# Research Interests

I like getting to the core of things. More specifically, I am interested in the complexity of discrete processes and the reasons behind their complexity. Currently, my main focus is on the analysis of randomized processes. However, I am also interested in complexity theory and game theory, where complexity seems to emerge from simple concepts. For all of these settings, I am not only interested in the complexity alone but also in the analysis and development of methods and tools used in order to derive good run time results.

# Publications

2021 [ nach oben ]

- A Simplified Run Time Analysis of the Univariate Marginal Distribution Algorithm on LeadingOnes. Theoretical Computer Science 2021: 121-128

2020 [ nach oben ]

- Lower Bounds on the Run Time of the Univariate Marginal Distribution Algorithm on OneMax. Theoretical Computer Science 2020: 143-165
- Significance-based Estimation-of-Distribution Algorithms. Transactions on Evolutionary Computation 2020: 1025-1034
- Theory of Estimation-of-Distribution Algorithms. Theory of Evolutionary Computation: Recent Developments in Discrete Optimization 2020: 405-442
- The Univariate Marginal Distribution Algorithm Copes Well With Deception and Epistasis. Evolutionary Computation in Combinatorial Optimisation (EvoCOP) 2020: 51-66Best-Paper Award
- Bivariate Estimation-of-Distribution Algorithms Can Find an Exponential Number of Optima. Genetic and Evolutionary Computation Conference (GECCO) 2020: 796–804
- Memetic Genetic Algorithms for Time Series Compression by Piecewise Linear Approximation. International Conference on Neural Information Processing (ICONIP) 2020: 592-604

2019 [ nach oben ]

- Routing for On-Street Parking Search using Probabilistic Data. AI Communications 2019: 113-124
- Surfing on the seascape: Adaptation in a changing environment. Evolution: International Journal of Organic Evolution 2019: 1356-1374
- Unbiasedness of Estimation-of-Distribution Algorithms. Theoretical Computer Science 2019: 46-59
- First-hitting times under drift. Theoretical Computer Science 2019: 51-69
- Mixed Integer Programming versus Evolutionary Computation for Optimizing a Hard Real-World Staff Assignment Problem. International Conference on Automated Planning and Scheduling (ICAPS) 2019: 541-554

2018 [ nach oben ]

- Escaping Local Optima Using Crossover with Emergent Diversity. Transactions on Evolutionary Computation 2018: 484-497
- Significance-based Estimation-of-Distribution Algorithms. Genetic and Evolutionary Computation Conference (GECCO) 2018: 1483-1490
- First-Hitting Times for Finite State Spaces. Parallel Problem Solving From Nature (PPSN) 2018: 79-91
- First-Hitting Times Under Additive Drift. Parallel Problem Solving From Nature (PPSN) 2018: 92-104
- Memory-restricted Routing With Tiled Map Data. Systems, Man, and Cybernetics (SMC) 2018: 3347-3354

2017 [ nach oben ]

- The Compact Genetic Algorithm is Efficient under Extreme Gaussian Noise. Transactions on Evolutionary Computation 2017: 477-490
- Lower Bounds on the Run Time of the Univariate Marginal Distribution Algorithm on OneMax. Foundations of Genetic Algorithms (FOGA) 2017: 65-79

2016 [ nach oben ]

- Robustness of Ant Colony Optimization to Noise. Evolutionary Computation 2016: 237-254
- Probabilistic Routing for On-Street Parking Search. European Symposium on Algorithms (ESA) 2016: 6:1-6:13
- The Benefit of Recombination in Noisy Evolutionary Search. Genetic and Evolutionary Computation Conference (GECCO) 2016: 161-162
- Escaping Local Optima with Diversity Mechanisms and Crossover. Genetic and Evolutionary Computation Conference (GECCO) 2016: 645-652
- Fast Building Block Assembly by Majority Vote Crossover. Genetic and Evolutionary Computation Conference (GECCO) 2016: 661-668
- EDAs cannot be Balanced and Stable. Genetic and Evolutionary Computation Conference (GECCO) 2016: 1139-1146
- Graceful Scaling on Uniform versus Steep-Tailed Noise. Parallel Problem Solving From Nature (PPSN) 2016: 761-770
- Emergence of Diversity and its Benefits for Crossover in Genetic Algorithms. Parallel Problem Solving From Nature (PPSN) 2016: 890-900

2015 [ nach oben ]

- Robustness of Ant Colony Optimization to Noise. Genetic and Evolutionary Computation Conference (GECCO) 2015: 17-24Best-Paper Award (ACO/SI Track)
- The Benefit of Recombination in Noisy Evolutionary Search. International Symposium of Algorithms and Computation (ISAAC) 2015: 140-150