List of Publications of Carola Doerr (formerly Winzen)

Carola Doerr CNRS Research director (Directrice de recherche) Sorbonne Université LIP6, équipe Recherche Opérationnelle case 169, 4 place Jussieu 75252 Paris Cedex 05 France Email: Carola [dot] Doerr "at" lip6.fr Phone: 0033 (0)1 44 27 70 64 dblp entry, Google scholar profile, full publication record

Main Page Software Editorials Book Chapters Journal Articles Conference Articles Poster Papers Workshop Articles Preprints Theses Tutorials Miscellaneous

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Availability of my (co-)authored works on arXiv and other open access formats

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• Almost all of my papers are available on arXiv. If you need a copy of a work that you cannot find on arXiv or if you need the "official" version, please do not hesitate to send me an e-mail.
• All papers from GECCO and FOGA proceedings are available free of charge through the SIGEVO website (thanks, SIGEVO!)
  
  

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Software and Benchmarking Ontology

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• [IOHprofiler] Hao Wang, Diederick Vermetten, Furong Ye, Ofer M. Shir, Carola Doerr, Thomas Bäck.
  IOHprofiler: A Benchmarking and Profiling Tool for Iterative Optimization Heuristics
  The wiki page has all relevant links to our GitHub repository, CRAN, user manuals, tutorials, etc.
  
  
• [OPTION] Ana Kostovska, Diederick Vermetten, Carola Doerr, Sašo Džeroski, Panče Panov, Tome Eftimov
  OPTION: OPTImization Algorithm Benchmarking ONtology
  IEEE Transactions on Evolutionary Computation, Volume 27, issue 6, pages 1618-1632, IEEE, 2023.
  official version, arXiv version, GitHub repository, OPTION at BioPortal, OPTION interface at IOHanalyzer
  
  

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Editorial Work

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• [IEEE TEVC 2022] Thomas Bäck, Carola Doerr, Bernhard Sendhoff, Thomas Stützle
  Guest Editorial: Special Issue on Benchmarking Sampling-Based Optimization Heuristics: Methodology and Software
  IEEE Transactions on Evolutionary Computation, Volume 26, pages 1202-1205, IEEE, 2022.
  official link
  
  
• [PPSN 2020 1/2] Thomas Thomas Bäck, Mike Preuss, Andre Deutz, Hao Wang, Carola Doerr, Michael Emmerich, Heike Trautmann.
  Parallel Problem Solving from Nature – PPSN XVI, PPSN 2020, Leiden, The Netherlands, September 5-9, 2020.
  Proceedings, Part I. LNCS 12269, Springer 2020.
  official link
  
  
• [PPSN 2020 2/2] Thomas Thomas Bäck, Mike Preuss, Andre Deutz, Hao Wang, Carola Doerr, Michael Emmerich, Heike Trautmann.
  Parallel Problem Solving from Nature – PPSN XVI, PPSN 2020, Leiden, The Netherlands, September 5-9, 2020.
  Proceedings, Part II. LNCS 12270, Springer 2020.
  official link
  
  
• [Dagstuhl 2019] Carola Doerr, Carlos M. Fonseca, Tobias Friedrich, Xin Yao.
  Theory of Randomized Optimization Heuristics (Dagstuhl Seminar 19431).
  Dagstuhl Reports, Volume 9, number 10, Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik, 2020.
  official link
  
  
• [FOGA 2019] Tobias Friedrich, Carola Doerr, Dirk V. Arnold.
  Proceedings of the 15th ACM/SIGEVO Conference on Foundations of Genetic Algorithms, FOGA 2019, Potsdam, Germany, August 27-29, 2019.
  ACM, 2019.
  official link, overview of papers. All papers in this proceedings are available free of charge here
  
  
• [Algorithmica 2019] Carola Doerr, Dirk Sudholt
  Preface to the Special Issue on Theory of Genetic and Evolutionary Computation.
  Algorithmica, Volume 81, pages 589-592, Springer, 2019.
  official link
  
  
• [Dagstuhl 2017] Carola Doerr, Christian Igel, Lothar Thiele, Xin Yao.
  Theory of Randomized Optimization Heuristics (Dagstuhl Seminar 17191).
  Dagstuhl Reports, Volume 7, number 5, Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik, 2017.
  official link
  
  
• [Algorithmica 2017] Carola Doerr, Francisco Chicano.
  Preface to the Special Issue on Theory of Genetic and Evolutionary Computation.
  Algorithmica, Volume 78, pages 558--560, Springer, 2017.
  official link
  

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Book Chapters

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• [Parameter Control 2020] Benjamin Doerr, Carola Doerr.
  Theory of Parameter Control for Discrete Black-Box Optimization: Provable Performance Gains Through Dynamic Parameter Choices
  In: B. Doerr, F. Neumann (Eds.), Theory of Evolutionary Computation, pages 271-321. Springer, 2020.
  Official version. Preliminary version on arXiv.
  
  
• [Black-Box Complexity 2020] Carola Doerr.
  Complexity Theory for Black-Box Optimization Heuristics
  In: B. Doerr, F. Neumann (Eds.), Theory of Evolutionary Computation, pages 133-212. Springer, 2020.
  Official version. Preliminary version on arXiv.
  
  
• [Discrepancy 2018: Latin Hypercube Samples] Benjamin Doerr, Carola Doerr, Michael Gnewuch.
  Probabilistic Lower Discrepancy Bounds for Latin Hypercube Samples
  J. Dick, F. Y. Kuo, H. Wozniakowski (Eds.), Contemporary Computational Mathematics - A Celebration of the 80th Birthday of Ian Sloan, pages 339-350, Springer, 2018.
  official link, arXiv version.
  
  
• [Discrepancy: Overview Article 2014] Carola Doerr, Michael Gnewuch, Magnus Wahlström.
  Calculation of Discrepancy Measures and Applications
  A Panorama of Discrepancy Theory, W.W.L. Chen, A. Srivastav, G. Travaglini (Eds.), pages 621-678. Springer, 2014.
  official link.. Author-generated version.
  
  

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Journal Articles

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• [Proc. AMS 2024+] François Clément, Carola Doerr, Kathrin Klamroth, Luís Paquete
  Constructing Optimal Star Discrepancy Sets
  Proceedings of the American Mathematical Society, Volume tbd, pages tbd, AMS, to appear (accepted November 26, 2024).
  official version to come, extended arXiv version
  
  
• [IEEE TEVC 2024+] Manuel López-Ibáñez, Diederick Vermetten, Johann Dreo, Carola Doerr
  Using the Empirical Attainment Function for Analyzing Single-objective Black-box Optimization Algorithms
  IEEE Transactions on Evolutionary Computation, Volume tbd, pages tbd, IEEE, to appear (accepted August 28, 2024).
  official version to come, arXiv version
  
  
• [Algorithmica 2024] Carola Doerr, Duri Andrea Janett, Johannes Lengler
  Tight Runtime Bounds for Static Unary Unbiased Evolutionary Algorithms on Linear Functions
  Algorithmica, volume 86, pages 3115-3152. Springer, 2024.
  official version, arXiv version
  
  
• [ECJ 2024+] Ana Kostovska, Diederick Vermetten, Peter Korosec, Saso Dzeroski, Carola Doerr, Tome Eftimov
  Using Machine Learning Methods to Assess Module Performance Contribution in Modular Optimization Frameworks
  Evolutionary Computation, MIT press, to appear. (accepted June 26, 2024)
  official version, arXiv version will be made available soon.
  
  
• [TELO 2024+] Diederick Vermetten, Furong Ye, Thomas Bäck, Carola Doerr
  MA-BBOB: A Problem Generator for Black-Box Optimization Using Affine Combinations and Shifts
  ACM Transactions on Evolutionary Learning and Optimization, Volume tbd, Issue tbd, article tbd, pages tbd, ACM, to appear (accepted May 2, 2024).
  arXiv version
  
  
• [TELO 2024] Maria Laura Santoni, Elena Raponi, Renato De Leone, Carola Doerr
  Comparison of High-Dimensional Bayesian Optimization Algorithms on BBOB
  ACM Transactions on Evolutionary Learning and Optimization, Volume 4, Issue 3, article 17, pages 17:1-17:33, ACM, 2024.
  official version, arXiv version
  
  
• [JoC 2024] François Clément, Carola Doerr, Luís Paquete
  Heuristic Approaches to Obtain Low-Discrepancy Point Sets via Subset Selection
  Journal of Complexity, Volume 83, article number 101852. Elsevier, 2024.
  official version, arXiv version
  
  
• [IEEE TEVC 2023+] Elena Raponi, Nathanael Carraz Rakotonirina, Jérémy Rapin, Carola Doerr, Olivier Teytaud
  Optimizing with Low Budgets: a Comparison on the Black-box Optimization Benchmarking Suite and OpenAI Gym
  IEEE Transactions on Evolutionary Computation, Volume tbd, pages tbd. IEEE, to appear (accepted December 7, 2023).
  official version, arXiv version
  
  
• [ECJ 2024, Software Article] Jacob de Nobel, Furong Ye, Diederick Vermetten, Hao Wang, Carola Doerr, Thomas Bäck
  IOHexperimenter: Benchmarking Platform for Iterative Optimization Heuristics
  Evolutionary Computation, volume 32, pages 205-210. MIT press, 2024.
  official version, arXiv version
  
