The Benefit of Sex in Noisy Evolutionary Search. - Tobias Friedrich 001; Timo Kötzing; Martin S. Krejca; Andrew M. Sutton (CoRR, 2015)

Probabilistic Routing for On-Street Parking Search. - Tobias Arndt; Danijar Hafner; Thomas Kellermeier; Simon Krogmann; Armin Razmjou; Martin S. Krejca; Ralf Rothenberger; Tobias Friedrich 001 (ESA, 2016)

Escaping Local Optima with Diversity Mechanisms and Crossover. - Duc-Cuong Dang; Tobias Friedrich 001; Timo Kötzing; Martin S. Krejca; Per Kristian Lehre; Pietro S. Oliveto; Dirk Sudholt; Andrew M. Sutton (GECCO, 2016)

EDAs cannot be Balanced and Stable. - Tobias Friedrich 001; Timo Kötzing; Martin S. Krejca (GECCO, 2016)

Fast Building Block Assembly by Majority Vote Crossover. - Tobias Friedrich 001; Timo Kötzing; Martin S. Krejca; Samadhi Nallaperuma; Frank Neumann 001; Martin Schirneck (GECCO, 2016)

The Benefit of Recombination in Noisy Evolutionary Search. - Tobias Friedrich 001; Timo Kötzing; Martin S. Krejca; Andrew M. Sutton (GECCO (Companion), 2016)

Emergence of Diversity and Its Benefits for Crossover in Genetic Algorithms. - Duc-Cuong Dang; Tobias Friedrich 001; Timo Kötzing; Martin S. Krejca; Per Kristian Lehre; Pietro S. Oliveto; Dirk Sudholt; Andrew M. Sutton (PPSN, 2016)

Graceful Scaling on Uniform Versus Steep-Tailed Noise. - Tobias Friedrich 001; Timo Kötzing; Martin S. Krejca; Andrew M. Sutton (PPSN, 2016)

Escaping Local Optima using Crossover with Emergent or Reinforced Diversity. - Duc-Cuong Dang; Tobias Friedrich 001; Timo Kötzing; Martin S. Krejca; Per Kristian Lehre; Pietro S. Oliveto; Dirk Sudholt; Andrew M. Sutton (CoRR, 2016)

Robustness of Ant Colony Optimization to Noise. - Tobias Friedrich 001; Timo Kötzing; Martin S. Krejca; Andrew M. Sutton (Evol. Comput., 2016)

The Compact Genetic Algorithm is Efficient Under Extreme Gaussian Noise. - Tobias Friedrich 001; Timo Kötzing; Martin S. Krejca; Andrew M. Sutton (IEEE Trans. Evol. Comput., 2017)

First-Hitting Times for Finite State Spaces. - Timo Kötzing; Martin S. Krejca (PPSN (2), 2018)

First-Hitting Times Under Additive Drift. - Timo Kötzing; Martin S. Krejca (PPSN (2), 2018)

Memory-Restricted Routing with Tiled Map Data. - Thomas Bläsius; Jan Eube; Thomas Feldtkeller; Tobias Friedrich 001; Martin S. Krejca; J. A. Gregor Lagodzinski; Ralf Rothenberger; Julius Severin; Fabian Sommer; Justin Trautmann (SMC, 2018)

Intuitive Analyses via Drift Theory. - Andreas Göbel 001; Timo Kötzing; Martin S. Krejca (CoRR, 2018)

Theory of Estimation-of-Distribution Algorithms. - Martin S. Krejca; Carsten Witt (CoRR, 2018)

Escaping Local Optima Using Crossover With Emergent Diversity. - Duc-Cuong Dang; Tobias Friedrich 001; Timo Kötzing; Martin S. Krejca; Per Kristian Lehre; Pietro S. Oliveto; Dirk Sudholt; Andrew M. Sutton (IEEE Trans. Evol. Comput., 2018)

Mixed Integer Programming versus Evolutionary Computation for Optimizing a Hard Real-World Staff Assignment Problem. - Jannik Peters 001; Daniel Stephan; Isabel Amon; Hans Gawendowicz; Julius Lischeid; Lennart Salabarria; Jonas Umland; Felix Werner; Martin S. Krejca; Ralf Rothenberger; Timo Kötzing; Tobias Friedrich 001 (ICAPS, 2019)

Routing for on-street parking search using probabilistic data. - Tobias Friedrich 001; Martin S. Krejca; Ralf Rothenberger; Tobias Arndt; Danijar Hafner; Thomas Kellermeier; Simon Krogmann; Armin Razmjou (AI Commun., 2019)

Unbiasedness of estimation-of-distribution algorithms. - Tobias Friedrich 001; Timo Kötzing; Martin S. Krejca (Theor. Comput. Sci., 2019)

