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Documents authored by Zitzler, Eckart

Document
DOI: 10.4230/DagRep.2.1.50
Learning in Multiobjective Optimization (Dagstuhl Seminar 12041)

Authors: Salvatore Greco, Joshua D. Knowles, Kaisa Miettinen, and Eckart Zitzler

Published in: Dagstuhl Reports, Volume 2, Issue 1 (2012)

Abstract
This report documents the programme and outcomes of the Dagstuhl Seminar 12041 "Learning in Multiobjective Optimization". The purpose of the seminar was to bring together researchers from the two main communities studying multiobjective optimization, Multiple Criteria Decision Making and Evolutionary Multiobjective Optimization, to take part in a wide-ranging discussion of what constitutes learning in multiobjective optimization, how it can be facilitated, and how it can be measured. The outcome was a deeper, more integrated understanding of the whole problem-solving process in multiobjective optimization from the viewpoint of learning, and several concrete research projects directly addressing different aspects of learning.
Cite as

Salvatore Greco, Joshua D. Knowles, Kaisa Miettinen, and Eckart Zitzler. Learning in Multiobjective Optimization (Dagstuhl Seminar 12041). In Dagstuhl Reports, Volume 2, Issue 1, pp. 50-99, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2012)

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@Article{greco_et_al:DagRep.2.1.50,
  author =	{Greco, Salvatore and Knowles, Joshua D. and Miettinen, Kaisa and Zitzler, Eckart},
  title =	{{Learning in Multiobjective Optimization (Dagstuhl Seminar 12041)}},
  pages =	{50--99},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2012},
  volume =	{2},
  number =	{1},
  editor =	{Greco, Salvatore and Knowles, Joshua D. and Miettinen, Kaisa and Zitzler, Eckart},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DagRep.2.1.50},
  URN =		{urn:nbn:de:0030-drops-34575},
  doi =		{10.4230/DagRep.2.1.50},
  annote =	{Keywords: multiple criteria decision making, evolutionary multiobjective optimization}
}
Document
DOI: 10.4230/DagSemProc.09041.1
09041 Abstracts Collection – Hybrid and Robust Approaches to Multiobjective Optimization

Authors: Salvatore Greco, Kalyanmoy Deb, Kaisa Miettinen, and Eckart Zitzler

Published in: Dagstuhl Seminar Proceedings, Volume 9041, Hybrid and Robust Approaches to Multiobjective Optimization (2009)

Abstract
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.
Cite as

Salvatore Greco, Kalyanmoy Deb, Kaisa Miettinen, and Eckart Zitzler. 09041 Abstracts Collection – Hybrid and Robust Approaches to Multiobjective Optimization. In Hybrid and Robust Approaches to Multiobjective Optimization. Dagstuhl Seminar Proceedings, Volume 9041, pp. 1-10, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2009)

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@InProceedings{greco_et_al:DagSemProc.09041.1,
  author =	{Greco, Salvatore and Deb, Kalyanmoy and Miettinen, Kaisa and Zitzler, Eckart},
  title =	{{09041 Abstracts Collection – Hybrid and Robust Approaches to Multiobjective Optimization}},
  booktitle =	{Hybrid and Robust Approaches to Multiobjective Optimization},
  pages =	{1--10},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2009},
  volume =	{9041},
  editor =	{Kalyanmoy Deb and Salvatore Greco and Kaisa Miettinen and Eckart Zitzler},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DagSemProc.09041.1},
  URN =		{urn:nbn:de:0030-drops-20069},
  doi =		{10.4230/DagSemProc.09041.1},
  annote =	{Keywords: Multi-objective optimization, multiple criteria decision making, evolutionary multi-objective optimization, robust optimization, interactive optimization}
}
Document
DOI: 10.4230/DagSemProc.09041.2
09041 Summary – Hybrid and Robust Approaches to Multiobjective Optimization

Authors: Kalyanmoy Deb, Salvatore Greco, Kaisa Miettinen, and Eckart Zitzler

Published in: Dagstuhl Seminar Proceedings, Volume 9041, Hybrid and Robust Approaches to Multiobjective Optimization (2009)

Abstract
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.
Cite as

Kalyanmoy Deb, Salvatore Greco, Kaisa Miettinen, and Eckart Zitzler. 09041 Summary – Hybrid and Robust Approaches to Multiobjective Optimization. In Hybrid and Robust Approaches to Multiobjective Optimization. Dagstuhl Seminar Proceedings, Volume 9041, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2009)