  
• [IEEE TEVC 2023] Ana Kostovska, Diederick Vermetten, Carola Doerr, Sašo Džeroski, Panče Panov, Tome Eftimov
  OPTION: OPTImization Algorithm Benchmarking ONtology
  IEEE Transactions on Evolutionary Computation, Volume 27, issue 6, pages 1618-1632, IEEE, 2023.
  official version, arXiv version
  
  
• [IEEE TEVC 2023] Carola Doerr, Martin S. Krejca
  Run Time Analysis for Random Local Search on Generalized Majority Functions
  IEEE Transactions on Evolutionary Computation, Volume 27, issue 5, pages 1385 - 1397, IEEE, 2023.
  official version, arXiv version
  
  
• [IEEE TEVC 2022] Furong Ye, Carola Doerr, Hao Wang, Thomas Bäck
  Automated Configuration of Genetic Algorithms by Tuning for Anytime Performance
  IEEE Transactions on Evolutionary Computation, Volume 26, pages 1526 - 1538, IEEE, 2022.
  official version, arXiv version
  
  
• [JoC 2022] François Clement, Carola Doerr, Luís Paquete
  Star Discrepancy Subset Selection: Problem Formulation and Efficient Approaches for Low Dimensions
  Journal of Complexity, Volume 70, pages/article 101645, Elsevier, 2022.
  official link, arXiv version
  
  
• [TELO 2022] Hao Wang, Diederick Vermetten, Furong Ye, Carola Doerr, Thomas Bäck
  IOHanalyzer: Performance Analysis for Iterative Optimization Heuristic
  ACM Transactions on Evolutionary Learning and Optimization, Volume 2, Issue 1, article 3, pages 1-29, ACM, 2022.
  official version, arXiv version
  
  
• [Algorithmica 2022] Maxim Buzdalov, Benjamin Doerr, Carola Doerr, Dmitry Vinokurov.
  Fixed-Target Runtime Analysis
  Algorithmica, Volume 84, pages 1762-1793, Springer, 2022.
  official version, arXiv version
  
  
• [IEEE TEVC 2022] Laurent Meunier, Herilalaina Rakotoarison, Pak Kan Wong, Baptiste Roziere, Jeremy Rapin, Olivier Teytaud, Antoine Moreau, Carola Doerr
  Black-Box Optimization Revisited: Improving Algorithm Selection Wizards through Massive Benchmarking
  IEEE Transactions on Evolutionary Computation, Volume 26, pages 490-500, IEEE, 2022.
  official version, arXiv version
  
  
• [ECJ 2021] Nathan Buskulic, Carola Doerr.
  Maximizing Drift is Not Optimal for Solving OneMax
  Evolutionary Computation, volume 29, issue 4, pages 521-541. MIT press, 2021.
  official version, arXiv version
  
  
• [Algorithmica 2021] Benjamin Doerr, Carola Doerr, Johannes Lengler.
  Self-Adjusting Mutation Rates with Provably Optimal Success Rules
  Algorithmica, Volume 83, pages 3108--3147, Springer, 2021.
  official version, arXiv version
  
  
• [ASoC 2020] Carola Doerr, Furong Ye, Naama Horesh, Hao Wang, Ofer M. Shir, Thomas Bäck.
  Benchmarking Discrete Optimization Heuristics with IOHprofiler
  Applied Soft Computing, Volume 88, number 106027, Elsevier, 2020.
  official link, arXiv version
  
  
• [TCS 2020] Benjamin Doerr, Carola Doerr, Jing Yang.
  Optimal Parameter Choices via Precise Black-Box Analysis
  Theoretical Computer Science, volume 801, pages 1-34, Elsevier, 2020.
  official link, arXiv version
  
  
• [DAM 2019] Peyman Afshani, Manindra Agrawal, Benjamin Doerr, Carola Doerr, Kasper Green Larsen, Kurt Mehlhorn.
  The Query Complexity of a Permutation-Based Variant of Mastermind..
  Discrete Applied Mathematics, Volume 260, pages 28-50, Elsevier, 2019.
  official link, arXiv version
  
  
• [Algorithmica 2019] Benjamin Doerr, Carola Doerr, Timo Kötzing.
  Solving Problems with Unknown Solution Length at Almost No Extra Cost
  Algorithmica, Volume 81, pages 703-748, Springer, 2019.
  official link
  
  
• [Algorithmica 2018] Benjamin Doerr, Carola Doerr, Timo Kötzing.
  Static and Self-Adjusting Mutation Strengths for Multi-Valued Decision Variables
  Algorithmica, volume 80, pages 1732-1768, Springer, 2018.
  official link, free HAL version
  
  
• [Algorithmica 2018] Benjamin Doerr, Carola Doerr.
  Optimal Static and Self-Adjusting Parameter Choices for the $(1+(\lambda,\lambda))$ Genetic Algorithm
  Algorithmica, volume 80, pages 1658-1709, Springer, 2018.
  official link
  
  
• [Algorithmica 2018] Carola Doerr, Johannes Lengler.
  The (1+1) Elitist Black-Box Complexity of LeadingOnes
  Algorithmica, volume 80, pages 1579-1603, Springer, 2018.
  official link
  
  
• [ECJ 2017] Carola Doerr, Johannes Lengler.
  Introducing Elitist Black-Box Models: When Does Elitist Behavior Weaken the Performance of Evolutionary Algorithms?
  Evolutionary Computation, Volume 25, pages 587-606. MIT press, 2017.
  official link
  
  
• [Algorithmica 2017] Carola Doerr, Johannes Lengler.
  OneMax in Black-Box Models with Several Restrictions
  Algorithmica, Volume 78, pages 610--640, Springer, 2017.
  official link
  
  
• [JACM 2016] Benjamin Doerr, Carola Doerr, Reto Spöhel, Henning Thomas.
  Playing Mastermind with Many Colors
  Journal of the ACM, Volume 63, Article 42, ACM, 2016.
  official link, arXiv version.
  
  
• [Algorithmica 2016] Benjamin Doerr, Carola Doerr.
  The Impact of Random Initialization on the Runtime of Randomized Search Heuristics
  Algorithmica, Volume 75, pages 529-553, Springer, 2016.
  Official link.
  
  
• [DIST 2016] Benjamin Doerr, Carola Doerr, Shay Moran, Shlomo Moran.
  Simple and Optimal Randomized Fault-Tolerant Rumor Spreading.
  Distributed Computing, Volume 29, pages 89-104, Springer, 2016.
  Official link., Preliminary arXiv version.
  
  
• [RSA 2016] Andrea Clementi, Pierluigi Crescenzi, Carola Doerr, Pierre Fraigniaud, Francesco Pasquale, Riccardo Silvestri.
  Rumor Spreading in Random Evolving Graphs.
  Random Structures & Algorithms, Volume 48, pages 290-312, Wiley, 2016.
  Official link.
  
  
• [ECJ 2015] Benjamin Doerr, Carola Doerr, Timo Kötzing.
  Unbiased Black-Box Complexities of Jump Functions
  Evolutionary Computation, Volume 23, pages 641-670, MIT press, 2015.
  Official link.
  
  
• [TCS 2015] Benjamin Doerr, Carola Doerr, Franziska Ebel.
  From Black-Box Complexity to Designing New Genetic Algorithms
  Theoretical Computer Science, Volume 567, pages 87-104, Elsevier, 2015.
  Official link.
  
  
• [ArtInt 2014] Benjamin Doerr, Carola Doerr, Timo Kötzing.
  The Unbiased Black-Box Complexity of Partition is Polynomial
  Artificial Intelligence, Volume 216, pages 275-286, Elsevier, 2014.
  official link..
  
  
• [JGAA 2014] Carola Doerr, Jens M. Schmidt, G. Ramakrishna.
  Computing Minimum Cycle Bases in Weighted Partial 2-Trees in Linear Time.
  Journal of Graph Algorithms and Applications, Volume 18, pages 325-346, 2014.
  official link..
  
  
• [ToCS 2014] Benjamin Doerr, Carola Winzen.
  Playing Mastermind with Constant-Size Memory
  Theory of Computing Systems, STACS 2012 special issue, Volume 55, pages 658-684, Springer, 2014.
  Official link., arXiv version.
  
  
• [Algorithmica 2014] Benjamin Doerr, Carola Winzen.
  Ranking-Based Black-Box Complexity
  Algorithmica, Volume 68, pages 571-609, Springer, 2014.
  official link. Preliminary arXiv version..
  
  
• [TEAC 2014] Xujin Chen, Benjamin Doerr, Carola Doerr, Xiaodong Hu, Weidong Ma, Rob van Stee.
  The Price of Anarchy for Selfish Ring Routing is Two
  ACM Transactions on Economics and Computation, volume 2, 8 pages, ACM, 2014.
  official link. arXiv version.
  
  
• [TCS 2014] Benjamin Doerr, Carola Winzen.
  Reducing the Arity in Unbiased Black-Box Complexity
  Theoretical Computer Science, Gecco 2012 special issue, volume 545, pages 108-121, Elsevier, 2014.
  official link. arXiv version.
  
  
• [IPL 2013] Carola Winzen.
  Direction-Reversing Quasi-Random Rumor Spreading with Restarts
  Information Processing Letters, Volume 113, pages 921-926, Elsevier, 2013.
  official link., arXiv version.
  
