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Documents authored by Branke, Jürgen

Document
DOI: 10.4230/DagRep.15.11.1
Bayesian Optimisation (Dagstuhl Seminar 25451)

Authors: Jürgen Branke, Frank Hutter, Giulia Pedrielli, Matthias Poloczek, and Leonard Papenmeier

Published in: Dagstuhl Reports, Volume 15, Issue 11 (2026)

Abstract
This report documents the programme and outcomes of Dagstuhl Seminar 25451, "Bayesian Optimisation", held from November 2–7, 2025. The seminar brought together 39 international experts from machine learning, optimisation, statistics, and engineering to discuss recent advances, open challenges, and emerging research directions in Bayesian optimisation. The programme comprised plenary talks spanning foundational issues, benchmarking, and the growing interaction between Bayesian optimisation and generative AI, alongside focused working groups on key thematic areas. Beyond technical discussions, the seminar placed strong emphasis on community building and worked towards establishing best practices. This report summarises the plenary contributions, the outcomes of the working groups, and additional community-driven activities, including a collection of practical "tricks of the trade" and exploratory benchmarking exercises.
Cite as

Jürgen Branke, Frank Hutter, Giulia Pedrielli, Matthias Poloczek, and Leonard Papenmeier. Bayesian Optimisation (Dagstuhl Seminar 25451). In Dagstuhl Reports, Volume 15, Issue 11, pp. 1-66, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)

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@Article{branke_et_al:DagRep.15.11.1,
  author =	{Branke, J\"{u}rgen and Hutter, Frank and Pedrielli, Giulia and Poloczek, Matthias and Papenmeier, Leonard},
  title =	{{Bayesian Optimisation (Dagstuhl Seminar 25451)}},
  pages =	{1--66},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2026},
  volume =	{15},
  number =	{11},
  editor =	{Branke, J\"{u}rgen and Hutter, Frank and Pedrielli, Giulia and Poloczek, Matthias and Papenmeier, Leonard},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagRep.15.11.1},
  URN =		{urn:nbn:de:0030-drops-274940},
  doi =		{10.4230/DagRep.15.11.1},
  annote =	{Keywords: AutoML, Bayesian optimization, Benchmarking, Gaussian processes}
}
Document
DOI: 10.4230/OASIcs.SCOR.2012.11
Revenue maximization through dynamic pricing under unknown market behaviour

Authors: Sergio Morales-Enciso and Jürgen Branke

Published in: OASIcs, Volume 22, 3rd Student Conference on Operational Research (2012)

Abstract
We consider the scenario of a multimodal memoryless market to sell one product, where a customer’s probability to actually buy the product depends on the price. We would like to set the price for each customer in a way that maximizes our overall revenue. In this case, an exploration vs. exploitation problem arises. If we explore customer responses to different prices, we get a pretty good idea of what customers are willing to pay. On the other hand, this comes at the cost of losing a customer (when we set the price too high) or selling the product too cheap (when we set the price too low). The goal is to infer the true underlying probability curve as a function of the price (market behaviour) while maximizing the revenue at the same time. This paper focuses on learning the underlying market characteristics with as few data samples as possible by exploiting the knowledge gained from both exploring potentially profitable areas with high uncertainty and optimizing the trade-off between knowledge gained and revenue exploitation. The response variable being binary by nature, classification methods such as logistic regression and Gaussian processes are explored. Two new policies adapted to non parametric inference models are presented, one based on the efficient global optimization (EGO) algorithm and the second based on a dynamic programming approach. Series of simulations of the evolution of the proposed model are finally presented to summarize the achieved performance of the policies.
Cite as

Sergio Morales-Enciso and Jürgen Branke. Revenue maximization through dynamic pricing under unknown market behaviour. In 3rd Student Conference on Operational Research. Open Access Series in Informatics (OASIcs), Volume 22, pp. 11-20, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2012)

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@InProceedings{moralesenciso_et_al:OASIcs.SCOR.2012.11,
  author =	{Morales-Enciso, Sergio and Branke, J\"{u}rgen},
  title =	{{Revenue maximization through dynamic pricing under unknown market behaviour}},
  booktitle =	{3rd Student Conference on Operational Research},
  pages =	{11--20},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-939897-39-2},
  ISSN =	{2190-6807},
  year =	{2012},
  volume =	{22},
  editor =	{Ravizza, Stefan and Holborn, Penny},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.SCOR.2012.11},
  URN =		{urn:nbn:de:0030-drops-35426},
  doi =		{10.4230/OASIcs.SCOR.2012.11},
  annote =	{Keywords: Dynamic pricing, revenue management, EGO, Gaussian processes for classification}
}
Document
DOI: 10.4230/DagSemProc.09181.1
09181 Abstracts Collection – Sampling-based Optimization in the Presence of Uncertainty