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@InProceedings{deb_et_al:DagSemProc.09041.2,
  author =	{Deb, Kalyanmoy and Greco, Salvatore and Miettinen, Kaisa and Zitzler, Eckart},
  title =	{{09041 Summary – Hybrid and Robust Approaches to Multiobjective Optimization}},
  booktitle =	{Hybrid and Robust Approaches to Multiobjective Optimization},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2009},
  volume =	{9041},
  editor =	{Kalyanmoy Deb and Salvatore Greco and Kaisa Miettinen and Eckart Zitzler},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DagSemProc.09041.2},
  URN =		{urn:nbn:de:0030-drops-20054},
  doi =		{10.4230/DagSemProc.09041.2},
  annote =	{Keywords: Multi-objective optimization, multiple criteria decision making, evolutionary multi-objective optimization, robust optimization, interactive optimization}
}
Document
DOI: 10.4230/DagSemProc.09041.4
09041 Working Group on EMO for Interactive Multiobjective Optimization (1st Round)

Authors: Fonseca Carlos, Xavier Gandibleux, Pekka Korhonen, Luis Marti, Boris Naujoks, Lothar Thiele, Wallenius Jyrki, and Eckart Zitzler

Published in: Dagstuhl Seminar Proceedings, Volume 9041, Hybrid and Robust Approaches to Multiobjective Optimization (2009)

Abstract
This group explored the use of EMO in an interactive manner to solve multiobjective optimization problems.
Cite as

Fonseca Carlos, Xavier Gandibleux, Pekka Korhonen, Luis Marti, Boris Naujoks, Lothar Thiele, Wallenius Jyrki, and Eckart Zitzler. 09041 Working Group on EMO for Interactive Multiobjective Optimization (1st Round). In Hybrid and Robust Approaches to Multiobjective Optimization. Dagstuhl Seminar Proceedings, Volume 9041, pp. 1-11, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2009)

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@InProceedings{fonsecacarlos_et_al:DagSemProc.09041.4,
  author =	{Fonseca Carlos and Gandibleux, Xavier and Korhonen, Pekka and Marti, Luis and Naujoks, Boris and Thiele, Lothar and Wallenius Jyrki and Zitzler, Eckart},
  title =	{{09041 Working Group on EMO for Interactive Multiobjective Optimization (1st Round)}},
  booktitle =	{Hybrid and Robust Approaches to Multiobjective Optimization},
  pages =	{1--11},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2009},
  volume =	{9041},
  editor =	{Kalyanmoy Deb and Salvatore Greco and Kaisa Miettinen and Eckart Zitzler},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DagSemProc.09041.4},
  URN =		{urn:nbn:de:0030-drops-20041},
  doi =		{10.4230/DagSemProc.09041.4},
  annote =	{Keywords: Interactive multiobjective optimization}
}
Document
DOI: 10.4230/DagSemProc.04461.6
An Adaptive Scheme to Generate the Pareto Front Based on the Epsilon-Constraint Method

Authors: Marco Laumanns, Lothar Thiele, and Eckart Zitzler

Published in: Dagstuhl Seminar Proceedings, Volume 4461, Practical Approaches to Multi-Objective Optimization (2005)

Abstract
We discuss methods for generating or approximating the Pareto set of multiobjective optimization problems by solving a sequence of constrained single-objective problems. The necessity of determining the constraint value a priori is shown to be a serious drawback of the original epsilon-constraint method. We therefore propose a new, adaptive scheme to generate appropriate constraint values during the run. A simple example problem is presented, where the running time (measured by the number of constrained single-objective sub-problems to be solved) of the original epsilon-constraint method is exponential in the problem size (number of decision variables), although the size of the Pareto set grows only linearly. We prove that --- independent of the problem or the problem size --- the time complexity of the new scheme is O(k^{m-1}), where k is the number of Pareto-optimal solutions to be found and m the number of objectives. Simulation results for the example problem as well as for different instances of the multiobjective knapsack problem demonstrate the behavior of the method, and links to reference implementations are provided.
Cite as

Marco Laumanns, Lothar Thiele, and Eckart Zitzler. An Adaptive Scheme to Generate the Pareto Front Based on the Epsilon-Constraint Method. In Practical Approaches to Multi-Objective Optimization. Dagstuhl Seminar Proceedings, Volume 4461, pp. 1-11, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2005)

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@InProceedings{laumanns_et_al:DagSemProc.04461.6,
  author =	{Laumanns, Marco and Thiele, Lothar and Zitzler, Eckart},
  title =	{{An Adaptive Scheme to Generate the Pareto Front Based on the Epsilon-Constraint Method}},
  booktitle =	{Practical Approaches to Multi-Objective Optimization},
  pages =	{1--11},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2005},
  volume =	{4461},
  editor =	{J\"{u}rgen Branke and Kalyanmoy Deb and Kaisa Miettinen and Ralph E. Steuer},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DagSemProc.04461.6},
  URN =		{urn:nbn:de:0030-drops-2465},
  doi =		{10.4230/DagSemProc.04461.6},
  annote =	{Keywords: Multiple objective optimization, non-dominated set, Pareto set, epsilon-constraint method, generating methods}
}
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