  
• [TCS 2013] Benjamin Doerr, Timo Kötzing, Johannes Lengler, Carola Winzen.
  Black-Box Complexities of Combinatorial Problems
  Theoretical Computer Science, Volume 471, pages 84–106, Elsevier, 2013.
  official link, DOI: 10.1016/j.tcs.2012.10.039. arXiv version.
  
  
• [ECJ 2013] Benjamin Doerr, Thomas Jansen, Dirk Sudholt, Carola Winzen, Christine Zarges.
  Mutation Rate Matters Even When Optimizing Monotone Functions
  Evolutionary Computation, Volume 21, pages 1-27, MIT Press, 2013.
  Official link. arXiv version.
  
  
• [SIAM JoNA 2012] Michael Gnewuch, Magnus Wahlström, Carola Winzen.
  A New Randomized Algorithm to Approximate the Star Discrepancy Based on Threshold Accepting
  SIAM Journal on Numerical Analysis, Volume 50, pages 781-807, SIAM Society for Industrial and Applied Mathematics, 2012.
  official link. Extended authors generated version.
  
  
• [Algorithmica 2012] Benjamin Doerr, Daniel Johannsen, Carola Winzen.
  Multiplicative Drift Analysis
  Algorithmica (special issue on evolutionary computation), Volume 64, pages 673-697, Springer, 2012.
  official link to online version. arXiv version.
  
  
• [TCS 2012] Benjamin Doerr, Daniel Johannsen, Carola Winzen.
  Non-Existence of Universal Drift Functions
  Theoretical Computer Science, Volume 436, pages 71-86, Elsevier, 2012.
  Official link. arXiv version.
  
  
• [IPL 2012] Benjamin Doerr, Carola Winzen.
  Memory-Restricted Black-Box Complexity of OneMax
  Information Processing Letters, Volume 112, pages 32-34, Elsevier, 2012.
  Official link. ECCC version.
  
  
• [J. Complexity 2009] Michael Gnewuch, Anand Srivastav, Carola Winzen.
  Finding optimal volume subintervals with k points and calculating the star discrepancy are NP-hard problems
  Journal of Complexity, Volume 25, pages 115-127, Elsevier, 2009.
  official link. authors generated version.
  
  

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Conference Articles

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• [EMO 2025] Diederick Vermetten, Jeroen Rook, Oliver Preuss, Jacob de Nobel, Carola Doerr, Manuel López-Ibáñez, Heike Trautmann, Thomas Bäck
  MO-IOHinspector: Anytime Benchmarking of Multi-Objective Algorithms using IOHprofiler
  Proc. of Evolutionary Multi-Criterion Optimization (EMO 2025), Lecture Notes in Computer Science, vol tbd. Springer, 2025.
  arXiv version will be made available soon.
  
  
• [PPSN 2024] Diederick Vermetten, Johannes Lengler, Dimitri Rusin, Thomas Bäck, Carola Doerr
  Empirical Analysis of the Dynamic Binary Value Problem with IOHprofiler
  Proc. of Parallel Problem Solving from Nature – PPSN XVIII (PPSN 2024), Lecture Notes in Computer Science, vol 15149. Springer, 2024.
  official version, arXiv version
  
  
• [PPSN 2024] Moritz Seiler, Urban Škvorc, Gjorgjina Cenikj, Carola Doerr, Heike Trautmann
  Learned Features vs. Classical ELA on Affine BBOB Functions
  Proc. of Parallel Problem Solving from Nature – PPSN XVIII (PPSN 2024), Lecture Notes in Computer Science, vol 15149. Springer, 2024.
  official version, arXiv version coming soon, happy to share a preliminary version in the meantime...
  
  
• [PPSN 2024] Konstantin Dietrich, Raphael Patrick Prager, Carola Doerr, Heike Trautmann
  Hybridizing Target- and SHAP-encoded Features for Algorithm Selection in Mixed-variable Black-box Optimization
  Proc. of Parallel Problem Solving from Nature – PPSN XVIII (PPSN 2024), Lecture Notes in Computer Science, vol 15149. Springer, 2024.
  official version, arXiv version
  
  
• [LION 2024] Moritz Vinzent Seiler, Urban Škvorc, Carola Doerr, Heike Trautmann
  Synergies of Deep and Classical ELA Features
  Proc. of Learning and Intelligent Optimization (LION 2024), pages tbd. Springer, 2024. To appear.
  HAL version (open access)
  
  
• [GECCO 2024] Konstantin Dietrich, Diederick Vermetten, Carola Doerr, Pascal Kerschke
  Impact of Training Instance Selection on Automated Algorithm Selection Models for Numerical Black-box Optimization
  Proc. of Genetic and Evolutionary Computation Conference (GECCO 2024), pages 1007-1016. ACM, 2024.
  official version, arXiv version
  
  
• [GECCO 2024] Diederick Vermetten, Carola Doerr, Hao Wang, Anna V. Kononova, Thomas Bäck
  Large-scale Benchmarking of Metaphor-based Optimization Heuristics
  Proc. of Genetic and Evolutionary Computation Conference (GECCO 2024), pages 41-49. ACM, 2024.
  official version, arXiv version
  
  
• [WCCI CEC 2024] Ana Nikolikj, Ana Kostovska, Diederick Vermetten, Carola Doerr, Tome Eftimov
  Quantifying Individual and Joint Module Impact in Modular Optimization Frameworks
  Proc. of IEEE Congress on Evolutionary Computation (CEC 2024). IEEE, 2024.
  official version, arXiv version
  
  
• [WCCI CEC 2024] Ana Nikolikj, Ana Kostovska, Gjorgjina Cenikj, Carola Doerr, Tome Eftimov
  Generalization Ability of Feature-based Performance Prediction Models: A Statistical Analysis across Benchmarks
  Proc. of IEEE Congress on Evolutionary Computation (CEC 2024). IEEE, 2024.
  official version, arXiv version
  
  
• [FOGA 2023] Deyao Chen, Maxim Buzdalov, Carola Doerr, Nguyen Dang
  Using Automated Algorithm Configuration for Parameter Control
  Proc. of the 17th ACM/SIGEVO Conference on Foundations of Genetic Algorithms (FOGA XVII), pages 38-49. ACM, 2023.
  official version, arXiv version
  Runner-up for the best paper award (program)
  
  
• [AutoML 2023 (ABCD track)] Diederick Vermetten, Furong Ye, Thomas Bäck, Carola Doerr
  MA-BBOB: Many-Affine Combinations of BBOB Functions for Evaluating AutoML Approaches in Noiseless Numerical Black-Box Optimization Contexts
  Proc. of International Conference on Automated Machine Learning (AutoML 2023). Proceedings of Machine Learning Research (PMLR), volume 224, pages 7/1-14, 2023.
  official version, arXiv version
  
  
• [AutoML 2023] Ana Kostovska, Gjorgjina Cenikj, Diederick Vermetten, Anja Jankovic, Ana Nikolikj, Urban Skvorc, Peter Korosec, Carola Doerr, Tome Eftimov
  PS-AAS: Portfolio Selection for Automated Algorithm Selection in Black-Box Optimization
  Proc. of International Conference on Automated Machine Learning (AutoML 2023). Proceedings of Machine Learning Research (PMLR), volume 224, pages 11/1-17, 2023.
  official version
  
  
• [AutoML 2023] Carolin Benjamins, Elena Raponi, Anja Jankovic, Carola Doerr, Marius Lindauer
  Self-Adjusting Weighted Expected Improvement for Bayesian Optimization
  Proc. of International Conference on Automated Machine Learning (AutoML 2023). Proceedings of Machine Learning Research (PMLR), volume 224, pages 6/1-50, 2023.
  official version, arXiv version
  
  
• [GECCO 2023] Carola Doerr, Duri Andrea Janett, Johannes Lengler
  Tight Runtime Bounds for Static Unary Unbiased Evolutionary Algorithms on Linear Functions
  Proc. of Genetic and Evolutionary Computation Conference (GECCO 2023), pages 1565-1574. ACM, 2023.
  official version, arXiv version
  
  
• [GECCO 2023] François Clement, Diederick Vermetten, Jacob de Nobel, Alexandre Jesus, Luís Paquete, Carola Doerr
  Computing Star Discrepancies with Numerical Black-Box Optimization Algorithms
  Proc. of Genetic and Evolutionary Computation Conference (GECCO 2023), pages 1330-1338. ACM, 2023.
  official version, arXiv version
  
  
• [GECCO 2023] Diederick Vermetten, Furong Ye, Carola Doerr
  Using Affine Combinations of BBOB Problems for Performance Assessment
  Proc. of Genetic and Evolutionary Computation Conference (GECCO 2023), pages 873-881. ACM, 2023.
  official version, arXiv version
  Best paper award (ENUM track).
  
