4 Search Results for "Rudolph, G�nter"

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-dev.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-dev.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/DagRep.5.1.96
Understanding Complexity in Multiobjective Optimization (Dagstuhl Seminar 15031)

Authors: Salvatore Greco, Kathrin Klamroth, Joshua D. Knowles, and Günter Rudolph

Published in: Dagstuhl Reports, Volume 5, Issue 1 (2015)

Abstract
This report documents the program and outcomes of the Dagstuhl Seminar 15031 Understanding Complexity in Multiobjective Optimization. This seminar carried on the series of four previous Dagstuhl Seminars (04461, 06501, 09041 and 12041) that were focused on Multiobjective Optimization, and strengthening the links between the Evolutionary Multiobjective Optimization (EMO) and Multiple Criteria Decision Making (MCDM) communities. The purpose of the seminar was to bring together researchers from the two communities to take part in a wide-ranging discussion about the different sources and impacts of complexity in multiobjective optimization. The outcome was a clarified viewpoint of complexity in the various facets of multiobjective optimization, leading to several research initiatives with innovative approaches for coping with complexity.
Cite as

Salvatore Greco, Kathrin Klamroth, Joshua D. Knowles, and Günter Rudolph. Understanding Complexity in Multiobjective Optimization (Dagstuhl Seminar 15031). In Dagstuhl Reports, Volume 5, Issue 1, pp. 96-163, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2015)

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@Article{greco_et_al:DagRep.5.1.96,
  author =	{Greco, Salvatore and Klamroth, Kathrin and Knowles, Joshua D. and Rudolph, G\"{u}nter},
  title =	{{Understanding Complexity in Multiobjective Optimization (Dagstuhl Seminar 15031)}},
  pages =	{96--163},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2015},
  volume =	{5},
  number =	{1},
  editor =	{Greco, Salvatore and Klamroth, Kathrin and Knowles, Joshua D. and Rudolph, G\"{u}nter},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DagRep.5.1.96},
  URN =		{urn:nbn:de:0030-drops-50373},
  doi =		{10.4230/DagRep.5.1.96},
  annote =	{Keywords: multiple criteria decision making, evolutionary multiobjective optimization}
}
Document
DOI: 10.4230/DagSemProc.08091.3
Approximate OWL Instance Retrieval with SCREECH

Authors: Pascal Hitzler, Markus Krötzsch, Sebastian Rudolph, and Tuvshintur Tserendorj

Published in: Dagstuhl Seminar Proceedings, Volume 8091, Logic and Probability for Scene Interpretation (2008)

Abstract
With the increasing interest in expressive ontologies for the Semantic Web, it is critical to develop scalable and efficient ontology reasoning techniques that can properly cope with very high data volumes. For certain application domains, approximate reasoning solutions, which trade soundness or completeness for increased reasoning speed, will help to deal with the high computational complexities which state of the art ontology reasoning tools have to face. In this paper, we present a comprehensive overview of the SCREECH approach to approximate instance retrieval with OWL ontologies, which is based on the KAON2 algorithms, facilitating a compilation of OWL DL TBoxes into Datalog, which is tractable in terms of data complexity. We present three different instantiations of the Screech approach, and report on experiments which show that the gain in efficiency outweighs the number of introduced mistakes in the reasoning process.
Cite as

Pascal Hitzler, Markus Krötzsch, Sebastian Rudolph, and Tuvshintur Tserendorj. Approximate OWL Instance Retrieval with SCREECH. In Logic and Probability for Scene Interpretation. Dagstuhl Seminar Proceedings, Volume 8091, pp. 1-8, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2008)

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@InProceedings{hitzler_et_al:DagSemProc.08091.3,
  author =	{Hitzler, Pascal and Kr\"{o}tzsch, Markus and Rudolph, Sebastian and Tserendorj, Tuvshintur},
  title =	{{Approximate OWL Instance Retrieval with SCREECH}},
  booktitle =	{Logic and Probability for Scene Interpretation},
  pages =	{1--8},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2008},
  volume =	{8091},
  editor =	{Anthony G. Cohn and David C. Hogg and Ralf M\"{o}ller and Bernd Neumann},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DagSemProc.08091.3},
  URN =		{urn:nbn:de:0030-drops-16157},
  doi =		{10.4230/DagSemProc.08091.3},
  annote =	{Keywords: Description logics, automated reasoning, approximate reasoning, Horn logic}
}
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