Authors: Jürgen Branke, Barry L. Nelson, Warren Buckler Powell, and Thomas J. Santner

Published in: Dagstuhl Seminar Proceedings, Volume 9181, Sampling-based Optimization in the Presence of Uncertainty (2009)

Abstract
This Dagstuhl seminar brought together researchers from statistical ranking and selection; experimental design and response-surface modeling; stochastic programming; approximate dynamic programming; optimal learning; and the design and analysis of computer experiments with the goal of attaining a much better mutual understanding of the commonalities and differences of the various approaches to sampling-based optimization, and to take first steps toward an overarching theory, encompassing many of the topics above.
Cite as

Jürgen Branke, Barry L. Nelson, Warren Buckler Powell, and Thomas J. Santner. 09181 Abstracts Collection – Sampling-based Optimization in the Presence of Uncertainty. In Sampling-based Optimization in the Presence of Uncertainty. Dagstuhl Seminar Proceedings, Volume 9181, pp. 1-15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2009)

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@InProceedings{branke_et_al:DagSemProc.09181.1,
  author =	{Branke, J\"{u}rgen and Nelson, Barry L. and Powell, Warren Buckler and Santner, Thomas J.},
  title =	{{09181 Abstracts Collection – Sampling-based Optimization in the Presence of Uncertainty}},
  booktitle =	{Sampling-based Optimization in the Presence of Uncertainty},
  pages =	{1--15},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2009},
  volume =	{9181},
  editor =	{J\"{u}rgen Branke and Barry L. Nelson and Warren Buckler Powell and Thomas J. Santner},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagSemProc.09181.1},
  URN =		{urn:nbn:de:0030-drops-21187},
  doi =		{10.4230/DagSemProc.09181.1},
  annote =	{Keywords: Optimal learning, optimization in the presence of uncertainty, simulation optimization, sequential experimental design, ranking and selection, random search, stochastic approximation, approximate dynamic programming}
}
Document
DOI: 10.4230/DagSemProc.09181.2
09181 Executive Summary – Sampling-based Optimization in the Presence of Uncertainty

Authors: Jürgen Branke, Barry L. Nelson, Warren Buckler Powell, and Thomas J. Santner

Published in: Dagstuhl Seminar Proceedings, Volume 9181, Sampling-based Optimization in the Presence of Uncertainty (2009)

Abstract
This Dagstuhl seminar brought together researchers from statistical ranking and selection; experimental design and response-surface modeling; stochastic programming; approximate dynamic programming; optimal learning; and the design and analysis of computer experiments with the goal of attaining a much better mutual understanding of the commonalities and differences of the various approaches to sampling-based optimization, and to take first steps toward an overarching theory, encompassing many of the topics above.
Cite as

Jürgen Branke, Barry L. Nelson, Warren Buckler Powell, and Thomas J. Santner. 09181 Executive Summary – Sampling-based Optimization in the Presence of Uncertainty. In Sampling-based Optimization in the Presence of Uncertainty. Dagstuhl Seminar Proceedings, Volume 9181, pp. 1-3, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2009)

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@InProceedings{branke_et_al:DagSemProc.09181.2,
  author =	{Branke, J\"{u}rgen and Nelson, Barry L. and Powell, Warren Buckler and Santner, Thomas J.},
  title =	{{09181 Executive Summary – Sampling-based Optimization in the Presence of Uncertainty }},
  booktitle =	{Sampling-based Optimization in the Presence of Uncertainty},
  pages =	{1--3},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2009},
  volume =	{9181},
  editor =	{J\"{u}rgen Branke and Barry L. Nelson and Warren Buckler Powell and Thomas J. Santner},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagSemProc.09181.2},
  URN =		{urn:nbn:de:0030-drops-21161},
  doi =		{10.4230/DagSemProc.09181.2},
  annote =	{Keywords: Optimal learning, optimization in the presence of uncertainty, simulation optimization, sequential experimental design, ranking and selection, random search, stochastic approximation, approximate dynamic programming}
}
Document
DOI: 10.4230/DagSemProc.06501.1
06501 Abstracts Collection – Practical Approaches to Multi-Objective Optimization

Authors: Jürgen Branke, Kalyanmoy Deb, Kaisa Miettinen, and Roman Slowinski

Published in: Dagstuhl Seminar Proceedings, Volume 6501, Practical Approaches to Multi-Objective Optimization (2007)

