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Documents authored by Wiecek, Margaret M.

Document
DOI: 10.4230/DagRep.13.9.1
Multiobjective Optimization on a Budget (Dagstuhl Seminar 23361)

Authors: Richard Allmendinger, Carlos M. Fonseca, Serpil Sayin, Margaret M. Wiecek, and Michael Stiglmayr

Published in: Dagstuhl Reports, Volume 13, Issue 9 (2024)

Abstract
The Dagstuhl Seminar 23361 Multiobjective Optimization on a Budget carried on a series of seven previous Dagstuhl Seminars (04461, 06501, 09041, 12041, 15031, 18031, 20031) focused on Multiobjective Optimization. The original goal of this series has been to strengthen the links between the Evolutionary Multiobjective Optimization (EMO) and the Multiple Criteria Decision Making (MCDM) communities, two of the largest communities concerned with multiobjective optimization today. This seminar particularly focused on the case where the approaches from both communities may be challenged by limited resources. This report documents the program and the outcomes of Dagstuhl Seminar 23361 "Multiobjective Optimization on a Budget". Three major types of resource limitations were highlighted during the seminar: methodological, technical and human related. The effect of these limitations on optimization and decision-making quality, as well as methods to quantify and mitigate this influence, were considered in different working groups.
Cite as

Richard Allmendinger, Carlos M. Fonseca, Serpil Sayin, Margaret M. Wiecek, and Michael Stiglmayr. Multiobjective Optimization on a Budget (Dagstuhl Seminar 23361). In Dagstuhl Reports, Volume 13, Issue 9, pp. 1-68, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@Article{allmendinger_et_al:DagRep.13.9.1,
  author =	{Allmendinger, Richard and Fonseca, Carlos M. and Sayin, Serpil and Wiecek, Margaret M. and Stiglmayr, Michael},
  title =	{{Multiobjective Optimization on a Budget (Dagstuhl Seminar 23361)}},
  pages =	{1--68},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2024},
  volume =	{13},
  number =	{9},
  editor =	{Allmendinger, Richard and Fonseca, Carlos M. and Sayin, Serpil and Wiecek, Margaret M. and Stiglmayr, Michael},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagRep.13.9.1},
  URN =		{urn:nbn:de:0030-drops-198207},
  doi =		{10.4230/DagRep.13.9.1},
  annote =	{Keywords: evolutionary algorithms, expensive optimization, few-shot learning, machine learning, optimization, simulation}
}
Document
DOI: 10.4230/DagRep.10.1.52
Scalability in Multiobjective Optimization (Dagstuhl Seminar 20031)

Authors: Carlos M. Fonseca, Kathrin Klamroth, Günter Rudolph, and Margaret M. Wiecek

Published in: Dagstuhl Reports, Volume 10, Issue 1 (2020)

Abstract
The Dagstuhl Seminar 20031 Scalability in Multiobjective Optimization carried on a series of six previous Dagstuhl Seminars (04461, 06501, 09041, 12041, 15031 and 18031) that were focused on Multiobjective Optimization. The continuing goal of this series is to strengthen the links between the Evolutionary Multiobjective Optimization (EMO) and the Multiple Criteria Decision Making (MCDM) communities, two of the largest communities concerned with multiobjective optimization today. This report documents the program and the outcomes of Dagstuhl Seminar 20031 "Scalability in Multiobjective Optimization". The seminar focused on three main aspects of scalability in multiobjective optimization (MO) and their interplay, namely (1) MO with many objective functions, (2) MO with many decision makers, and (3) MO with many variables and large amounts of data.
Cite as

Carlos M. Fonseca, Kathrin Klamroth, Günter Rudolph, and Margaret M. Wiecek. Scalability in Multiobjective Optimization (Dagstuhl Seminar 20031). In Dagstuhl Reports, Volume 10, Issue 1, pp. 52-129, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)

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@Article{fonseca_et_al:DagRep.10.1.52,
  author =	{Fonseca, Carlos M. and Klamroth, Kathrin and Rudolph, G\"{u}nter and Wiecek, Margaret M.},
  title =	{{Scalability in Multiobjective Optimization (Dagstuhl Seminar 20031)}},
  pages =	{52--129},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2020},
  volume =	{10},
  number =	{1},
  editor =	{Fonseca, Carlos M. and Klamroth, Kathrin and Rudolph, G\"{u}nter and Wiecek, Margaret M.},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagRep.10.1.52},
  URN =		{urn:nbn:de:0030-drops-124017},
  doi =		{10.4230/DagRep.10.1.52},
  annote =	{Keywords: multiple criteria decision making, evolutionary multiobjective optimization, scalability}
}
Document
DOI: 10.4230/DagRep.8.1.33
Personalized Multiobjective Optimization: An Analytics Perspective (Dagstuhl Seminar 18031)

Authors: Kathrin Klamroth, Joshua D. Knowles, Günter Rudolph, and Margaret M. Wiecek

Published in: Dagstuhl Reports, Volume 8, Issue 1 (2018)

Abstract
The Dagstuhl Seminar 18031 Personalization in Multiobjective Optimization: An Analytics Perspective carried on a series of five previous Dagstuhl Seminars (04461, 06501, 09041, 12041 and 15031) that were focused on Multiobjective Optimization. The continuing goal of this series is to strengthen the links between the Evolutionary Multiobjective Optimization (EMO) and the Multiple Criteria Decision Making (MCDM) communities, two of the largest communities concerned with multiobjective optimization today. Personalization in Multiobjective Optimization, the topic of this seminar, was motivated by the scientific challenges generated by personalization, mass customization, and mass data, and thus crosslinks application challenges with research domains integrating all aspects of EMO and MCDM. The outcome of the seminar was a new perspective on the opportunities as well as the research requirements for multiobjective optimization in the thriving fields of data analytics and personalization. Several multi-disciplinary research projects and new collaborations were initiated during the seminar, further interlacing the two communities of EMO and MCDM.
Cite as

Kathrin Klamroth, Joshua D. Knowles, Günter Rudolph, and Margaret M. Wiecek. Personalized Multiobjective Optimization: An Analytics Perspective (Dagstuhl Seminar 18031). In Dagstuhl Reports, Volume 8, Issue 1, pp. 33-99, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)

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@Article{klamroth_et_al:DagRep.8.1.33,
  author =	{Klamroth, Kathrin and Knowles, Joshua D. and Rudolph, G\"{u}nter and Wiecek, Margaret M.},
  title =	{{Personalized Multiobjective Optimization: An Analytics Perspective (Dagstuhl Seminar 18031)}},
  pages =	{33--99},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2018},
  volume =	{8},
  number =	{1},
  editor =	{Klamroth, Kathrin and Knowles, Joshua D. and Rudolph, G\"{u}nter and Wiecek, Margaret M.},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagRep.8.1.33},
  URN =		{urn:nbn:de:0030-drops-92846},
  doi =		{10.4230/DagRep.8.1.33},
  annote =	{Keywords: multiple criteria decision making, evolutionary multiobjective optimization}
}
Document
DOI: 10.4230/DagSemProc.09041.6
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.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
DOI: 10.4230/DagSemProc.09041.8
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.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}
}
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