Search Results - "Doerr, Carola"

Self-Adjusting Mutation Rates with Provably Optimal Success Rules by Doerr, Benjamin, Doerr, Carola, Lengler, Johannes

“…The one-fifth success rule is one of the best-known and most widely accepted techniques to control the parameters of evolutionary algorithms. While it is often…”
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Tight Runtime Bounds for Static Unary Unbiased Evolutionary Algorithms on Linear Functions by Doerr, Carola, Janett, Duri Andrea, Lengler, Johannes

“…In a seminal paper in 2013, Witt showed that the (1+1) Evolutionary Algorithm with standard bit mutation needs time ( 1 + o ( 1 ) ) n ln n / p 1 to find the…”
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Fixed-Target Runtime Analysis by Buzdalov, Maxim, Doerr, Benjamin, Doerr, Carola, Vinokurov, Dmitry

“…Runtime analysis aims at contributing to our understanding of evolutionary algorithms through mathematical analyses of their runtimes. In the context of…”
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Black-Box Optimization Revisited: Improving Algorithm Selection Wizards Through Massive Benchmarking by Meunier, Laurent, Rakotoarison, Herilalaina, Wong, Pak Kan, Roziere, Baptiste, Rapin, Jeremy, Teytaud, Olivier, Moreau, Antoine, Doerr, Carola

“…Existing studies in black-box optimization suffer from low generalizability, caused by a typically selective choice of problem instances used for training and…”
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Optimal Static and Self-Adjusting Parameter Choices for the (1+(λ,λ)) Genetic Algorithm by Doerr, Benjamin, Doerr, Carola

“…The ( 1 + ( λ , λ ) )  genetic algorithm proposed in Doerr et al. (Theor Comput Sci 567:87–104, 2015 ) is one of the few examples for which a super-constant…”
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From black-box complexity to designing new genetic algorithms by Doerr, Benjamin, Doerr, Carola, Ebel, Franziska

“…Black-box complexity theory recently produced several surprisingly fast black-box optimization algorithms. In this work, we exhibit one possible reason: These…”
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The Impact of Random Initialization on the Runtime of Randomized Search Heuristics by Doerr, Benjamin, Doerr, Carola

“…Analyzing the runtime of a Randomized Search Heuristic (RSH) by theoretical means often turns out to be rather tricky even for simple optimization problems…”
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The (1+1) Elitist Black-Box Complexity of LeadingOnes by Doerr, Carola, Lengler, Johannes

“…One important goal of black-box complexity theory is the development of complexity models allowing to derive meaningful lower bounds for whole classes of…”
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Automated Configuration of Genetic Algorithms by Tuning for Anytime Performance by Ye, Furong, Doerr, Carola, Wang, Hao, Back, Thomas

“…Finding the best configuration of algorithms' hyperparameters for a given optimization problem is an important task in evolutionary computation. We compare in…”
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Preface to the Special Issue on Theory of Genetic and Evolutionary Computation by Doerr, Carola, Sudholt, Dirk

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OneMax in Black-Box Models with Several Restrictions by Doerr, Carola, Lengler, Johannes

“…Black-box complexity studies lower bounds for the efficiency of general-purpose black-box optimization algorithms such as evolutionary algorithms and other…”
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Run Time Analysis for Random Local Search on Generalized Majority Functions by Doerr, Carola, Krejca, Martin S.

“…Run time analysis of evolutionary algorithms recently makes significant progress in linking algorithm performance to algorithm parameters. However, settings…”
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Benchmarking discrete optimization heuristics with IOHprofiler by Doerr, Carola, Ye, Furong, Horesh, Naama, Wang, Hao, Shir, Ofer M., Bäck, Thomas

“…Automated benchmarking environments aim to support researchers in understanding how different algorithms perform on different types of optimization problems…”
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Using the Empirical Attainment Function for Analyzing Single-Objective Black-Box Optimization Algorithms by Lopez-Ibanez, Manuel, Vermetten, Diederick, Dreo, Johann, Doerr, Carola

“…A widely accepted way to assess the performance of iterative black-box optimizers is to analyze their empirical cumulative distribution function (ECDF) of…”
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Preface to the Special Issue on Theory of Genetic and Evolutionary Computation by Doerr, Carola, Chicano, Francisco

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Heuristic approaches to obtain low-discrepancy point sets via subset selection by Clément, François, Doerr, Carola, Paquete, Luís

“…Building upon the exact methods presented in our earlier work (2022) [5], we introduce a heuristic approach for the star discrepancy subset selection problem…”
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IOHexperimenter: Benchmarking Platform for Iterative Optimization Heuristics by de Nobel, Jacob, Ye, Furong, Vermetten, Diederick, Wang, Hao, Doerr, Carola, Bäck, Thomas

“…We present IOHexperimenter, the experimentation module of the IOHprofiler project. IOHexperimenter aims at providing an easy-to-use and customizable toolbox…”
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Guest Editorial Special Issue on Benchmarking Sampling-Based Optimization Heuristics: Methodology and Software by Back, Thomas, Doerr, Carola, Sendhoff, Bernhard, Stutzle, Thomas

“…Benchmarking provides an essential ground base for adequately assessing and comparing evolutionary computation methods and other optimization algorithms. It…”
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Static and Self-Adjusting Mutation Strengths for Multi-valued Decision Variables by Doerr, Benjamin, Doerr, Carola, Kötzing, Timo

“…The most common representation in evolutionary computation are bit strings. With very little theoretical work existing on how to use evolutionary algorithms…”
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Optimizing With Low Budgets: A Comparison On the Black-Box Optimization Benchmarking Suite and OpenAI Gym by Raponi, Elena, Rakotonirina, Nathanael Carraz, Rapin, Jeremy, Doerr, Carola, Teytaud, Olivier

“…The growing ubiquity of machine learning (ML) has led it to enter various areas of computer science, including black-box optimization (BBO). Recent research is…”
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