Search Results

Documents authored by Klamroth, Kathrin

Document
DOI: 10.4230/OASIcs.ATMOS.2021.8
Solving the Dynamic Dial-a-Ride Problem Using a Rolling-Horizon Event-Based Graph

Authors: Daniela Gaul, Kathrin Klamroth, and Michael Stiglmayr

Published in: OASIcs, Volume 96, 21st Symposium on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2021)

Abstract
In many ridepooling applications transportation requests arrive throughout the day and have to be answered and integrated into the existing (and operated) vehicle routing. To solve this dynamic dial-a-ride problem we present a rolling-horizon algorithm that dynamically updates the current solution by solving an MILP formulation. The MILP model is based on an event-based graph with nodes representing pick-up and drop-off events associated with feasible user allocations in the vehicles. The proposed solution approach is validated on a set of real-word instances with more than 500 requests. In 99.5% of all iterations the rolling-horizon algorithm returned optimal insertion positions w.r.t. the current schedule in a time-limit of 30 seconds. On average, incoming requests are answered within 2.8 seconds.
Cite as

Daniela Gaul, Kathrin Klamroth, and Michael Stiglmayr. Solving the Dynamic Dial-a-Ride Problem Using a Rolling-Horizon Event-Based Graph. In 21st Symposium on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2021). Open Access Series in Informatics (OASIcs), Volume 96, pp. 8:1-8:16, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)

Copy BibTex To Clipboard

@InProceedings{gaul_et_al:OASIcs.ATMOS.2021.8,
  author =	{Gaul, Daniela and Klamroth, Kathrin and Stiglmayr, Michael},
  title =	{{Solving the Dynamic Dial-a-Ride Problem Using a Rolling-Horizon Event-Based Graph}},
  booktitle =	{21st Symposium on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2021)},
  pages =	{8:1--8:16},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-213-6},
  ISSN =	{2190-6807},
  year =	{2021},
  volume =	{96},
  editor =	{M\"{u}ller-Hannemann, Matthias and Perea, Federico},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.ATMOS.2021.8},
  URN =		{urn:nbn:de:0030-drops-148776},
  doi =		{10.4230/OASIcs.ATMOS.2021.8},
  annote =	{Keywords: Dial-a-Ride Problem, Ridepooling, Event-Based MILP, Rolling-Horizon, Dynamic Requests}
}
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)

Copy BibTex To Clipboard

@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)

Copy BibTex To Clipboard

@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/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)

Copy BibTex To Clipboard

@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.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.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)

Copy BibTex To Clipboard

@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}
}
Questions / Remarks / Feedback
X

Feedback for Dagstuhl Publishing


Thanks for your feedback!

Feedback submitted

Could not send message

Please try again later or send an E-mail
© 2023-2024 Schloss Dagstuhl – LZI GmbH Imprint Privacy Contact