First-hitting times under drift. - Timo Kötzing; Martin S. Krejca (Theor. Comput. Sci., 2019)

Theoretical analyses of univariate estimation-of-distribution algorithms - Martin S. Krejca (2019)

Memetic Genetic Algorithms for Time Series Compression by Piecewise Linear Approximation. - Tobias Friedrich 001; Martin S. Krejca; J. A. Gregor Lagodzinski; Manuel Rizzo; Arthur Zahn (ICONIP (3), 2020)

Polymer dynamics via cliques with applications to hard-sphere mixtures. - Tobias Friedrich 001; Andreas Göbel 001; Martin S. Krejca; Marcus Pappik (CoRR, 2020)

Lower bounds on the run time of the Univariate Marginal Distribution Algorithm on OneMax. - Martin S. Krejca; Carsten Witt (Theor. Comput. Sci., 2020)

Significance-Based Estimation-of-Distribution Algorithms. - Benjamin Doerr; Martin S. Krejca (IEEE Trans. Evol. Comput., 2020)

Theory of Estimation-of-Distribution Algorithms. - Martin S. Krejca; Carsten Witt (Theory of Evolutionary Computation, 2020)

The Flip Schelling Process on Random Geometric and Erdös-Rényi Graphs. - Thomas Bläsius; Tobias Friedrich 001; Martin S. Krejca; Louise Molitor (CoRR, 2021)

Algorithms for general hard-constraint point processes via discretization. - Tobias Friedrich 001; Andreas Göbel 001; Maximilian Katzmann; Martin S. Krejca; Marcus Pappik (CoRR, 2021)

The Univariate Marginal Distribution Algorithm Copes Well with Deception and Epistasis. - Benjamin Doerr; Martin S. Krejca (Evol. Comput., 2021)

A simplified run time analysis of the univariate marginal distribution algorithm on LeadingOnes. - Benjamin Doerr; Martin S. Krejca (Theor. Comput. Sci., 2021)

Algorithms for Hard-Constraint Point Processes via Discretization. - Tobias Friedrich 001; Andreas Göbel 001; Maximilian Katzmann; Martin S. Krejca; Marcus Pappik (COCOON, 2022)

Theory-inspired parameter control benchmarks for dynamic algorithm configuration. - André Biedenkapp; Nguyen Dang 001; Martin S. Krejca; Frank Hutter; Carola Doerr (GECCO, 2022)

Escaping Local Optima with Local Search: A Theory-Driven Discussion. - Tobias Friedrich 001; Timo Kötzing; Martin S. Krejca; Amirhossein Rajabi (PPSN (2), 2022)

Accelerated Information Dissemination on Networks with Local and Global Edges. - Sarel Cohen; Philipp Fischbeck; Tobias Friedrich 001; Martin S. Krejca; Thomas Sauerwald (SIROCCO, 2022)

Using random graphs to sample repulsive Gibbs point processes with arbitrary-range potentials. - Tobias Friedrich 001; Andreas Göbel 001; Maximilian Katzmann; Martin S. Krejca; Marcus Pappik (CoRR, 2022)

A Spectral Independence View on Hard Spheres via Block Dynamics. - Tobias Friedrich 001; Andreas Göbel 001; Martin S. Krejca; Marcus Pappik (SIAM J. Discret. Math., 2022)

The Common-Neighbors Metric Is Noise-Robust and Reveals Substructures of Real-World Networks. - Sarel Cohen; Philipp Fischbeck; Tobias Friedrich 001; Martin S. Krejca (PAKDD (1), 2023)

The impact of geometry on monochrome regions in the flip Schelling process. - Thomas Bläsius; Tobias Friedrich 001; Martin S. Krejca; Louise Molitor (Comput. Geom., 2023)

Lasting Diversity and Superior Runtime Guarantees for the (μ+1) Genetic Algorithm. - Benjamin Doerr; Aymen Echarghaoui; Mohammed Jamal; Martin S. Krejca (CoRR, 2023)

Synergizing Theory and Practice of Automated Algorithm Design for Optimization (Dagstuhl Seminar 23332). - Diederick Vermetten; Martin S. Krejca; Marius Lindauer; Manuel López-Ibáñez 001; Katherine M. Malan (Dagstuhl Reports, 2023)

Polymer dynamics via cliques: New conditions for approximations. - Tobias Friedrich 001; Andreas Göbel 001; Martin S. Krejca; Marcus Pappik (Theor. Comput. Sci., 2023)

Bivariate estimation-of-distribution algorithms can find an exponential number of optima. - Benjamin Doerr; Martin S. Krejca (Theor. Comput. Sci., 2023)