  
• [GECCO 2023] Gjorgjina Cenikj, Gašper Petelin, Carola Doerr, Peter Korošec, Tome Eftimov
  DynamoRep: Trajectory-Based Population Dynamics for Classification of Black-box Optimization Problems
  Proc. of Genetic and Evolutionary Computation Conference (GECCO 2023), pages 813-821. ACM, 2023.
  official version, arXiv version
  
  
• [GECCO 2023] Ana Nikolikj, Saso Dzeroski, Mario Andrés Muñoz, Carola Doerr, Peter Korošec, Tome Eftimov
  Algorithm Instance Footprint: Separating Easily Solvable and Challenging Problem Instances
  Proc. of Genetic and Evolutionary Computation Conference (GECCO 2023), pages 529-537. ACM, 2023.
  official version, arXiv version
  
  
• [CEC 2023] Ana Nikolikj, Michal Pluhacek, Carola Doerr, Peter Korosec, Tome Eftimov
  Sensitivity analysis of RF+clust for leave-one-problem-out performance prediction
  Proc. of 2023 IEEE Congress on Evolutionary Computation (CEC), pages 1-8, IEEE, 2023.
  official version, arXiv version
  
  
• [EvoApplications 2023] Ana Kostovska, Diederick Vermetten, Sašo Džeroski, Panče Panov, Tome Eftimov, Carola Doerr
  Using Knowledge Graphs for Performance Prediction of Modular Optimization Algorithms
  Proc. of International Conference on the Applications of Evolutionary Computation (EvoApplications 2023), pages 253-268, LNCS vol. 13989, Springer, 2023.
  official version, arXiv version
  
  
• [EvoApplications 2023] Ana Nikolikj, Carola Doerr, Tome Eftimov
  RF+clust for Leave-One-Problem-Out Performance Prediction
  Proc. of International Conference on the Applications of Evolutionary Computation (EvoApplications 2023), pages 285-301, LNCS vol. 13989, Springer, 2023.
  official version, arXiv version
  
  
• [SSCI 2022] Ana Kostovska, Carola Doerr, Sašo Džeroski, Dragi Kocev, Panče Panov, Tome Eftimov
  Explainable Model-specific Algorithm Selection for Multi-Label Classification
  Proc. of IEEE Symposium Series on Computational Intelligence (SSCI 2022), pages 39-46, IEEE, 2022.
  official version arXiv version
  
  
• [PPSN 2022] Kirill Antonov, Elena Raponi, Hao Wang, Carola Doerr
  High Dimensional Bayesian Optimization with Kernel PCA
  Proc. of Parallel Problem Solving from Nature – PPSN XVII (PPSN 2022), pages 118–131, Springer, LNCS, volume 13398, 2022.
  official version, arXiv version
  
  
• [PPSN 2022] Risto Trajanov, Ana Nikolikj, Gjorgjina Cenikj, Fabien Teytaud, Mathurin Videau, Olivier Teytaud, Tome Eftimov, Manuel López-Ibáñez, Carola Doerr
  Improving Nevergrad's Algorithm Selection Wizard NGOpt through Automated Algorithm Configuration
  Proc. of Parallel Problem Solving from Nature – PPSN XVII (PPSN 2022), pages 18–31, Springer, LNCS volume 13398, 2022.
  official version, arXiv version.
  
  
• [PPSN 2022] Furong Ye, Diederick Vermetten, Carola Doerr, Thomas Bäck
  Non-Elitist Selection Can Improve the Performance of Irace
  Proc. of Parallel Problem Solving from Nature – PPSN XVII (PPSN 2022), pages 32–45, Springer, LNCS volume 13398, 2022.
  official version, arXiv version
  
  
• [PPSN 2022] Ana Kostovska, Anja Jankovic, Diederick Vermetten, Jacob de Nobel, Hao Wang, Tome Eftimov, Carola Doerr
  Per-Run Algorithm Selection with Warm-starting Using Trajectory-based Features
  Proc. of Parallel Problem Solving from Nature – PPSN XVII (PPSN 2022), pages 46–60, Springer, LNCS volume 13398, 2022.
  official version, arXiv version
  
  
• [WCCI CEC 2022] Anja Jankovic, Diederick Vermetten, Ana Kostovska, Jacob de Nobel, Tome Eftimov, Carola Doerr
  Trajectory-based Algorithm Selection with Warm-starting
  Proc. of IEEE World Congress on Computational Intelligence (WCCI CEC 2022), pages 1-8, IEEE, 2022.
  official version, arXiv version
  
  
• [WCCI CEC 2022] Nina Bulanova, Arina Buzdalova, Carola Doerr
  Fast Re-Optimization of LeadingOnes with Frequent Changes
  Proc. of IEEE World Congress on Computational Intelligence (WCCI CEC 2022), pages 1-8, IEEE, 2022.
  official version, arXiv version.
  
  
• [GECCO 2022] André Biedenkapp, Nguyen Dang, Martin Krejca, Frank Hutter, Carola Doerr
  Theory-inspired Parameter Control Benchmarks for Dynamic Algorithm Configuration
  Proc. of Genetic and Evolutionary Computation Conference (GECCO 2022), pages 766–775, ACM, 2022.
  official version, arXiv version
  Best paper award (GECH track).
  
  
• [GECCO 2022] Diederick Vermetten, Hao Wang, Carola Doerr, Manuel López-Ibáñez, Thomas Bäck
  Analyzing the Impact of Undersampling on the Benchmarking and Configuration of Evolutionary Algorithms
  Proc. of Genetic and Evolutionary Computation Conference (GECCO 2022), pages 867–875, ACM, 2022.
  official version, arXiv version
  
  
• [GECCO 2022] Gjorgjina Cenikj, Ryan Dieter Lang, Andries Petrus Engelbrecht, Carola Doerr, Peter Korošec, Tome Eftimov
  SELECTOR: Selecting a Representative Benchmark Suite for Reproducible Statistical Comparison
  Proc. of Genetic and Evolutionary Computation Conference (GECCO 2022), pages 620–629, ACM, 2022.
  official version, arXiv version
  
  
• [GECCO 2022] Quentin Renau, Johann Dreo, Alain Peres, Yann Semet, Carola Doerr, Benjamin Doerr
  Automated Algorithm Selection for Radar Network Configuration
  Proc. of Genetic and Evolutionary Computation Conference (GECCO 2022), pages 1263–1271, ACM, 2022.
  official version, arXiv version
  
  
• [GECCO 2022] Ana Kostovska, Diederick Vermetten, Sašo Džeroski, Carola Doerr, Peter Korošec, Tome Eftimov
  The Importance of Landscape Features for Performance Prediction of Modular CMA-ES Variants
  Proc. of Genetic and Evolutionary Computation Conference (GECCO 2022), pages 648–656, ACM, 2022.
  official version, arXiv version
  
  
• [CEC 2021] Kirill Antonov, Maxim Buzdalov, Arina Buzdalova, Carola Doerr
  Blending Dynamic Programming with Monte Carlo Simulation for Bounding the Running Time of Evolutionary Algorithms
  Proc. of IEEE Congress on Evolutionary Computation (CEC 2021), pages 878-885, IEEE, 2021.
  official version, arXiv version
  Best paper award.
  
  
• [GECCO 2021] Maxim Buzdalov, Carola Doerr
  Optimal Static Mutation Strength Distributions for the (1+lambda) Evolutionary Algorithm on OneMax
  Proc. of Genetic and Evolutionary Computation Conference (GECCO 2021), pages 660-668, ACM, 2021.
  official version, arXiv version, GitHub page, data on zenodo
  
  
• [GECCO 2021] Anja Jankovic, Gorjan Popovski, Tome Eftimov, Carola Doerr
  The Impact of Hyper-Parameter Tuning for Landscape-Aware Performance Regression and Algorithm Selection
  Proc. of Genetic and Evolutionary Computation Conference (GECCO 2021), pages 687-696, ACM, 2021.
  arXiv paper
  
  
• [GECCO 2021] Tome Eftimov, Anja Jankovic, Gorjan Popovski, Carola Doerr, Peter Korošec
  Personalizing Performance Regression Models to Black-Box Optimization Problems
  Proc. of Genetic and Evolutionary Computation Conference (GECCO 2021), pages 669-677, ACM, 2021.
  arXiv paper
  
  
• [EvoApplications 2021] Anja Jankovic, Tome Eftimov, Carola Doerr
  Towards Feature-Based Performance Regression Using Trajectory Data
  Proc. of International Conference on the Applications of Evolutionary Computation (EvoAPP), pages 601-617, LNCS volume 12694, Springer, 2021.
  Best paper award.
  official version, arXiv paper
  
  
• [EvoApplications 2021] Quentin Renau, Carola Doerr, Johann Dreo, Benjamin Doerr
  Towards Explainable Exploratory Landscape Analysis: Extreme Feature Selection for Classifying BBOB Functions
  Proc. of International Conference on the Applications of Evolutionary Computation (EvoAPP), pages 17-33, LNCS volume 12694, Springer, 2021.
  official version, arXiv paper, project data on zenodo.
  
