10 Search Results for "Zitzler, Eckart"


Document
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
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
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
09041 Working Group 4: MCDM and RIMO

Authors: Matthias Ehrgott, Jussi Hakanen, Hisao Ishibuchi, Andreas Loehne, Mariano Luque, Kaisa Miettinen, Wlodek Ogryczak, Olexandr Romanko, Theodor J. Stewart, and Andrzej Wierzbicki

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


Abstract
We were looking at robustness and related issues in the context of interactive MCDM, in different stages of the decision process.

Cite as

Matthias Ehrgott, Jussi Hakanen, Hisao Ishibuchi, Andreas Loehne, Mariano Luque, Kaisa Miettinen, Wlodek Ogryczak, Olexandr Romanko, Theodor J. Stewart, and Andrzej Wierzbicki. 09041 Working Group 4: MCDM and RIMO. In Hybrid and Robust Approaches to Multiobjective Optimization. Dagstuhl Seminar Proceedings, Volume 9041, pp. 1-5, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2009)


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@InProceedings{ehrgott_et_al:DagSemProc.09041.3,
  author =	{Ehrgott, Matthias and Hakanen, Jussi and Ishibuchi, Hisao and Loehne, Andreas and Luque, Mariano and Miettinen, Kaisa and Ogryczak, Wlodek and Romanko, Olexandr and Stewart, Theodor J. and Wierzbicki, Andrzej},
  title =	{{09041 Working Group 4: MCDM and RIMO}},
  booktitle =	{Hybrid and Robust Approaches to Multiobjective Optimization},
  pages =	{1--5},
  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.09041.3},
  URN =		{urn:nbn:de:0030-drops-20016},
  doi =		{10.4230/DagSemProc.09041.3},
  annote =	{Keywords: Interactive methods, robustness, MCDM, objectivity, subjectivity}
}
Document
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
09041 Working Group on EMO for Robust Multiobjective Optimization (1st Round)

Authors: Joerg Fliege, Nicola Beume, Juergen Branke, Heinrich Braun, Nirupam Chakraborti, Kalyanmoy Deb, Sabine Helwig, Joshua Knowles, Martin Middendorf, Sanaz Mostaghim, Silvia Poles, Salazar Daniel, Shukla Pradymn, and El-Ghazli Talbi

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


Abstract
This group explored various robust methodologies for multiobjective optimization.

Cite as

Joerg Fliege, Nicola Beume, Juergen Branke, Heinrich Braun, Nirupam Chakraborti, Kalyanmoy Deb, Sabine Helwig, Joshua Knowles, Martin Middendorf, Sanaz Mostaghim, Silvia Poles, Salazar Daniel, Shukla Pradymn, and El-Ghazli Talbi. 09041 Working Group on EMO for Robust Multiobjective Optimization (1st Round). In Hybrid and Robust Approaches to Multiobjective Optimization. Dagstuhl Seminar Proceedings, Volume 9041, pp. 1-5, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2009)


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@InProceedings{fliege_et_al:DagSemProc.09041.5,
  author =	{Fliege, Joerg and Beume, Nicola and Branke, Juergen and Braun, Heinrich and Chakraborti, Nirupam and Deb, Kalyanmoy and Helwig, Sabine and Knowles, Joshua and Middendorf, Martin and Mostaghim, Sanaz and Poles, Silvia and Salazar Daniel and Shukla Pradymn and Talbi, El-Ghazli},
  title =	{{09041 Working Group on EMO for Robust Multiobjective Optimization (1st Round)}},
  booktitle =	{Hybrid and Robust Approaches to Multiobjective Optimization},
  pages =	{1--5},
  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.09041.5},
  URN =		{urn:nbn:de:0030-drops-20030},
  doi =		{10.4230/DagSemProc.09041.5},
  annote =	{Keywords: Robust multiobjective optimization}
}
Document
09041 Working Group on MCDM for Robust Multiobjective Optimization (1st Round)

Authors: Jos Figueira, Martin Geiger, Salvatore Greco, Johannes Jahn, Kathrin Klamroth, Masahiro Inuiguchi, Vincent Mousseau, Sayin Serpil, Roman Slowinski, Margaret M. Wiecek, and Witting Katrin

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


Abstract
This group explored MCDM techniques for robust multiobjective optimization.

