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Dirk Sudholt
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A new method for lower bounds on the running time of evolutionary algorithms
D Sudholt
IEEE Transactions on Evolutionary Computation 17 (3), 418-435, 2012
1622012
Escaping local optima using crossover with emergent diversity
DC Dang, T Friedrich, T Kötzing, MS Krejca, PK Lehre, PS Oliveto, ...
IEEE Transactions on Evolutionary Computation 22 (3), 484-497, 2017
1282017
Analysis of diversity-preserving mechanisms for global exploration
T Friedrich, PS Oliveto, D Sudholt, C Witt
Evolutionary Computation 17 (4), 455-476, 2009
1192009
Crossover is provably essential for the Ising model on trees
D Sudholt
Proceedings of the 7th annual conference on Genetic and evolutionary …, 2005
1122005
The choice of the offspring population size in the (1, λ) evolutionary algorithm
JE Rowe, D Sudholt
Theoretical Computer Science 545, 20-38, 2014
1072014
Parallel evolutionary algorithms
D Sudholt
Springer Handbook of Computational Intelligence, 929-959, 2015
902015
How crossover helps in pseudo-Boolean optimization
T Kötzing, D Sudholt, M Theile
Proceedings of the 13th annual conference on Genetic and evolutionary …, 2011
892011
Running time analysis of ant colony optimization for shortest path problems
D Sudholt, C Thyssen
Journal of Discrete Algorithms 10, 165-180, 2012
862012
Analysis of different MMAS ACO algorithms on unimodal functions and plateaus
F Neumann, D Sudholt, C Witt
Swarm Intelligence 3, 35-68, 2009
832009
Adaptive population models for offspring populations and parallel evolutionary algorithms
J Lässig, D Sudholt
Proceedings of the 11th workshop proceedings on Foundations of genetic …, 2011
802011
The impact of parametrization in memetic evolutionary algorithms
D Sudholt
Theoretical Computer Science 410 (26), 2511-2528, 2009
792009
Mutation rate matters even when optimizing monotonic functions
B Doerr, T Jansen, D Sudholt, C Winzen, C Zarges
Evolutionary computation 21 (1), 1-27, 2013
782013
Unbiased black-box complexity of parallel search
G Badkobeh, PK Lehre, D Sudholt
Parallel Problem Solving from Nature–PPSN XIII: 13th International …, 2014
762014
The benefits of population diversity in evolutionary algorithms: a survey of rigorous runtime analyses
D Sudholt
Theory of evolutionary computation: Recent developments in discrete …, 2020
692020
Escaping local optima with diversity mechanisms and crossover
DC Dang, T Friedrich, T Kötzing, MS Krejca, PK Lehre, PS Oliveto, ...
Proceedings of the Genetic and Evolutionary Computation Conference 2016, 645-652, 2016
692016
How crossover speeds up building block assembly in genetic algorithms
D Sudholt
Evolutionary computation 25 (2), 237-274, 2017
652017
Improved evolutionary algorithm design for the project scheduling problem based on runtime analysis
LL Minku, D Sudholt, X Yao
IEEE Transactions on Software Engineering 40 (1), 83-102, 2013
632013
Crossover speeds up building-block assembly
D Sudholt
Proceedings of the 14th annual conference on Genetic and evolutionary …, 2012
562012
On the runtime analysis of the 1-ANT ACO algorithm
B Doerr, F Neumann, D Sudholt, C Witt
Proceedings of the 9th annual conference on Genetic and evolutionary …, 2007
562007
A simple ant colony optimizer for stochastic shortest path problems
D Sudholt, C Thyssen
Algorithmica 64, 643-672, 2012
542012
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