Abstract
From 10.12.06 to 15.12.06, the Dagstuhl Seminar 06501 ``Practical Approaches to Multi-Objective Optimization'' was held in the International Conference and Research Center (IBFI), Schloss Dagstuhl. During the seminar, several participants presented their current research, and ongoing work and open problems were discussed. Abstracts of the presentations given during the seminar as well as abstracts of seminar results and ideas are put together in this paper. The first section describes the seminar topics and goals in general. Links to extended abstracts or full papers are provided, if available.
Cite as

Jürgen Branke, Kalyanmoy Deb, Kaisa Miettinen, and Roman Slowinski. 06501 Abstracts Collection – Practical Approaches to Multi-Objective Optimization. In Practical Approaches to Multi-Objective Optimization. Dagstuhl Seminar Proceedings, Volume 6501, pp. 1-15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2007)

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@InProceedings{branke_et_al:DagSemProc.06501.1,
  author =	{Branke, J\"{u}rgen and Deb, Kalyanmoy and Miettinen, Kaisa and Slowinski, Roman},
  title =	{{06501 Abstracts Collection – Practical Approaches to Multi-Objective Optimization}},
  booktitle =	{Practical Approaches to Multi-Objective Optimization},
  pages =	{1--15},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2007},
  volume =	{6501},
  editor =	{J\"{u}rgen Branke and Kalyanmoy Deb and Kaisa Miettinen and Roman Slowinski},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagSemProc.06501.1},
  URN =		{urn:nbn:de:0030-drops-11224},
  doi =		{10.4230/DagSemProc.06501.1},
  annote =	{Keywords: Multi-criteria optimization, evolutionary and classical methods, interaction}
}
Document
DOI: 10.4230/DagSemProc.04461.1
04461 Abstracts Collection – Practical Approaches to Multi-Objective Optimization

Authors: Jürgen Branke, Deb Kalyanmoy, Kaisa Miettinen, and Ralph E. Steuer

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

Abstract
From 07.11.04 to 12.11.04, the Dagstuhl Seminar 04461 ``Practical Approaches to Multi-Objective Optimization'' was held in the International Conference and Research Center (IBFI), Schloss Dagstuhl. During the seminar, several participants presented their current research, and ongoing work and open problems were discussed. Abstracts of the presentations given during the seminar as well as abstracts of seminar results and ideas are put together in this paper. The first section describes the seminar topics and goals in general. Links to extended abstracts or full papers are provided, if available.
Cite as

Jürgen Branke, Deb Kalyanmoy, Kaisa Miettinen, and Ralph E. Steuer. 04461 Abstracts Collection – Practical Approaches to Multi-Objective Optimization. In Practical Approaches to Multi-Objective Optimization. Dagstuhl Seminar Proceedings, Volume 4461, pp. 1-17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2005)

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@InProceedings{branke_et_al:DagSemProc.04461.1,
  author =	{Branke, J\"{u}rgen and Kalyanmoy, Deb and Miettinen, Kaisa and Steuer, Ralph E.},
  title =	{{04461 Abstracts Collection – Practical Approaches to Multi-Objective Optimization}},
  booktitle =	{Practical Approaches to Multi-Objective Optimization},
  pages =	{1--17},
  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.dagstuhl.de/entities/document/10.4230/DagSemProc.04461.1},
  URN =		{urn:nbn:de:0030-drops-2551},
  doi =		{10.4230/DagSemProc.04461.1},
  annote =	{Keywords: Multi-objective optimization, evolutionary algorithms, decision support system}
}
Document
DOI: 10.4230/DagSemProc.04461.2
04461 Summary – Practical Approaches to Multi-Criterion Optimization

Authors: Jürgen Branke, Kalyanmoy Deb, Kaisa Miettinen, and Ralph E. Steuer

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

Abstract
Summary of the Dagstuhl Seminar 04461. Motivation, proceedings, achievements and feedback, future seminars
Cite as

Jürgen Branke, Kalyanmoy Deb, Kaisa Miettinen, and Ralph E. Steuer. 04461 Summary – Practical Approaches to Multi-Criterion Optimization. In Practical Approaches to Multi-Objective Optimization. Dagstuhl Seminar Proceedings, Volume 4461, pp. 1-5, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2005)

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@InProceedings{branke_et_al:DagSemProc.04461.2,
  author =	{Branke, J\"{u}rgen and Deb, Kalyanmoy and Miettinen, Kaisa and Steuer, Ralph E.},
  title =	{{04461 Summary – Practical Approaches to Multi-Criterion Optimization}},
  booktitle =	{Practical Approaches to Multi-Objective Optimization},
  pages =	{1--5},
  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.dagstuhl.de/entities/document/10.4230/DagSemProc.04461.2},
  URN =		{urn:nbn:de:0030-drops-2430},
  doi =		{10.4230/DagSemProc.04461.2},
  annote =	{Keywords: Multi-criterion Optimization, Classical and Evolutionary Approaches}
}
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