Run Time Analysis for Random Local Search on Generalized Majority Functions. - Carola Doerr; Martin S. Krejca (IEEE Trans. Evol. Comput., 2023)

Evolutionary Minimization of Traffic Congestion. - Maximilian Böther; Leon Schiller; Philipp Fischbeck; Louise Molitor; Martin S. Krejca; Tobias Friedrich 001 (IEEE Trans. Evol. Comput., 2023)

The Irrelevance of Influencers: Information Diffusion with Re-Activation and Immunity Lasts Exponentially Long on Social Network Models. - Tobias Friedrich 001; Andreas Göbel 001; Nicolas Klodt; Martin S. Krejca; Marcus Pappik (AAAI, 2024)

Runtime Analysis of the (μ + 1) GA: Provable Speed-Ups from Strong Drift towards Diverse Populations. - Benjamin Doerr; Aymen Echarghaoui; Mohammed Jamal; Martin S. Krejca (AAAI, 2024)

From Market Saturation to Social Reinforcement: Understanding the Impact of Non-Linearity in Information Diffusion Models. - Tobias Friedrich 001; Andreas Göbel 001; Nicolas Klodt; Martin S. Krejca; Marcus Pappik (AAMAS, 2024)

Superior Genetic Algorithms for the Target Set Selection Problem Based on Power-Law Parameter Choices and Simple Greedy Heuristics. - Benjamin Doerr; Martin S. Krejca; Nguyen Vu (GECCO, 2024)

A Flexible Evolutionary Algorithm with Dynamic Mutation Rate Archive. - Martin S. Krejca; Carsten Witt (GECCO, 2024)

Proven Runtime Guarantees for How the MOEA/D: Computes the Pareto Front from the Subproblem Solutions. - Benjamin Doerr; Martin S. Krejca; Noé Weeks (PPSN (3), 2024)

Robust Parameter Fitting to Realistic Network Models via Iterative Stochastic Approximation. - Thomas Bläsius; Sarel Cohen; Philipp Fischbeck; Tobias Friedrich 001; Martin S. Krejca (CoRR, 2024)

Difficulties of the NSGA-II with the Many-Objective LeadingOnes Problem. - Benjamin Doerr; Dimitri Korkotashvili; Martin S. Krejca (CoRR, 2024)

Theory of Randomized Optimization Heuristics (Dagstuhl Seminar 24271). - Anne Auger; Tobias Glasmachers; Martin S. Krejca; Johannes Lengler; Alexander Jungeilges (Dagstuhl Reports, 2024)

Estimation-of-distribution algorithms for multi-valued decision variables. - Firas Ben Jedidia; Benjamin Doerr; Martin S. Krejca (Theor. Comput. Sci., 2024)

Robust Parameter Fitting to Realistic Network Models via Iterative Stochastic Approximation (Data and Code). - Thomas Bläsius; Sarel Cohen; Philipp Fischbeck; Tobias Friedrich 001; Martin S. Krejca (Zenodo, 2024)

Speeding Up the NSGA-II With a Simple Tie-Breaking Rule (Code). - Benjamin Doerr; Tudor Ivan; Martin S. Krejca (Zenodo, 2024)

Runtime Analysis for Multi-Objective Evolutionary Algorithms in Unbounded Integer Spaces (Code). - Benjamin Doerr; Martin S. Krejca; Günter Rudolph (Zenodo, 2024)

Speeding Up the NSGA-II with a Simple Tie-Breaking Rule. - Benjamin Doerr; Tudor Ivan; Martin S. Krejca (AAAI, 2025)

Runtime Analysis for Multi-Objective Evolutionary Algorithms in Unbounded Integer Spaces. - Benjamin Doerr; Martin S. Krejca; Günter Rudolph (AAAI, 2025)

Sampling repulsive Gibbs point processes using random graphs. - Tobias Friedrich 001; Andreas Göbel 001; Maximilian Katzmann; Martin S. Krejca; Marcus Pappik (Comb. Probab. Comput., 2025)

Runtime Analysis of the Compact Genetic Algorithm on the LeadingOnes Benchmark. - Marcel Chwialkowski; Benjamin Doerr; Martin S. Krejca (CoRR, 2025)

Tight Runtime Guarantees From Understanding the Population Dynamics of the GSEMO Multi-Objective Evolutionary Algorithm. - Benjamin Doerr; Martin S. Krejca; Andre Opris (CoRR, 2025)

Proven Approximation Guarantees in Multi-Objective Optimization: SPEA2 Beats NSGA-II. - Yasser Alghouass; Benjamin Doerr; Martin S. Krejca; Mohammed Lagmah (CoRR, 2025)