Cite as

Jos Figueira, Martin Geiger, Salvatore Greco, Johannes Jahn, Kathrin Klamroth, Masahiro Inuiguchi, Vincent Mousseau, Sayin Serpil, Roman Slowinski, Margaret M. Wiecek, and Witting Katrin. 09041 Working Group on MCDM for Robust Multiobjective Optimization (1st Round). In Hybrid and Robust Approaches to Multiobjective Optimization. Dagstuhl Seminar Proceedings, Volume 9041, pp. 1-2, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2009)


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@InProceedings{figueira_et_al:DagSemProc.09041.6,
  author =	{Figueira, Jos and Geiger, Martin and Greco, Salvatore and Jahn, Johannes and Klamroth, Kathrin and Inuiguchi, Masahiro and Mousseau, Vincent and Sayin Serpil and Slowinski, Roman and Wiecek, Margaret M. and Witting Katrin},
  title =	{{09041 Working Group on MCDM for Robust Multiobjective Optimization (1st Round)}},
  booktitle =	{Hybrid and Robust Approaches to Multiobjective Optimization},
  pages =	{1--2},
  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.09041.6},
  URN =		{urn:nbn:de:0030-drops-20025},
  doi =		{10.4230/DagSemProc.09041.6},
  annote =	{Keywords: Robust multiobjective optimization}
}
Document
A Polynomial Chaos Approach to Robust Multiobjective Optimization

Authors: Silvia Poles and Alberto Lovison

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


Abstract
Robust design optimization is a modeling methodology, combined with a suite of computational tools, which is aimed to solve problems where some kind of uncertainty occurs in the data or in the model. This paper explores robust optimization complexity in the multiobjective case, describing a new approach by means of Polynomial Chaos expansions (PCE). The aim of this paper is to demonstrate that the use of PCE may help and speed up the optimization process if compared to standard approaches such as Monte Carlo and Latin Hypercube sampling.

Cite as

Silvia Poles and Alberto Lovison. A Polynomial Chaos Approach to Robust Multiobjective Optimization. In Hybrid and Robust Approaches to Multiobjective Optimization. Dagstuhl Seminar Proceedings, Volume 9041, pp. 1-15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2009)


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@InProceedings{poles_et_al:DagSemProc.09041.7,
  author =	{Poles, Silvia and Lovison, Alberto},
  title =	{{A Polynomial Chaos Approach to Robust Multiobjective Optimization}},
  booktitle =	{Hybrid and Robust Approaches to Multiobjective Optimization},
  pages =	{1--15},
  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.09041.7},
  URN =		{urn:nbn:de:0030-drops-20009},
  doi =		{10.4230/DagSemProc.09041.7},
  annote =	{Keywords: Uncertainty Quantification, Multiobjective Robust Design, Monte Carlo, Latin Hypercube, Polynomial Chaos}
}
Document
Decomposition and Coordination for Multiobjective Complex Systems

Authors: Margaret M. Wiecek and Melissa Gardenghi

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


Abstract
Complex systems are modeled as collections of multiobjective programs each representing a subsystem (or component) of the overall system. The subsystems interact with each other in various ways adding to the complexity of the overall problem. Since the calculation of efficient sets of these complex systems presents a challenging problem, it is desirable to decompose the overall system into component multiobjective programs that are more easily solvable and then construct the efficient set of the overall system. Selected cases of complex system are presented and relationships between their efficient sets the efficient sets of their subsystems are given.

Cite as

Margaret M. Wiecek and Melissa Gardenghi. Decomposition and Coordination for Multiobjective Complex Systems. In Hybrid and Robust Approaches to Multiobjective Optimization. Dagstuhl Seminar Proceedings, Volume 9041, pp. 1-9, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2009)


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@InProceedings{wiecek_et_al:DagSemProc.09041.8,
  author =	{Wiecek, Margaret M. and Gardenghi, Melissa},
  title =	{{Decomposition and Coordination for Multiobjective Complex Systems}},
  booktitle =	{Hybrid and Robust Approaches to Multiobjective Optimization},
  pages =	{1--9},
  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.09041.8},
  URN =		{urn:nbn:de:0030-drops-19992},
  doi =		{10.4230/DagSemProc.09041.8},
  annote =	{Keywords: Multiobjective programs, complex systems, efficient set, decomposition, coordination}
}
Document
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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