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- Publications
- Influence

Multiplicative drift analysis

- B. Doerr, D. Johannsen, Carola Doerr
- Computer Science
- GECCO
- 7 July 2010

Drift analysis is one of the strongest tools in the analysis of evolutionary algorithms. Its main weakness is that it is often very hard to find a good drift function. In this paper, we make progress… Expand

From black-box complexity to designing new genetic algorithms

- Benjamin Doerr, Carola Doerr, F. Ebel
- Computer Science, Mathematics
- Theor. Comput. Sci.
- 16 February 2015

Black-box complexity theory recently produced several surprisingly fast black-box optimization algorithms. In this work, we exhibit one possible reason: These black-box algorithms often profit from… Expand

Optimal Parameter Choices Through Self-Adjustment: Applying the 1/5-th Rule in Discrete Settings

- B. Doerr, Carola Doerr
- Computer Science
- GECCO '15
- 13 April 2015

While evolutionary algorithms are known to be very successful for a broad range of applications, the algorithm designer is often left with many algorithmic choices, for example, the size of the… Expand

Drift analysis and linear functions revisited

- Benjamin Doerr, D. Johannsen, Carola Doerr
- Mathematics, Computer Science
- IEEE Congress on Evolutionary Computation
- 18 July 2010

We regard the classical problem how the (1+1) Evolutionary Algorithm optimizes an arbitrary linear pseudo-Boolean function. We show that any such function is optimized in time (1 + o(1)) 1.39en ln… Expand

Multiplicative Drift Analysis

- Benjamin Doerr, D. Johannsen, Carola Doerr
- Computer Science, Mathematics
- GECCO '10
- 4 January 2011

We introduce multiplicative drift analysis as a suitable way to analyze the runtime of randomized search heuristics such as evolutionary algorithms. Our multiplicative version of the classical drift… Expand

Mutation Rate Matters Even When Optimizing Monotonic Functions

- Benjamin Doerr, T. Jansen, Dirk Sudholt, Carola Doerr, C. Zarges
- Computer Science, Mathematics
- Evolutionary Computation
- 1 March 2013

Extending previous analyses on function classes like linear functions, we analyze how the simple (1+1) evolutionary algorithm optimizes pseudo-Boolean functions that are strictly monotonic. These… Expand

k-Bit Mutation with Self-Adjusting k Outperforms Standard Bit Mutation

- B. Doerr, Carola Doerr, Jing Yang
- Computer Science
- PPSN
- 17 September 2016

When using the classic standard bit mutation operator, parent and offspring differ in a random number of bits, distributed according to a binomial law. This has the advantage that all Hamming… Expand

Calculation of Discrepancy Measures and Applications

- Carola Doerr, M. Gnewuch, Magnus Wahlstrom
- Mathematics
- 7 May 2014

In this book chapter we survey known approaches and algorithms to compute discrepancy measures of point sets. After providing an introduction which puts the calculation of discrepancy measures in a… Expand

IOHprofiler: A Benchmarking and Profiling Tool for Iterative Optimization Heuristics

- Carola Doerr, Hao Wang, Furong Ye, Sander van Rijn, T. Bäck
- Computer Science
- ArXiv
- 11 October 2018

IOHprofiler is a new tool for analyzing and comparing iterative optimization heuristics. Given as input algorithms and problems written in C or Python, it provides as output a statistical evaluation… Expand

Unknown solution length problems with no asymptotically optimal run time

- B. Doerr, Carola Doerr, Timo Kötzing
- Mathematics, Computer Science
- GECCO
- 1 July 2017

We revisit the problem of optimizing a fitness function of unknown dimension; that is, we face a function defined over bit-strings of large length N, but only n ≪ N of them have an influence on the… Expand