  
• [EvoCOP 2021] Mohamed El Yafrani, Marcella Scoczynski Ribeiro Martins, Inkyung Sung, Markus Wagner, Carola Doerr, Peter Nielsen
  MATE: A Model-based Algorithm Tuning Engine
  Proc. of European Conference on Evolutionary Computation in Combinatorial Optimisation (EvoCOP), pages 51-67, LNCS volume 12692, Springer, 2021.
  official version, arXiv version
  
  
• [SSCI 2020] Tome Eftimov, Gorjan Popovski, Quentin Renau, Peter Korošec, Carola Doerr.
  Linear Matrix Factorization Embeddings for Single-objective Optimization Landscapes
  Proc. of IEEE Symposium Series on Computational Intelligence (IEEE SSCI), pages 775-782, IEEE, 2020.
  official link, arXiv version
  
  
• [PPSN 2020] Quentin Renau, Carola Doerr, Johann Dreo, Benjamin Doerr.
  Exploratory Landscape Analysis is Strongly Sensitive to the Sampling Strategy
  Proc. of Parallel Problem Solving from Nature (PPSN XVI), pages 139-153, LNCS volume 12270, Springer, 2020.
  official link, arXiv version
  
  
• [PPSN 2020] Laurent Meunier, Carola Doerr, Jeremy Rapin, Olivier Teytaud.
  Variance Reduction for Better Sampling in Continuous Domains
  Proc. of Parallel Problem Solving from Nature (PPSN XVI), pages 154-168, LNCS volume 12269, Springer, 2020.
  official link, arXiv version
  
  
• [PPSN 2020] Jakob Bossek, Carola Doerr, Pascal Kerschke, Aneta Neumann, Frank Neumann.
  Evolving Sampling Strategies for One-Shot Optimization Tasks
  Proc. of Parallel Problem Solving from Nature (PPSN XVI), pages 111-124, LNCS volume 12269, Springer, 2020.
  official link, arXiv version
  
  
• [PPSN 2020] Arina Buzdalova, Carola Doerr, Anna Rodionova.
  Hybridizing the 1/5-th Success Rule with Q-Learning for Controlling the Mutation Rate of an Evolutionary Algorithm
  Proc. of Parallel Problem Solving from Nature (PPSN XVI), pages 485-499, LNCS volume 12270, Springer, 2020.
  official link, arXiv version
  
  
• [PPSN 2020] Elena Raponi, Hao Wang, Mariusz Bujny, Simonetta Boria, Carola Doerr.
  High Dimensional Bayesian Optimization assisted by Principal Component Analysis
  Proc. of Parallel Problem Solving from Nature (PPSN XVI), pages 169-183, LNCS volume 12269, Springer, 2020.
  official link, arXiv version
  
  
• [PPSN 2020] Maxim Buzdalov, Carola Doerr.
  Optimal Mutation Rates for the (1+\lambda) EA on OneMax
  Proc. of Parallel Problem Solving from Nature (PPSN XVI), pages 574-587, LNCS volume 12270, Springer, 2020.
  official link, arXiv version
  
  
• [PPSN 2020] Furong Ye, Hao Wang, Carola Doerr, Thomas Bäck.
  Benchmarking a (\mu+\lambda) Genetic Algorithm with Configurable Crossover Probability
  Proc. of Parallel Problem Solving from Nature (PPSN XVI), pages 699-713, LNCS volume 12270, Springer, 2020.
  official link, arXiv version
  
  
• [GECCO 2020] Diederick Vermetten, Hao Wang, Carola Doerr, Thomas Bäck.
  Integrated vs. Sequential Approaches for Selecting and Tuning CMA-ES Variants
  Proc. of Genetic and Evolutionary Computation Conference (GECCO 2020), pages 903-912, ACM, 2020.
  arXiv version
  
  
• [GECCO 2020] Diederick Vermetten, Hao Wang, Thomas Bäck, Carola Doerr.
  Towards Dynamic Algorithm Selection for Numerical Black-Box Optimization: Investigating BBOB as a Use Case
  Proc. of Genetic and Evolutionary Computation Conference (GECCO 2020), pages 654-662, ACM, 2020.
  arXiv version
  
  
• [GECCO 2020] Anja Jankovic, Carola Doerr.
  Landscape-Aware Fixed-Budget Performance Regression for Modular CMA-ES Variants
  Proc. of Genetic and Evolutionary Computation Conference (GECCO 2020), pages 841-849, ACM, 2020.
  arXiv version
  
  
• [GECCO 2020] Jakob Bossek, Carola Doerr, Pascal Kerschke.
  Initial Design Strategies and their Effects on Sequential Model-Based Optimization: An Exploratory Case Study Based on BBOB
  Proc. of Genetic and Evolutionary Computation Conference (GECCO 2020), pages 778-786, ACM, 2020.
  arXiv version
  
  
• [GECCO 2020] Maxim Buzdalov, Benjamin Doerr, Carola Doerr, Dmitry Vinokurov.
  Fixed-Target Runtime Analysis
  Proc. of Genetic and Evolutionary Computation Conference (GECCO 2020), pages 1295-1303, ACM, 2020.
  full arXiv version
  
  
• [MOTOR 2020] Kirill Antonov, Arina Buzdalova, Carola Doerr.
  Mutation Rate Control in (1 + lambda) Evolutionary Algorithm with a Self-adjusting Lower Bound
  Proc. of Mathematical Optimization Theory and Operations Research (MOTOR 2020), Springer, 2020.
  
  
• [AAAI 2020, oral presentation] Benjamin Doerr, Carola Doerr, Aneta Neumann, Frank Neumann, Andrew M. Sutton.
  Optimization of Chance-Constrained Submodular Functions
  Proc. of AAAI Conference on Artificial Intelligence (AAAI 2020), pages 1460-1467, AAAI, 2020.
  arXiv version
  
  
• [GECCO 2019] Benjamin Doerr, Carola Doerr, Johannes Lengler.
  Self-Adjusting Mutation Rates with Provably Optimal Success Rules
  Proc. of Genetic and Evolutionary Computation Conference (GECCO 2019), pages 1479-1487, ACM, 2019.
  preliminary version on arXiv.
  
  
• [GECCO 2019] Diederick Vermetten, Sander van Rijn, Carola Doerr, Thomas Bäck
  Online Selection of CMA-ES Variants
  Proc. of Genetic and Evolutionary Computation Conference (GECCO 2019), pages 951-959, ACM, 2019.
  preliminary version on arXiv.
  
  
• [GECCO 2019] Benjamin Doerr, Carola Doerr, Frank Neumann.
  Fast Re-Optimization via Structural Diversity
  Proc. of Genetic and Evolutionary Computation Conference (GECCO 2019), pages 233-241, ACM, 2019.
  preliminary version on arXiv.
  
  
• [GECCO 2019] Nguyen Dang, Carola Doerr.
  Hyper-Parameter Tuning for the (1+(lambda,lambda)) GA
  Proc. of Genetic and Evolutionary Computation Conference (GECCO 2019), pages 889-897, ACM, 2019.
  preliminary version on arXiv.
  
  
• [GECCO 2019] Anna Rodionova, Kirill Antonov, Arina Buzdalova, Carola Doerr.
  Offspring Population Size Matters when Comparing Evolutionary Algorithms with Self-Adjusting Mutation Rates
  Proc. of Genetic and Evolutionary Computation Conference (GECCO 2019), pages 855-863, ACM, 2019.
  preliminary version on arXiv.
  
  
• [CEC 2019] Furong Ye, Carola Doerr, Thomas Bäck
  Interpolating Local and Global Search by Controlling the Variance of Standard Bit Mutation
  Proc. of Congress on Evolutionary Computation Conference (CEC 2019), pages 2292-2299, IEEE, 2019.
  preliminary version on arXiv
  
  
• [PPSN 2018] Sander van Rijn, Carola Doerr, Thomas Bäck
  Towards an Adaptive CMA-ES Configurator
  Proc. of Parallel Problem Solving from Nature (PPSN 2018), pages 54-65, LNCS 11101, Springer, 2018.
  
  
• [PPSN 2018] Eduardo Carvalho Pinto, Carola Doerr
  A Simple Proof for the Usefulness of Crossover in Black-Box Optimization
  Proc. of Parallel Problem Solving from Nature (PPSN 2018), pages 29-41, LNCS 11102, Springer, 2018.
  A longer paper covering the result presented in this paper is available on arXiv. It has a different title, since it subsumes some results and discussions that are not part of the PPSN paper.
  
  
• [PPSN 2018] Carola Doerr, Markus Wagner
  Sensitivity of Parameter Control Mechanisms with Respect to Their Initialization
  Proc. of Parallel Problem Solving from Nature (PPSN 2018), pages 360-372, LNCS 11102, Springer, 2018.
  
  
• [GECCO 2018] Carola Doerr, Furong Ye, Sander van Rijn, Hao Wang, Thomas Bäck
  Towards a Theory-Guided Benchmarking Suite for Discrete Black-Box Optimization: Profiling $(1+\lambda)$ EA Variants on OneMax and LeadingOnes
  Proc. of Genetic and Evolutionary Computation Conference (GECCO 2018), pages 951-958, ACM, 2018.
  
  
• [GECCO 2018] Carola Doerr, Markus Wagner
  On the Effectiveness of Simple Success-Based Parameter Selection Mechanisms for Two Classical Discrete Black-Box Optimization Benchmark Problems
  Proc. of Genetic and Evolutionary Computation Conference (GECCO 2018), pages 943-950, ACM, 2018.
  arxiv version.
  
  
• [GECCO 2018] Aneta Neumann, Wanru (Kelly) Gao, Carola Doerr, Frank Neumann, Markus Wagner
  Discrepancy-based Evolutionary Diversity Optimization
  Proc. of Genetic and Evolutionary Computation Conference (GECCO 2018), pages 991-998, ACM, 2018.
  arxiv version.
  
  
• [EA 2017] Eduardo Carvalho Pinto, Carola Doerr.
  Towards a More Practice-Aware Runtime Analysis
  Proc. of Artificial Evolution (EA 2017), pages 298-305, 2017.
  Official link.
  
  
• [GECCO 2017] Benjamin Doerr, Carola Doerr, Timo Kötzing
  Unknown Solution Length Problems With No Asymptotically Optimal Run Time
  Proc. of Genetic and Evolutionary Computation Conference (GECCO 2017), pages 1367-1374, ACM, 2017.
  Official link.
  
