and 06501 in 2006). The main idea of this seminar series has been to bring together two contemporary fields related to multiobjective optimization – Evolutionary Multiobjective Optimization (EMO) and Multiple Criteria Decision Making (MCDM) – to discuss critical research and application issues for bringing the entire field further and for fostering future collaboration.

This particular seminar was participated by 53 researchers actively working in multiobjective optimization. The purpose of the seminar was to discuss two fundamental research topics related to multiobjective optimization: interactive methods requiring optimization and decision making aspects to be integrated for a practical implementation and robust multiobjective methodologies dealing with uncertainties in problem parameters, objectives, constraints and algorithms. The seminar was structured to have more emphasis on working group discussions, rather than individual presentations, so that the open and free environment and facilities of Schloss Dagstuhl could be fully utilized.

Overall, the seminar provided a free atmosphere for everyone to speak and discuss freely about her of his research interests and ideas for considering robust and interactive methods for multiobjective optimization. Several future collaborative research strategies were planned involving researchers from both EMO and MCDM fields. It is hoped that in the next Dagstuhl seminar on the topic some of these collaborative research efforts will be presented.

  • Gideon Avigad (ORT Braude College, IL)
  • Jürgen Branke (University of Warwick, GB) [dblp]
  • Heinrich Braun (DHBW - Karlsruhe, DE) [dblp]
  • Nirupam Chakraborti (Indian Institut of Technology - Kharagpur, IN)
  • Carlos A. Coello Coello (CINVESTAV - Mexico, MX) [dblp]
  • Kalyanmoy Deb (Indian Inst. of Technology - Kanpur, IN) [dblp]
  • Matthias Ehrgott (University of Auckland, NZ) [dblp]
  • José Rui Figueira (IST - TU of Lisbon, PT) [dblp]
  • Jörg Fliege (University of Southampton, GB) [dblp]
  • Carlos M. Fonseca (University of Algarve, PT) [dblp]
  • Xavier Gandibleux (University of Nantes, FR) [dblp]
  • Martin Josef Geiger (University of Southern Denmark - Odense, DK) [dblp]
  • Salvatore Greco (Università di Catania, IT) [dblp]
  • Jussi Hakanen (University of Jyväskylä, FI) [dblp]
  • Sabine Helwig (Universität Erlangen-Nürnberg, DE)
  • Nicola Hochstrate (TU Dortmund University, DE)
  • Masahiro Inuiguchi (Osaka University, JP)
  • Hisao Ishibuchi (Osaka Prefecture University, JP) [dblp]
  • Johannes Jahn (Universität Erlangen-Nürnberg, DE) [dblp]
  • Andrzej Jaszkiewicz (Poznan University of Technology, PL) [dblp]
  • Yaochu Jin (Honda Research Europe - Offenbach, DE) [dblp]
  • Kathrin Klamroth (Bergische Universität Wuppertal, DE) [dblp]
  • Joshua D. Knowles (Univ. of Manchester, GB) [dblp]
  • Pekka Korhonen (Helsinki School of Economics, FI) [dblp]
  • Andreas Loehne (Martin-Luther-Universität Halle-Wittenberg, DE)
  • Mariano Luque (University of Malaga, ES) [dblp]
  • Luis Marti (Univ. Carlos III de Madrid, ES) [dblp]
  • Martin Middendorf (Universität Leipzig, DE)
  • Kaisa Miettinen (University of Jyväskylä, FI) [dblp]
  • Sanaz Mostaghim (KIT - Karlsruher Institut für Technologie, DE) [dblp]
  • Vincent Mousseau (Ecole Centrale Paris, FR) [dblp]
  • Boris Naujoks (Log!n GmbH - Schwelm, DE) [dblp]
  • Frank Neumann (MPI für Informatik - Saarbrücken, DE) [dblp]
  • Wlodek Ogryczak (Warsaw Univ. of Technology, PL)
  • Silvia Poles (Enginsoft - Padova, IT) [dblp]
  • Oleksandr Romanko (McMaster University - Hamilton, CA)
  • Sauli Ruuska (University of Jyväskylä, FI)
  • Daniel E. Salazar Aponte (Ecole des Mines - St. Etienne, FR)
  • Serpil Sayin (Koc University - Istanbul, TR) [dblp]
  • Pradyumn Kumar Shukla (TU Dresden, DE) [dblp]
  • Roman Slowinski (Poznan University of Technology, PL) [dblp]
  • Ralph E. Steuer (University of Georgia, US) [dblp]
  • Theodor J. Stewart (University of Cape Town, ZA) [dblp]
  • El-ghazali Talbi (University of Lille I, FR) [dblp]
  • Jacques Teghem (University of Mons, BE)
  • Jürgen Teich (Universität Erlangen-Nürnberg, DE) [dblp]
  • Lothar Thiele (ETH Zürich, CH) [dblp]
  • Jyrki Wallenius (Helsinki School of Economics, FI) [dblp]
  • Margaret M. Wiecek (Clemson University, US) [dblp]
  • Andrzej Wierzbicki (National Institute of Telecommunications - Warsaw, PL)
  • Katrin Witting (Universität Paderborn, DE)
  • Qingfu Zhang (University of Essex, GB) [dblp]
  • Eckart Zitzler (ETH Zürich, CH)

Related Seminars
  • Dagstuhl Seminar 04461: Practical Approaches to Multi-Objective Optimization (2004-11-07 - 2004-11-12) (Details)
  • Dagstuhl Seminar 06501: Practical Approaches to Multi-Objective Optimization (2006-12-10 - 2006-12-15) (Details)
  • Dagstuhl Seminar 12041: Learning in Multiobjective Optimization (2012-01-22 - 2012-01-27) (Details)
  • Dagstuhl Seminar 15031: Understanding Complexity in Multiobjective Optimization (2015-01-11 - 2015-01-16) (Details)
  • Dagstuhl Seminar 18031: Personalized Multiobjective Optimization: An Analytics Perspective (2018-01-14 - 2018-01-19) (Details)
  • Dagstuhl Seminar 20031: Scalability in Multiobjective Optimization (2020-01-12 - 2020-01-17) (Details)
  • Dagstuhl Seminar 23361: Multiobjective Optimization on a Budget (2023-09-03 - 2023-09-08) (Details)

  • Artificial intelligence
  • robotics
  • optimization
  • scheduling
  • soft computing
  • evol. algorithms

  • Multi-criteria optimization
  • multiple criterion decision making
  • evolutionary multiobjective optimization
  • hybrid methods
  • robustness
  • uncertainty