Per Kristian Lehre

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Duc-Cuong DangUniversity of Southampton, UKVerified email at soton.ac.uk
Pietro S. OlivetoProfessor of Computer Science, Chair in Algorithms, The University of SheffieldVerified email at sheffield.ac.uk
Xin YaoSouthern University of Science and Technology and University of Birmingham (UK)Verified email at cs.bham.ac.uk
Dirk SudholtUniversity of Passau, GermanyVerified email at uni-passau.de
Tobias FriedrichChair for Algorithm Engineering, Hasso Plattner Institute, Potsdam, GermanyVerified email at hpi.de
Anton EremeevOmsk Branch of Sobolev Institute of MathematicsVerified email at ofim.oscsbras.ru
Martin S. KrejcaLIX, CNRS, Ecole Polytechnique, IPPVerified email at polytechnique.edu
Dogan CorusKadir Has UniversityVerified email at khas.edu.tr
Andrew M. SuttonUniversity of Minnesota DuluthVerified email at umn.edu
Carsten WittTechnical University of DenmarkVerified email at imm.dtu.dk
Frank NeumannOptimisation and Logistics, School of ComputerVerified email at adelaide.edu.au
Pauline C HaddowNTNUVerified email at idi.ntnu.no
Golnaz BadkobehGoldsmiths, University of LondonVerified email at gold.ac.uk
Tiago PaixaoInstituto Gulbenkian de CiênciaVerified email at igc.gulbenkian.pt
Andrea ArcuriProfessor of Software Engineering at Kristiania University CollegeVerified email at kristiania.no
Barbora TrubenováETH ZurichVerified email at env.ethz.ch
Thomas JansenAberystwyth UniversityVerified email at aber.ac.uk
Carola DoerrCNRS research director (DR) at Sorbonne Université, Paris, FranceVerified email at mpi-inf.mpg.de
Markus WagnerAssociate Professor of Computer Science, Monash University, AustraliaVerified email at monash.edu
Ender ÖzcanProfessor of Computer Science and Operational Research, University of NottinghamVerified email at nottingham.ac.uk

Per Kristian Lehre

Professor at University of Birmingham and UKRI Turing AI Acceleration Fellow

Verified email at cs.bham.ac.uk - Homepage

Evolutionary Computation Coevolution Natural Computation


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Black-box search by unbiased variation PK Lehre, C Witt Proceedings of the 12th annual conference on Genetic and evolutionary …, 2010	214	2010
Level-based analysis of genetic algorithms and other search processes D Corus, DC Dang, AV Eremeev, PK Lehre IEEE Transactions on Evolutionary Computation 22 (5), 707-719, 2017	157	2017
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	119	2017
Negative drift in populations P Lehre Parallel Problem Solving from Nature–PPSN XI, 244-253, 2011	94	2011
On the impact of the mutation-selection balance on the runtime of evolutionary algorithms PK Lehre, X Yao Proceedings of the tenth ACM SIGEVO workshop on Foundations of genetic …, 2009	92	2009
On the effect of populations in evolutionary multi-objective optimization O Giel, PK Lehre Proceedings of the 8th annual conference on Genetic and evolutionary …, 2006	89	2006
Dynamic evolutionary optimisation: an analysis of frequency and magnitude of change P Rohlfshagen, PK Lehre, X Yao Proceedings of the 11th Annual conference on Genetic and evolutionary …, 2009	87	2009
Self-adaptation of mutation rates in non-elitist populations DC Dang, PK Lehre Parallel Problem Solving from Nature–PPSN XIV: 14th International Conference …, 2016	84	2016
Fitness-levels for non-elitist populations PK Lehre Proceedings of the 13th annual conference on Genetic and evolutionary …, 2011	83	2011
Unbiased black-box complexity of parallel search G Badkobeh, PK Lehre, D Sudholt Parallel Problem Solving from Nature–PPSN XIII: 13th International …, 2014	76	2014
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	69	2016
Faster black-box algorithms through higher arity operators B Doerr, D Johannsen, T Kötzing, PK Lehre, M Wagner, C Winzen Proceedings of the 11th workshop proceedings on Foundations of genetic …, 2011	66	2011
Runtime analysis of non-elitist populations: from classical optimisation to partial information DC Dang, PK Lehre Algorithmica 75, 428-461, 2016	63	2016
A runtime analysis of simple hyper-heuristics: To mix or not to mix operators PK Lehre, E Özcan Proceedings of the twelfth workshop on Foundations of genetic algorithms XII …, 2013	63	2013
Crossover can be constructive when computing unique input output sequences P Lehre, X Yao Simulated Evolution and Learning, 595-604, 2008	63	2008
Concentrated hitting times of randomized search heuristics with variable drift PK Lehre, C Witt International Symposium on Algorithms and Computation, 686-697, 2014	61	2014
Runtime analysis of the (1+ 1) ea on computing unique input output sequences PK Lehre, X Yao Information Sciences, 2010	55*	2010
Efficient optimisation of noisy fitness functions with population-based evolutionary algorithms DC Dang, PK Lehre Proceedings of the 2015 ACM Conference on Foundations of Genetic Algorithms …, 2015	51	2015
Theoretical analysis of rank-based mutation-combining exploration and exploitation PS Oliveto, PK Lehre, F Neumann Evolutionary Computation, 2009. CEC'09. IEEE Congress on, 1455-1462, 2009	48	2009
General drift analysis with tail bounds PK Lehre, C Witt arXiv preprint arXiv:1307.2559, 2013	38	2013

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