  
• [PPSN 2016] Benjamin Doerr, Carola Doerr, Jing Yang
  $k$-Bit Mutation with Self-Adjusting $k$ Outperforms Standard Bit Mutation
  Proc. of 14th International Conference on Parallel Problem Solving from Nature (PPSN 2016), pages 824-834, Springer, 2016.
  Official link.
  
  
• [PPSN 2016] Benjamin Doerr, Carola Doerr, Timo Kötzing
  Provably Optimal Self-Adjusting Step Sizes for Multi-Valued Decision Variables
  Proc. of 14th International Conference on Parallel Problem Solving from Nature (PPSN 2016), pages 782-791, Springer, 2016.
  Official link.
  
  
• [GECCO 2016] Carola Doerr, Johannes Lengler
  The (1+1) Elitist Black-Box Complexity of LeadingOnes
  Proc. of Genetic and Evolutionary Computation Conference (GECCO 2016), pages 1131-1138, ACM, 2016.
  Best paper award (Tracks ACO-SI + CO + THEORY).
  Official link.
  
  
• [GECCO 2016] Benjamin Doerr, Carola Doerr, Jing Yang
  Optimal Parameter Choices via Precise Black-Box Analysis
  Proc. of Genetic and Evolutionary Computation Conference (GECCO 2016), pages 1123-1130, ACM, 2016.
  Official link.
  
  
• [GECCO 2016] Benjamin Doerr, Carola Doerr and Timo Kötzing
  The Right Mutation Strength for Multi-Valued Decision Variables
  Proc. of Genetic and Evolutionary Computation Conference (GECCO 2016), pages 1115-1122, ACM, 2016.
  Official link.
  
  
• [GECCO 2015] Benjamin Doerr, Carola Doerr
  Optimal Parameter Choices Through Self-Adjustment: Applying the 1/5-th Rule in Discrete Settings
  Proc. of Genetic and Evolutionary Computation Conference (GECCO 2015), pages 1335-1342, ACM, 2015.
  Official link.
  
  
• [GECCO 2015] Benjamin Doerr, Carola Doerr, Timo Kötzing
  Solving Problems with Unknown Solution Length at (Almost) No Extra Cost
  Proc. of Genetic and Evolutionary Computation Conference (GECCO 2015), pages 831-838, ACM, 2015.
  Official link.
  
  
• [GECCO 2015] Carola Doerr, Johannes Lengler
  Elitist Black-Box Models: Analyzing the Impact of Elitist Selection on the Performance of Evolutionary Algorithms
  Proc. of Genetic and Evolutionary Computation Conference (GECCO 2015), pages 839-846, ACM, 2015.s
  Official link.
  
  
• [GECCO 2015] Carola Doerr, Johannes Lengler
  OneMax in Black-Box Models with Several Restrictions
  Proc. of Genetic and Evolutionary Computation Conference (GECCO 2015), pages 1431-1438, ACM, 2015.
  Official link.
  
  
• [GECCO 2015] Benjamin Doerr, Carola Doerr
  A Tight Runtime Analysis of the $(1+(\lambda, \lambda))$ Genetic Algorithm on OneMax
  Proc. of Genetic and Evolutionary Computation Conference (GECCO 2015), pages 1423-1430, ACM, 2015.
  Official link.
  
  
• [GECCO 2015] Axel de Perthuis de Laillevault, Benjamin Doerr, Carola Doerr
  Money for Nothing: Speeding Up Evolutionary Algorithms Through Better Initialization
  Proc. of Genetic and Evolutionary Computation Conference (GECCO 2015), pages 815-822, ACM, 2015.
  Official link.
  
  
• [GECCO 2014] Benjamin Doerr, Carola Doerr
  The Impact of Random Initialization on the Runtime of Randomized Search Heuristics
  Proc. of Genetic and Evolutionary Computation Conference (GECCO 2014), pages 1375-1382, ACM, 2014.
  Official link.
  
  
• [GECCO 2014] Benjamin Doerr, Carola Doerr, Timo Kötzing
  Unbiased Black-Box Complexities of Jump Functions---How to Cross Large Plateaus
  Proc. of Genetic and Evolutionary Computation Conference (GECCO 2014), pages 769-776, ACM, 2014.
  Official link.
  
  
• [ESA 2013] Andrea Clementi, Pierluigi Crescenzi, Carola Doerr, Pierre Fraigniaud, Marco Isopi, Alessandro Panconesi, Francesco Pasquale, Riccardo Silvestri.
  Rumor Spreading in Random Evolving Graphs.
  Proc. of the 21st European Symposium on Algorithms (ESA 2013). LNCS 8125, pages 325-336, Springer, 2013.
  Official link., arXiv version.
  
  
• [WG 2013] Carola Doerr, Jens M. Schmidt, G. Ramakrishna
  Computing Minimum Cycle Bases in Weighted Partial 2-Trees in Linear Time.
  Proc. of the 39th International Workshop on Graph-Theoretic Concepts in Computer Science (WG 2013). LNCS 8165, pages 225-236, Springer 2013.
  Official link., arXiv version.
  
  
• [GECCO 2013] Carola Doerr, François-Michel De Rainville.
  Constructing Low Star Discrepancy Point Sets with Genetic Algorithms
  Proc. of Genetic and Evolutionary Computation Conference (GECCO 2013), pages 789-796, ACM, 2013.
  Official link., arXiv version.
  
  
• [GECCO 2013] Benjamin Doerr, Carola Doerr, Franziska Ebel.
  Lessons From the Black-Box: Fast Crossover-Based Genetic Algorithms
  Proc. of Genetic and Evolutionary Computation Conference (GECCO 2013), pages 781-788, ACM, 2013.
  Best paper award (Genetic Algorithms track).
  Official link.
  
  
• [SODA 2013] Benjamin Doerr, Reto Spöhel, Henning Thomas, Carola Winzen.
  Playing Mastermind with Many Colors
  Proc. of ACM-SIAM Symposium on Discrete Algorithms (SODA 2013), pages 695-704, SIAM Society for Industrial and Applied Mathematics, 2013.
  Official link. arXiv version.
  
  
• [LNCS 2013] Peyman Afshani, Manindra Agrawal, Benjamin Doerr, Carola Doerr, Kasper Green Larsen, Kurt Mehlhorn.
  The Query Complexity of Finding a Hidden Permutation.
  Space-Efficient Data Structures, Streams, and Algorithms - Papers in Honor of J. Ian Munro on the Occasion of His 66th Birthday. LNCS 8066, pages 1-11, Springer, 2013.
  official link, ECCC version.
  
  
• [WINE 2012] Xujin Chen, Benjamin Doerr, Xiaodong Hu, Weidong Ma, Rob van Stee, Carola Winzen.
  The Price of Anarchy for Selfish Ring Routing is Two
  Proc. of the 8th Workshop on Internet & Network Economics (WINE 2012), pages 420-433, LNCS 7695, Springer, 2012.
  Official link. arXiv version.
  
  
• [GECCO 2012] Benjamin Doerr, Carola Winzen.
  Reducing the Arity in Unbiased Black-Box Complexity
  Proc. of Genetic and Evolutionary Computation Conference (GECCO 2012), pages 1309-1316, ACM, 2012.
  Best paper award (Theory track). The paper has been invited to a fast-track publication in Evolotionary Computation (declined) and to the TCS special issue.
  Official link. arXiv version.
  
  
• [STACS 2012] Benjamin Doerr, Carola Winzen.
  Playing Mastermind With Constant-Size Memory
  Proc. of Symposium on Theoretical Aspects of Computer Science (STACS 2012), pages 441-452, LIPIcs, 2012.
  Official link. arXiv version. The paper has been invited to the ToCS special issue.
  
  
• [GECCO 2011] Benjamin Doerr, Timo Kötzing, Carola Winzen.
  Too Fast Unbiased Black-Box Algorithms
  Proc. of Genetic and Evolutionary Computation Conference (GECCO 2011), pages 2043-2050, ACM, 2011.
  official link.
  
  
• [GECCO 2011] Benjamin Doerr, Timo Kötzing, Johannes Lengler, Carola Winzen.
  Black-Box Complexities of Combinatorial Problems
  Proc. of Genetic and Evolutionary Computation Conference (GECCO 2011), pages 981-988, ACM, 2011.
  official link. arXiv version.
  
  
• [CSR 2011] Benjamin Doerr, Carola Winzen.
  Towards a Complexity Theory of Randomized Search Heuristics: Ranking-Based Black-Box Complexity
  Proc. of 6th International Computer Science Symposium in Russia (CSR 2011), pages 15-28, LNCS, Springer, 2011.
  official link. arXiv version.
  
  
• [EA 2011] Benjamin Doerr, Carola Winzen.
  Black-Box Complexity: Breaking the O(n log n) Barrier of LeadingOnes
  Proceedings of Artificial Evolution (EA 2011), pages 205-216, LNCS 7401, Springer, 2012.
  official link. arXiv version.
  
  
• [FOGA 2011] Benjamin Doerr, Daniel Johannsen, Timo Kötzing, Per Kristian Lehre, Markus Wagner, Carola Winzen.
  Faster Black-Box Algorithms Through Higher Arity Operators
  Proc. of Foundations of Genetic Algorithms XI (FOGA 2011), pages 163-172, ACM, 2011.
  official link. arXiv version.
  
