Dirk Sudholt - Google Scholar

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Carsten WittTechnical University of DenmarkVerified email at imm.dtu.dk
Pietro S. OlivetoSenior Lecturer, EPSRC Early Career Fellow, The University of Sheffield, UKVerified email at sheffield.ac.uk
Frank NeumannOptimisation and Logistics, School of ComputerVerified email at adelaide.edu.au
Tobias FriedrichChair for Algorithm Engineering, Hasso Plattner Institute, Potsdam, GermanyVerified email at hpi.de
Per Kristian LehreUniversity of BirminghamVerified email at cs.bham.ac.uk
Thomas JansenAberystwyth UniversityVerified email at aber.ac.uk
Duc-Cuong DangINESC TEC, PortugalVerified email at inesctec.pt
Christine ZargesDepartment of Computer Science, Aberystwyth UniversityVerified email at aber.ac.uk
Andrew M. SuttonUniversity of Minnesota DuluthVerified email at umn.edu
Benjamin DoerrProfessor at Ecole Polytechnique, France; senior researcher at Max Planck Institute for InformaticsVerified email at mpi-inf.mpg.de
Carola DoerrCNRS researcher at Sorbonne UniversityVerified email at mpi-inf.mpg.de
Xin YaoSouthern University of Science and Technology (SUSTech) and University of BirminghamVerified email at cs.bham.ac.uk
Jonathan RoweSchool of Computer Science, University of Birmingham Verified email at cs.bham.ac.uk
Andrea MambriniOptidromeVerified email at optidrome.com
Leandro MinkuLecturer in Intelligent Systems, University of BirminghamVerified email at cs.bham.ac.uk
Heiko RöglinProfessor of Computer Science, University of BonnVerified email at cs.uni-bonn.de
Dimo BrockhoffInria, Ecole Polytechnique, Institut Polytechnique de ParisVerified email at inria.fr
Phil McMinnProfessor of Software Engineering, University of SheffieldVerified email at sheffield.ac.uk
Markus WagnerSenior Lecturer of Computer Science, The University of AdelaideVerified email at adelaide.edu.au
Alberto MoraglioUniversity of ExeterVerified email at exeter.ac.uk

Dirk Sudholt

University of Sheffield, UK

Verified email at sheffield.ac.uk

Computational complexity randomized algorithms metaheuristics natural computation parallelism


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
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	113	2012
Crossover is provably essential for the Ising model on trees D Sudholt Proceedings of the 7th annual conference on Genetic and evolutionary …, 2005	95	2005
Analysis of diversity-preserving mechanisms for global exploration T Friedrich, PS Oliveto, D Sudholt, C Witt Evolutionary Computation 17 (4), 455-476, 2009	93	2009
The impact of parametrization in memetic evolutionary algorithms D Sudholt Theoretical Computer Science 410 (26), 2511-2528, 2009	74	2009
The choice of the offspring population size in the (1, λ) evolutionary algorithm JE Rowe, D Sudholt Theoretical Computer Science 545, 20-38, 2014	71	2014
How crossover helps in pseudo-boolean optimization T Kötzing, D Sudholt, M Theile Proceedings of the 13th annual conference on Genetic and evolutionary …, 2011	70	2011
Analysis of different MMAS ACO algorithms on unimodal functions and plateaus F Neumann, D Sudholt, C Witt Swarm Intelligence 3 (1), 35-68, 2009	69	2009
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	63	2011
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	55	2007
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	54	2013
Running time analysis of ant colony optimization for shortest path problems D Sudholt, C Thyssen Journal of Discrete Algorithms 10, 165-180, 2012	53	2012
Crossover speeds up building-block assembly D Sudholt Proceedings of the 14th annual conference on Genetic and evolutionary …, 2012	51	2012
Unbiased black-box complexity of parallel search G Badkobeh, PK Lehre, D Sudholt International Conference on Parallel Problem Solving from Nature, 892-901, 2014	50	2014
Parallel evolutionary algorithms D Sudholt Springer Handbook of Computational Intelligence, 929-959, 2015	49	2015
The choice of the offspring population size in the (1, λ) EA JE Rowe, D Sudholt Proceedings of the 14th annual conference on Genetic and evolutionary …, 2012	47	2012
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	46	2017
A simple ant colony optimizer for stochastic shortest path problems D Sudholt, C Thyssen Algorithmica 64 (4), 643-672, 2012	44	2012
Rigorous analyses for the combination of ant colony optimization and local search F Neumann, D Sudholt, C Witt International Conference on Ant Colony Optimization and Swarm Intelligence …, 2008	44	2008
Design and analysis of migration in parallel evolutionary algorithms J Lässig, D Sudholt Soft Computing 17 (7), 1121-1144, 2013	40	2013
Runtime analysis of binary PSO D Sudholt, C Witt Proceedings of the 10th annual conference on Genetic and evolutionary …, 2008	40	2008

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