  
• [PPSN 2010] Benjamin Doerr, Thomas Jansen, Dirk Sudholt, Carola Winzen, Christine Zarges.
  Optimizing Monotone Functions Can Be Difficult
  Proc. of Parallel Problem Solving from Nature (PPSN 2010). LNCS 6238, pages 42-51, Springer, 2010.
  official link. arXiv version.
  
  
• [GECCO 2010] Benjamin Doerr, Daniel Johannsen, Carola Winzen.
  Multiplicative Drift Analysis
  Proc. of Genetic and Evolutionary Computation Conference (GECCO 2010), pages 1449-1456, ACM, 2010.
  Best paper award (Theory track). The paper has been invited to the Algorithmica special issue.
  official link. arXiv version.
  
  
• [CEC 2010] Benjamin Doerr, Daniel Johannsen, Carola Winzen.
  Drift Analysis and Linear Functions Revisited
  Proc. of the IEEE Congress on Evolutionary Computation (CEC 2010), pages 1967-1974, IEEE, 2010.
  official link.
  
  

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Poster Papers

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• [GECCO 2023, poster paper] Carolin Benjamins, Elena Raponi, Anja Jankovic, Carola Doerr, Marius Lindauer
  Towards Self-Adjusting Weighted Expected Improvement for Bayesian Optimization
  Proc. of Genetic and Evolutionary Computation Conference (GECCO 2023, Companion Material), pages tbd, ACM, 2023. To appear.
  Extended arXiv version (to appear in Proc. of AutoML 2023)
  
  
• [GECCO 2023, poster paper] Ana Kostovska, Anja Jankovic, Diederick Vermetten, Sašo Džeroski, Tome Eftimov, Carola Doerr
  Comparing Algorithm Selection Approaches on Black-Box Optimization Problems
  Proc. of Genetic and Evolutionary Computation Conference (GECCO 2023, Companion Material), pages tbd, ACM, 2023. To appear.
  arXiv version to be published soon. Please just send me an e-mail if you are interested in the PDF.
  
  
• [GECCO 2023, poster paper] Ana Nikolikj, Gjorgjina Cenikj, Gordana Ispirova, Diederick Vermetten, Ryan Dieter Lang, Andries Engelbrecht, Carola Doerr, Peter Korošec, Tome Eftimov
  Assessing the Generalizability of a Performance Predictive Model
  Proc. of Genetic and Evolutionary Computation Conference (GECCO 2023, Companion Material), pages tbd, ACM, 2023. To appear.
  arXiv version
  
  
• [GECCO 2021, poster paper] Furong Ye, Carola Doerr, Thomas Bäck
  Leveraging Benchmarking Data for Informed One-Shot Dynamic Algorithm Selection
  Proc. of Genetic and Evolutionary Computation Conference (GECCO 2021, Companion Material), pages 245-246, ACM, 2021.
  arXiv version
  
  
• [GECCO 2021, poster paper] Ana Kostovska, Diederick Vermetten, Carola Doerr, Sašo Džeroski, Panče Panov, Tome Eftimov
  OPTION: OPTImization Algorithm Benchmarking ONtology
  Proc. of Genetic and Evolutionary Computation Conference (GECCO 2021, Companion Material), pages 239-240, ACM, 2021.
  poster version on arXiv, extended version on arXiv.
  
  
• [GECCO 2019, Poster] Nathan Buskulic, Carola Doerr.
  Maximizing Drift is Not Optimal for Solving OneMax
  Proc. of Genetic and Evolutionary Computation Conference (GECCO 2019, Companion material), pages 425-426, ACM, 2019.
  preliminary version on arXiv.
  
  

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Workshop Papers

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• [AutoML 2024] Matt van den Nieuwenhuijzen, Carola Doerr, Henry Gouk, Jan van Rijn
  Selecting Pre-trained Models for Transfer Learning with Data-centric Meta-features
  openreview (has free access to PDF)
  
  
• [GECCO 2023, student workshop] Maria Laura Santoni, Elena Raponi, Renato De Leone, Carola Doerr
  Comparison of Bayesian Optimization Algorithms for BBOB Problems in Dimensions 10 and 60
  arXiv version
  
  
• [NeurIPS 2022] Carolin Benjamins, Anja Jankovic, Elena Raponi, Koen van der Blom, Marius Lindauer, Carola Doerr
  Towards Automated Design of Bayesian Optimization via Exploratory Landscape Analysis
  NeurIPS Workshop on Meta-Learning.
  arXiv version
  
  
• [NeurIPS 2022] Carolin Benjamins, Elena Raponi, Anja Jankovic, Koen van der Blom, Maria Laura Santoni, Marius Lindauer, Carola Doerr
  PI is back! Switching Acquisition Functions in Bayesian Optimization
  NeurIPS Workshop on Gaussian Processes, Spatiotemporal Modeling, and Decision-making Systems.
  arXiv version
  
  
• [GECCO 2021] Jacob de Nobel, Diederick Vermetten, Hao Wang, Carola Doerr, Thomas Bäck
  Tuning as a Means of Assessing the Benefits of New Ideas in Interplay with Existing Algorithmic Modules
  Companion Material of Proc. of Genetic and Evolutionary Computation Conference (GECCO 2021), pages 1375-1384, ACM, 2021.
  arXiv version
  
  
• [GECCO 2021] Amine Aziz-Alaoui, Carola Doerr, Johann Dreo
  Towards Large Scale Automated Algorithm Design by Integrating Modular Benchmarking Frameworks
  Companion Material of Proc. of Genetic and Evolutionary Computation Conference (GECCO 2021), pages 1365-1374, ACM, 2021.
  arXiv version
  
  
• [GECCO 2019, UMLOP workshop] Carola Doerr, Johann Dreo, Pascal Kerschke.
  Making a Case for (Hyper-)Parameter Tuning as Benchmark Problems
  Companion Material of Proc. of Genetic and Evolutionary Computation Conference (GECCO 2019), pages 1755-1764, ACM, 2019.
  
  
• [GECCO 2019, LAHS workshop] Johann Dreo, Carola Doerr, Yann Semet.
  Coupling the Design of Benchmark with Algorithm in Landscape-Aware Solver Design
  Companion Material of Proc. of Genetic and Evolutionary Computation Conference (GECCO 2019), pages 1419-1420, ACM, 2019.
  
  
• [GECCO 2019, BB-DOB workshop] Carola Doerr, Furong Ye, Naama Horesh, Hao Wang, Ofer M. Shir, Thomas Bäck
  Benchmarking Discrete Optimization Heuristics with IOHprofiler
  Companion Material of Proc. of Genetic and Evolutionary Computation Conference (GECCO 2019), pages 1798-1806, ACM, 2019.
  
  
• [GECCO 2019, BB-DOB workshop] Borja Calvo, Ofer M. Shir, Josu Ceberio, Carola Doerr, Hao Wang, Thomas Bäck, Jose A. Lozano.
  Bayesian Performance Analysis for Black-Box Optimization Benchmarking
  Companion Material of Proc. of Genetic and Evolutionary Computation Conference (GECCO 2019), pages 1789-1797, ACM, 2019.
  
  
• [GECCO 2019, BB-DOB workshop] Ivan Ignashov, Arina Buzdalova, Maxim Buzdalov, Carola Doerr.
  Illustrating the Trade-Off between Time, Quality, and Success Probability in Heuristic Search
  Companion Material of Proc. of Genetic and Evolutionary Computation Conference (GECCO 2019), pages 1807-1812, ACM, 2019.
  
  
• [GECCO 2019, student workshop] Anja Jankovic, Carola Doerr.
  Adaptive Landscape Analysis
  Companion Material of Proc. of Genetic and Evolutionary Computation Conference (GECCO 2019), pages 2032-2035, ACM, 2019.
  
  
• [GECCO 2019, student workshop] Quentin Reneau, Johann Dreo, Carola Doerr, Benjamin Doerr.
  Expressiveness and Robustness of Landscape Features
  Companion Material of Proc. of Genetic and Evolutionary Computation Conference (GECCO 2019), pages 2048-2051, ACM, 2019.
  
  
• [GECCO 2019, student workshop] Dimitry Vinokurov, Maxim Buzdalov, Arina Buzdalova, Benjamin Doerr, Carola Doerr.
  Fixed-Target Runtime Analysis of the (1+1) EA with Resampling
  Companion Material of Proc. of Genetic and Evolutionary Computation Conference (GECCO 2019), pages 2068-2071, ACM, 2019.
  
  
• [GECCO 2018, BB-DOB workshop] Ofer M. Shir, Carola Doerr, Thomas Bäck
  Compiling a benchmarking test-suite for combinatorial black-box optimization: a position paper
  Companion Material of Proc. of Genetic and Evolutionary Computation Conference (GECCO 2018), pages 1753-1760, ACM, 2018.
  
  
• [AlgoTel 2013] Andrea Clementi, Pierluigi Crescenzi, Carola Doerr, Pierre Fraigniaud, Francesco Pasquale, Riccardo Silvestri,
  Diffusion probabiliste dans les reseaux dynamiques (short version of our paper "Rumor Spreading in Random Evolving Graphs").
  Proc. of the 15èmes Rencontres Francophones pour les Aspects Algorithmiques des Télécommunications (AlgoTel 2013).
  prix du meilleur article.
  
  
• [CTW 2012] Benjamin Doerr, Reto Spöhel, Henning Thomas, Carola Winzen.
  Playing Mastermind with Many Colors
  Short abstract in Proc. of the 11th Cologne-Twente Workshop on Graphs and Combinatorial Optimization (CTW 2012).
  
  

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Preprints (non-exhaustive list)

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• [arXiv 2024] Maria Laura Santoni, Elena Raponi, Aneta Neumann, Frank Neumann, Mike Preuss, Carola Doerr
  Illuminating the Diversity-Fitness Trade-Off in Black-Box Optimization
  arXiv version
  
  
• [arXiv 2023] François Clément, Carola Doerr, Kathrin Klamroth, Luís Paquete
  Constructing Optimal L-infinity Star Discrepancy Sets
  arXiv version
  
  
• [bioRxiv 2023] Océane Fourquet, Martin S. Krejca, Carola Doerr, Benno Schwikowski
  Fast Identification of Optimal Monotonic Classifiers
  bioRxiv version
  
  
• [in preparation 2023] Alexis Robbes, Carola Doerr
  On the Difficulty of Tuning Generalized Mutation Operators for the (1+1) Evolutionary Algorithm Optimizing W-model Functions
  in preparation. Happy to share a preliminary version upon request.
  
  
• [arXiv 2020] Noor Awad, Gresa Shala, Difan Deng, Neeratyoy Mallik, Matthias Feurer, Katharina Eggensperger, Andre Biedenkapp, Diederick Vermetten, Hao Wang, Carola Doerr, Marius Lindauer, Frank Hutter
  Squirrel: A Switching Hyperparameter Optimizer
  arXiv version
  1st and 3rd rank at the black-box optimization challenge at NeurIPS 2020
  
  
• [arXiv 2020] Thomas Bartz-Beielstein, Carola Doerr, Daan van den Berg, Jakob Bossek, Sowmya Chandrasekaran, Tome Eftimov, Andreas Fischbach, Pascal Kerschke, William La Cava, Manuel Lopez-Ibanez, Katherine M. Malan, Jason H. Moore, Boris Naujoks, Patryk Orzechowski, Vanessa Volz, Markus Wagner, Thomas Weise
  Benchmarking in Optimization: Best Practice and Open Issues
  arXiv version
  
  
• [arXiv 2018] Carola Doerr, Hao Wang, Furong Ye, Sander van Rijn, Thomas Bäck
  IOHprofiler: A Benchmarking and Profiling Tool for Iterative Optimization Heuristics
  arXiv version
  
  

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Theses

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• [HDR 2020] Carola Doerr.
  Theory of Iterative Optimization Heuristics: From Black-Box Complexity over Algorithm Design to Parameter Control
  HDR manuscript
  
  
• [PhD 2011] Carola Winzen.
  Toward a Complexity Theory for Randomized Search Heuristics: Black-Box Models
  Dissertation. Universität des Saarlandes, Saarbrücken, Germany, 2011.
  The thesis has been awarded the Otto Hahn Medal of the Max-Planck-Society
  If you are interested in the thesis or the slides, please send me a mail. I will be happy to share it.
  Here is a short (non-scientific) article about my thesis (in German). This one here (also in German) is a bit more detailed.
  
  
• [Diplom 2007] Carola Winzen.
  Approximative Berechnung der Sterndiskrepanz
  Diplomarbeit. Christian-Albrechts-Universität zu Kiel, 2007.
  Published version: Approximative Berechnung der Sterndiskrepanz: Theorie und Heuristik. VDM Verlag Dr. Müller, 2010.
  If you are interested in the thesis, please send me a mail. I will be happy to share it. Please note that the thesis is in German.
  
  

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Published Tutorials

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• [Tutorial GECCO 2023] Carola Doerr, Hao Wang, Diederick Vermetten, Thomas Bäck, Jacob de Nobel, Furong Ye.
  Benchmarking and Analyzing Iterative Optimization Heuristics with IOHprofiler.
  Slides of the tutorial held at GECCO 2023
  Companion Material Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2023), pages 938-945, ACM, 2023.
  Official link
  
  
• [Tutorial GECCO 2022] Carola Doerr, Hao Wang, Diederick Vermetten, Thomas Bäck, Jacob de Nobel, Furong Ye.
  Benchmarking and Analyzing Iterative Optimization Heuristics with IOHprofiler.
  Slides of the tutorial held at GECCO 2022
  Companion Material Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2022), pages 1334-1341, ACM, 2022.
  
  
• [Tutorial GECCO 2020] Thomas Bäck, Carola Doerr, Ofer Shir, Hao Wang.
  Benchmarking and Analyzing Iterative Optimization Heuristics with IOHprofiler.
  Slides of the tutorial held at GECCO 2020
  Companion Material Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2020), pages 1043-1054, ACM, 2020.
  
  
• [Tutorial GECCO 2020] Gregor Papa, Carola Doerr.
  Dynamic Control Parameter Choices in Evolutionary Computation.
  Slides of the tutorial held at GECCO 2020
  Companion Material Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2020), pages 927-956, ACM, 2020.
  
  
• [Tutorial GECCO 2019] Carola Doerr.
  Dynamic Parameter Choices in Evolutionary Computation.
  Slides of the tutorial held at GECCO 2019
  Companion Material Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2019), pages 890-922, ACM, 2019.
  
  
• [Tutorial GECCO 2018] Carola Doerr.
  Dynamic Parameter Choices in Evolutionary Computation.
  Slides of the tutorial held at GECCO 2018
  Companion Material Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2018), pages 800--830, ACM, 2018.
  Updated Slide Deck, Official link
  
  
• [Tutorial GECCO 2017] Carola Doerr.
  Dynamic Parameter Choices in Evolutionary Computation.
  Slides of the tutorial held at GECCO 2017
  Companion Material Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2017), pages 736--761, ACM, 2017.
  Preliminary version, Official link
  
  
• [Tutorial GECCO 2016] Benjamin Doerr, Carola Doerr.
  Theory for Non-Theoreticians.
  Slides of the tutorial held at GECCO 2016
  Companion Material Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2016), pages 463--482, ACM, 2016.
  Official link
  
  
• [Tutorial GECCO 2014] Benjamin Doerr, Carola Doerr.
  Black-box complexity: from complexity theory to playing Mastermind.
  Slides of the tutorial held at GECCO 2014
  Companion Material Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2014), pages 623-646, ACM, 2014.
  Official link
  
  
• [Tutorial GECCO 2013] Benjamin Doerr, Carola Doerr.
  Black-box complexity: from complexity theory to playing Mastermind.
  Slides of the tutorial held at GECCO 2013
  Companion Material Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2013), pages 617-640, ACM, 2013.
  Official link
  
  

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Miscellaneous

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• [SIGEVOlution 2021] Thomas Bäck, Pauline Bennet, Jacob de Nobel, Carola Doerr, Johann Dreo, Herilalaina Rakotoarison, Jeremy Rapin, Olivier Teytaud, Diederick Vermetten, Hao Wang, Furong Ye
  Results from the Joint Nevergrad and IOHprofiler Open Optimization Competition 2021
  SIGEVOlution newsletter, volume 14, issue 4, available here
  
  
• [SIGEVOlution 2021] Pauline Bennet, Carola Doerr, Antoine Moreau, Jeremy Rapin, Fabien Teytaud, Olivier Teytaud
  Nevergrad: Black-Box Optimization Platform
  SIGEVOlution newsletter, volume 14, issue 1, available here
  
  
• [Images des Mathématiques 2018] Carola Doerr
  Optimisation Inspirée par la Nature.
  Images des Mathématiques, CNRS, 2018.
  available here
  
  
• [PPSN Tutorials 2018] Gisele Lobo Pappa, Michael T. M. Emmerich et al.
  Tutorials at PPSN 2018.
  Proc. of Parallel Problem Solving from Nature (PPSN 2018), Lecture Notes in Computer Science LNCS 11102, pages 477-489, Springer, 2018.
  
  
• [PPSN Tutorials 2016] Carola Doerr, Nicolas Bredeche et al.
  Tutorials at PPSN 2016.
  Proc. of Parallel Problem Solving from Nature (PPSN 2016), Lecture Notes in Computer Science LNCS 9921, pages 1012-1022, Springer, 2016.
  
  
• [Women@GECCO 2016] Carola Doerr, Julia Handl, Emma Hart, Gabriela Ochoa, Amarda Shehu, Tea Tusar, Anya E. Vostinar, Christine Zarges, A. Nur Zincir-Heywood.
  Women@GECCO 2016 Chairs' Welcome.
  Companion Material Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2014), pages 1447-1449, ACM, 2016.
  
  
• [Women@GECCO 2014] Una-May O'Reilly, Anna Esparcia-Alcázar, Anne Auger, Carola Doerr, Anikó Ekárt, Gabriela Ochoa.
  Women@GECCO 2014.
  Companion Material Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2014), pages 1487-1488, ACM, 2014.
  
  
• [ROADEF 2013] Carola Doerr.
  How Mastermind Helps us Understand Randomized Search Heuristics
  Invited article in the Newsletter of the ROADEF, the Société française de Recherche Opérationnelle et d'Aide à la Décision.
  
  
• [Non Science 2012] Carola Doerr.
  This is a short (non-scientific) article about my PhD thesis (in German).
  
  
• [GI Diss 2011] Carola Doerr.
  Entwicklung einer Komplexitätstheorie für randomisierte Suchheuristiken: Black-Box-Modelle
  "Ausgezeichnete Informatikdissertationen 2011", LNI 2012, pages 281-290.