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ORCIDPer Kristian Lehre
Person information
- affiliation: University of Birmingham, UK
- affiliation (former): University of Nottingham, UK
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2020 – today
- 2024
[j24]Per Kristian Lehre, Xiaoyu Qin
:
More Precise Runtime Analyses of Non-elitist Evolutionary Algorithms in Uncertain Environments. Algorithmica 86(2): 396-441 (2024)- [j23]Per Kristian Lehre:
Runtime Analysis of Competitive Co-evolutionary Algorithms for Maximin Optimisation of a Bilinear Function. Algorithmica 86(7): 2352-2392 (2024) - [c79]Alistair Benford, Markus Olhofer, Tobias Rodemann, Per Kristian Lehre:
Bicriteria Optimisation of Average and Worst-Case Performance Using Coevolutionary Algorithms. CEC 2024: 1-8 - [c78]Alistair Benford, Per Kristian Lehre:
Runtime Analysis of Coevolutionary Algorithms on a Class of Symmetric Zero-Sum Games. GECCO 2024 - [c77]Duc-Cuong Dang, Per Kristian Lehre:
The SLO Hierarchy of pseudo-Boolean Functions and Runtime of Evolutionary Algorithms. GECCO 2024 - [c76]Mario Alejandro Hevia Fajardo, Erik Hemberg, Jamal Toutouh, Una-May O'Reilly, Per Kristian Lehre:
A Self-adaptive Coevolutionary Algorithm. GECCO 2024 - [c75]Per Kristian Lehre:
Runtime Analysis of Population-based Evolutionary Algorithms. GECCO Companion 2024: 903-927 - [c74]Per Kristian Lehre, Shishen Lin:
Concentration Tail-Bound Analysis of Coevolutionary and Bandit Learning Algorithms. IJCAI 2024: 6940-6948 - [c73]Per Kristian Lehre, Shishen Lin:
Overcoming Binary Adversarial Optimisation with Competitive Coevolution. PPSN (3) 2024: 117-132 - [c72]Mario Alejandro Hevia Fajardo, Per Kristian Lehre:
Ranking Diversity Benefits Coevolutionary Algorithms on an Intransitive Game. PPSN (3) 2024: 213-229 - [i26]Per Kristian Lehre, Shishen Lin:
Concentration Tail-Bound Analysis of Coevolutionary and Bandit Learning Algorithms. CoRR abs/2405.04480 (2024) - [i25]Per Kristian Lehre, Shishen Lin:
Overcoming Binary Adversarial Optimisation with Competitive Coevolution. CoRR abs/2407.17875 (2024) - [i24]Alistair Benford, Per Kristian Lehre:
Runtime analysis of a coevolutionary algorithm on impartial combinatorial games. CoRR abs/2409.04177 (2024) - 2023
- [j22]Per Kristian Lehre, Aneta Neumann, Chao Qian:
Special Issue on Theoretical Foundations of Evolutionary Computation. Theor. Comput. Sci. 950: 113785 (2023) - [c71]Per Kristian Lehre, Shishen Lin:
Is CC-(1+1) EA More Efficient than (1+1) EA on Separable and Inseparable Problems? CEC 2023: 1-9 - [c70]Mario Alejandro Hevia Fajardo, Per Kristian Lehre, Shishen Lin:
Runtime Analysis of a Co-Evolutionary Algorithm: Overcoming Negative Drift in Maximin-Optimisation. FOGA 2023: 73-83 - [c69]Per Kristian Lehre, Xiaoyu Qin:
Self-adaptation Can Improve the Noise-tolerance of Evolutionary Algorithms. FOGA 2023: 105-116 - [c68]Zimin Liang, Miqing Li, Per Kristian Lehre:
Non-Elitist Evolutionary Multi-Objective Optimisation: Proof-of-Principle Results. GECCO Companion 2023: 383-386 - [c67]Mario Alejandro Hevia Fajardo, Per Kristian Lehre, Shishen Lin:
Runtime Analysis of a Co-Evolutionary Algorithm: Overcoming Negative Drift in Maximin-Optimisation. GECCO Companion 2023: 819-822 - [c66]Per Kristian Lehre, Mario Alejandro Hevia Fajardo, Jamal Toutouh, Erik Hemberg, Una-May O'Reilly:
Analysis of a Pairwise Dominance Coevolutionary Algorithm And DefendIt. GECCO 2023: 1027-1035 - [c65]Per Kristian Lehre, Pietro Simone Oliveto:
Runtime Analysis of Population-based Evolutionary Algorithms - Part I: Steady State EAs. GECCO Companion 2023: 1271-1300 - [c64]Mario Alejandro Hevia Fajardo, Per Kristian Lehre:
How Fitness Aggregation Methods Affect the Performance of Competitive CoEAs on Bilinear Problems. GECCO 2023: 1593-1601 - [c63]Per Kristian Lehre, Andrew M. Sutton:
Runtime Analysis with Variable Cost. GECCO 2023: 1611-1618 - [c62]Per Kristian Lehre, Xiaoyu Qin:
Self-adaptation Can Help Evolutionary Algorithms Track Dynamic Optima. GECCO 2023: 1619-1627 - [c61]Mario Alejandro Hevia Fajardo, Per Kristian Lehre, Jamal Toutouh, Erik Hemberg, Una-May O'Reilly:
Analysis of a Pairwise Dominance Coevolutionary Algorithm with Spatial Topology. GPTP 2023: 19-44 - [i23]Zimin Liang, Miqing Li, Per Kristian Lehre:
Non-Elitist Evolutionary Multi-Objective Optimisation: Proof-of-Principle Results. CoRR abs/2305.16870 (2023) - 2022
- [c60]Duc-Cuong Dang, Anton V. Eremeev, Per Kristian Lehre, Xiaoyu Qin:
Fast non-elitist evolutionary algorithms with power-law ranking selection. GECCO 2022: 1372-1380 - [c59]Per Kristian Lehre, Pietro S. Oliveto:
Runtime analysis of population-based evolutionary algorithms. GECCO Companion 2022: 1398-1426 - [c58]Per Kristian Lehre:
Runtime analysis of competitive co-evolutionary algorithms for maximin optimisation of a bilinear function. GECCO 2022: 1408-1416 - [c57]Per Kristian Lehre, Xiaoyu Qin:
Self-adaptation via multi-objectivisation: a theoretical study. GECCO 2022: 1417-1425 - [c56]Xiaoyu Qin, Per Kristian Lehre:
Self-adaptation via Multi-objectivisation: An Empirical Study. PPSN (1) 2022: 308-323 - [i22]Per Kristian Lehre:
Runtime Analysis of Competitive co-Evolutionary Algorithms for Maximin Optimisation of a Bilinear Function. CoRR abs/2206.15238 (2022) - 2021
- [j21]Anne Auger, Per Kristian Lehre:
Preface to the Special Issue on Theory of Genetic and Evolutionary Computation. Algorithmica 83(4): 903-905 (2021) - [j20]Per Kristian Lehre, Phan Trung Hai Nguyen:
Runtime Analyses of the Population-Based Univariate Estimation of Distribution Algorithms on LeadingOnes. Algorithmica 83(10): 3238-3280 (2021) - [j19]Per Kristian Lehre, Carsten Witt:
Tail bounds on hitting times of randomized search heuristics using variable drift analysis. Comb. Probab. Comput. 30(4): 550-569 (2021) - [c55]Duc-Cuong Dang, Anton V. Eremeev, Per Kristian Lehre:
Escaping Local Optima with Non-Elitist Evolutionary Algorithms. AAAI 2021: 12275-12283 - [c54]Per Kristian Lehre, Pietro S. Oliveto:
Runtime analysis of evolutionary algorithms: basic introduction. GECCO Companion 2021: 399-425 - [c53]Per Kristian Lehre, Pietro S. Oliveto:
Runtime analysis of population-based evolutionary algorithms. GECCO Companion 2021: 856-880 - [c52]Duc-Cuong Dang, Anton V. Eremeev, Per Kristian Lehre:
Non-elitist evolutionary algorithms excel in fitness landscapes with sparse deceptive regions and dense valleys. GECCO 2021: 1133-1141 - [c51]Per Kristian Lehre, Xiaoyu Qin:
More precise runtime analyses of non-elitist EAs in uncertain environments. GECCO 2021: 1160-1168 - 2020
- [j18]Brendan Case, Per Kristian Lehre:
Self-Adaptation in Nonelitist Evolutionary Algorithms on Discrete Problems With Unknown Structure. IEEE Trans. Evol. Comput. 24(4): 650-663 (2020) - [j17]Per Kristian Lehre, Dirk Sudholt:
Parallel Black-Box Complexity With Tail Bounds. IEEE Trans. Evol. Comput. 24(6): 1010-1024 (2020) - [c50]Per Kristian Lehre, Pietro S. Oliveto:
Runtime analysis of population-based evolutionary algorithms: introductory tutorial at GECCO 2020. GECCO Companion 2020: 458-494 - [i21]Brendan Case, Per Kristian Lehre:
Self-adaptation in non-Elitist Evolutionary Algorithms on Discrete Problems with Unknown Structure. CoRR abs/2004.00327 (2020)
2010 – 2019
- 2019
- [j16]Duc-Cuong Dang, Per Kristian Lehre, Phan Trung Hai Nguyen:
Level-Based Analysis of the Univariate Marginal Distribution Algorithm. Algorithmica 81(2): 668-702 (2019) - [c49]Per Kristian Lehre, Phan Trung Hai Nguyen:
On the limitations of the univariate marginal distribution algorithm to deception and where bivariate EDAs might help. FOGA 2019: 154-168 - [c48]Per Kristian Lehre, Pietro S. Oliveto:
Runtime analysis of evolutionary algorithms: basic introduction: introductory tutorial at GECCO 2019. GECCO (Companion) 2019: 662-693 - [c47]Per Kristian Lehre, Phan Trung Hai Nguyen:
Runtime analysis of the univariate marginal distribution algorithm under low selective pressure and prior noise. GECCO 2019: 1497-1505 - [i20]Per Kristian Lehre, Dirk Sudholt:
Parallel Black-Box Complexity with Tail Bounds. CoRR abs/1902.00107 (2019) - [i19]Per Kristian Lehre, Phan Trung Hai Nguyen:
Runtime Analysis of the Univariate Marginal Distribution Algorithm under Low Selective Pressure and Prior Noise. CoRR abs/1904.09239 (2019) - [i18]Per Kristian Lehre, Phan Trung Hai Nguyen:
On the Limitations of the Univariate Marginal Distribution Algorithm to Deception and Where Bivariate EDAs might help. CoRR abs/1907.12438 (2019) - [i17]Duc-Cuong Dang, Anton V. Eremeev, Per Kristian Lehre:
Runtime Analysis of Fitness-Proportionate Selection on Linear Functions. CoRR abs/1908.08686 (2019) - 2018
- [j15]Duc-Cuong Dang, Tobias Friedrich, Timo Kötzing, Martin S. Krejca, Per Kristian Lehre, Pietro S. Oliveto, Dirk Sudholt, Andrew M. Sutton:
Escaping Local Optima Using Crossover With Emergent Diversity. IEEE Trans. Evol. Comput. 22(3): 484-497 (2018) - [j14]Dogan Corus, Duc-Cuong Dang, Anton V. Eremeev, Per Kristian Lehre:
Level-Based Analysis of Genetic Algorithms and Other Search Processes. IEEE Trans. Evol. Comput. 22(5): 707-719 (2018) - [c46]Per Kristian Lehre, Pietro S. Oliveto:
Runtime analysis of evolutionary algorithms: basic introduction. GECCO (Companion) 2018: 448-468 - [c45]Per Kristian Lehre, Phan Trung Hai Nguyen:
Level-Based Analysis of the Population-Based Incremental Learning Algorithm. PPSN (2) 2018: 105-116 - [c44]Gisele Lobo Pappa, Michael T. M. Emmerich, Ana L. C. Bazzan, Will N. Browne, Kalyanmoy Deb, Carola Doerr, Marko Durasevic, Michael G. Epitropakis, Saemundur O. Haraldsson, Domagoj Jakobovic, Pascal Kerschke, Krzysztof Krawiec, Per Kristian Lehre, Xiaodong Li, Andrei Lissovoi, Pekka Malo, Luis Martí, Yi Mei, Juan Julián Merelo Guervós, Julian F. Miller, Alberto Moraglio, Antonio J. Nebro, Su Nguyen, Gabriela Ochoa, Pietro S. Oliveto, Stjepan Picek, Nelishia Pillay, Mike Preuss, Marc Schoenauer, Roman Senkerik, Ankur Sinha, Ofer M. Shir, Dirk Sudholt, L. Darrell Whitley, Mark Wineberg, John R. Woodward, Mengjie Zhang:
Tutorials at PPSN 2018. PPSN (2) 2018: 477-489 - [r1]Per Kristian Lehre, Pietro S. Oliveto:
Theoretical Analysis of Stochastic Search Algorithms. Handbook of Heuristics 2018: 849-884 - [i16]Per Kristian Lehre, Phan Trung Hai Nguyen:
Improved Runtime Bounds for the Univariate Marginal Distribution Algorithm via Anti-Concentration. CoRR abs/1802.00721 (2018) - [i15]Per Kristian Lehre, Phan Trung Hai Nguyen:
Level-Based Analysis of the Population-Based Incremental Learning Algorithm. CoRR abs/1806.01710 (2018) - [i14]Duc-Cuong Dang, Per Kristian Lehre, Phan Trung Hai Nguyen:
Level-Based Analysis of the Univariate Marginal Distribution Algorithm. CoRR abs/1807.10038 (2018) - 2017
- [j13]Duc-Cuong Dang, Thomas Jansen, Per Kristian Lehre:
Populations Can Be Essential in Tracking Dynamic Optima. Algorithmica 78(2): 660-680 (2017) - [c43]Per Kristian Lehre, Pietro S. Oliveto:
Runtime analysis of population-based evolutionary algorithms: introductory tutorial at GECCO 2017. GECCO (Companion) 2017: 414-434 - [c42]Per Kristian Lehre, Phan Trung Hai Nguyen:
Improved runtime bounds for the univariate marginal distribution algorithm via anti-concentration. GECCO 2017: 1383-1390 - [i13]Per Kristian Lehre, Pietro S. Oliveto:
Theoretical Analysis of Stochastic Search Algorithms. CoRR abs/1709.00890 (2017) - 2016
- [j12]Duc-Cuong Dang, Per Kristian Lehre:
Runtime Analysis of Non-elitist Populations: From Classical Optimisation to Partial Information. Algorithmica 75(3): 428-461 (2016) - [j11]Dogan Corus, Per Kristian Lehre, Frank Neumann, Mojgan Pourhassan:
A Parameterised Complexity Analysis of Bi-level Optimisation with Evolutionary Algorithms. Evol. Comput. 24(1): 183-203 (2016) - [c41]Fawaz Alanazi, Per Kristian Lehre:
Limits to Learning in Reinforcement Learning Hyper-heuristics. EvoCOP 2016: 170-185 - [c40]Per Kristian Lehre, Pietro S. Oliveto:
Runtime Analysis of Population-based Evolutionary Algorithms. GECCO (Companion) 2016: 435-462 - [c39]Duc-Cuong Dang, Tobias Friedrich, Timo Kötzing, Martin S. Krejca, Per Kristian Lehre, Pietro S. Oliveto, Dirk Sudholt, Andrew M. Sutton:
Escaping Local Optima with Diversity Mechanisms and Crossover. GECCO 2016: 645-652 - [c38]Duc-Cuong Dang, Per Kristian Lehre:
Self-adaptation of Mutation Rates in Non-elitist Populations. PPSN 2016: 803-813 - [c37]Duc-Cuong Dang, Tobias Friedrich, Timo Kötzing, Martin S. Krejca, Per Kristian Lehre, Pietro S. Oliveto, Dirk Sudholt, Andrew M. Sutton:
Emergence of Diversity and Its Benefits for Crossover in Genetic Algorithms. PPSN 2016: 890-900 - [c36]Carola Doerr, Nicolas Bredèche, Enrique Alba, Thomas Bartz-Beielstein, Dimo Brockhoff, Benjamin Doerr, Gusz Eiben, Michael G. Epitropakis, Carlos M. Fonseca, Andreia P. Guerreiro, Evert Haasdijk, Jacqueline Heinerman, Julien Hubert, Per Kristian Lehre, Luigi Malagò, Juan Julián Merelo Guervós, Julian Francis Miller, Boris Naujoks, Pietro S. Oliveto, Stjepan Picek, Nelishia Pillay, Mike Preuss, Patricia Ryser-Welch, Giovanni Squillero, Jörg Stork, Dirk Sudholt, Alberto Paolo Tonda, L. Darrell Whitley, Martin Zaefferer:
Tutorials at PPSN 2016. PPSN 2016: 1012-1022 - [i12]Duc-Cuong Dang, Per Kristian Lehre:
Self-adaptation of Mutation Rates in Non-elitist Populations. CoRR abs/1606.05551 (2016) - [i11]Duc-Cuong Dang, Thomas Jansen, Per Kristian Lehre:
Populations can be essential in tracking dynamic optima. CoRR abs/1607.03317 (2016) - [i10]Duc-Cuong Dang, Tobias Friedrich, Timo Kötzing, Martin S. Krejca, Per Kristian Lehre, Pietro S. Oliveto, Dirk Sudholt, Andrew M. Sutton:
Escaping Local Optima using Crossover with Emergent or Reinforced Diversity. CoRR abs/1608.03123 (2016) - [i9]Nick Barton, Per Kristian Lehre, Nisheeth K. Vishnoi:
Evolution and Computing (Dagstuhl Seminar 16011). Dagstuhl Reports 6(1): 1-14 (2016) - 2015
- [c35]Golnaz Badkobeh, Per Kristian Lehre, Dirk Sudholt:
Black-box Complexity of Parallel Search with Distributed Populations. FOGA 2015: 3-15 - [c34]Duc-Cuong Dang, Per Kristian Lehre:
Efficient Optimisation of Noisy Fitness Functions with Population-based Evolutionary Algorithms. FOGA 2015: 62-68 - [c33]Per Kristian Lehre, Pietro S. Oliveto:
Runtime Analysis of Evolutionary Algorithms: Basic Introduction. GECCO (Companion) 2015: 121-136 - [c32]Duc-Cuong Dang, Per Kristian Lehre:
Simplified Runtime Analysis of Estimation of Distribution Algorithms. GECCO 2015: 513-518 - [c31]Duc-Cuong Dang, Thomas Jansen, Per Kristian Lehre:
Populations can be Essential in Dynamic Optimisation. GECCO 2015: 1407-1414 - [i8]Duc-Cuong Dang, Anton V. Eremeev, Per Kristian Lehre:
Level-Based Analysis of Genetic Algorithms for Combinatorial Optimization. CoRR abs/1512.02047 (2015) - 2014
- [j10]Per Kristian Lehre, Xin Yao:
Runtime analysis of the (1 + 1) EA on computing unique input output sequences. Inf. Sci. 259: 510-531 (2014) - [j9]Frank Neumann, Benjamin Doerr, Per Kristian Lehre, Pauline C. Haddow:
Editorial for the Special Issue on Theoretical Foundations of Evolutionary Computation. IEEE Trans. Evol. Comput. 18(5): 625-627 (2014) - [c30]Fawaz Alanazi, Per Kristian Lehre:
Runtime analysis of selection hyper-heuristics with classical learning mechanisms. IEEE Congress on Evolutionary Computation 2014: 2515-2523 - [c29]Per Kristian Lehre, Pietro S. Oliveto:
Runtime analysis of evolutionary algorithms: basic introduction. GECCO (Companion) 2014: 459-486 - [c28]Duc-Cuong Dang, Per Kristian Lehre:
Evolution under partial information. GECCO 2014: 1359-1366 - [c27]Duc-Cuong Dang, Per Kristian Lehre:
Refined upper bounds on the expected runtime of non-elitist populations from fitness-levels. GECCO 2014: 1367-1374 - [c26]Per Kristian Lehre, Carsten Witt:
Concentrated Hitting Times of Randomized Search Heuristics with Variable Drift. ISAAC 2014: 686-697 - [c25]Golnaz Badkobeh, Per Kristian Lehre, Dirk Sudholt:
Unbiased Black-Box Complexity of Parallel Search. PPSN 2014: 892-901 - [c24]Dogan Corus, Duc-Cuong Dang, Anton V. Eremeev, Per Kristian Lehre:
Level-Based Analysis of Genetic Algorithms and Other Search Processes. PPSN 2014: 912-921 - [i7]Dogan Corus, Per Kristian Lehre, Frank Neumann, Mojgan Pourhassan:
A Parameterized Complexity Analysis of Bi-level Optimisation with Evolutionary Algorithms. CoRR abs/1401.1905 (2014) - [i6]Dogan Corus, Duc-Cuong Dang, Anton V. Eremeev, Per Kristian Lehre:
Level-based Analysis of Genetic Algorithms and other Search Processes. CoRR abs/1407.7663 (2014) - 2013
- [c23]Per Kristian Lehre, Ender Özcan:
A runtime analysis of simple hyper-heuristics: to mix or not to mix operators. FOGA 2013: 97-104 - [c22]Per Kristian Lehre, Pietro S. Oliveto:
Runtime analysis of evolutionary algorithms: basic introduction. GECCO (Companion) 2013: 469-498 - [c21]Dogan Corus, Per Kristian Lehre, Frank Neumann:
The generalized minimum spanning tree problem: a parameterized complexity analysis of bi-level optimisation. GECCO 2013: 519-526 - [i5]Per Kristian Lehre, Carsten Witt:
General Drift Analysis with Tail Bounds. CoRR abs/1307.2559 (2013) - 2012
- [j8]Per Kristian Lehre, Carsten Witt:
Black-Box Search by Unbiased Variation. Algorithmica 64(4): 623-642 (2012) - [j7]Per Kristian Lehre, Frank Neumann, Jonathan E. Rowe, Xin Yao:
Editorial to the special issue on "Theoretical Foundations of Evolutionary Computation". Theor. Comput. Sci. 425: 2-3 (2012) - [j6]Per Kristian Lehre, Xin Yao:
On the Impact of Mutation-Selection Balance on the Runtime of Evolutionary Algorithms. IEEE Trans. Evol. Comput. 16(2): 225-241 (2012) - [c20]Per Kristian Lehre:
Drift analysis. GECCO (Companion) 2012: 1239-1258 - 2011
- [j5]Per Kristian Lehre, Xin Yao:
Crossover can be constructive when computing unique input-output sequences. Soft Comput. 15(9): 1675-1687 (2011) - [c19]Benjamin Doerr, Daniel Johannsen, Timo Kötzing, Per Kristian Lehre, Markus Wagner, Carola Winzen:
Faster black-box algorithms through higher arity operators. FOGA 2011: 163-172 - [c18]Stephan Cathabard, Per Kristian Lehre, Xin Yao:
Non-uniform mutation rates for problems with unknown solution lengths. FOGA 2011: 173-180 - [c17]Per Kristian Lehre:
Fitness-levels for non-elitist populations. GECCO 2011: 2075-2082 - [i4]Per Kristian Lehre, Carsten Witt:
Finite First Hitting Time versus Stochastic Convergence in Particle Swarm Optimisation. CoRR abs/1105.5540 (2011) - 2010
- [j4]Oliver Giel, Per Kristian Lehre:
On the Effect of Populations in Evolutionary Multi-Objective Optimisation. Evol. Comput. 18(3): 335-356 (2010) - [c16]Timo Kötzing, Per Kristian Lehre, Frank Neumann, Pietro S. Oliveto:
Ant colony optimization and the minimum cut problem. GECCO 2010: 1393-1400 - [c15]Per Kristian Lehre, Carsten Witt:
Black-box search by unbiased variation. GECCO 2010: 1441-1448 - [c14]Stefan Kratsch, Per Kristian Lehre, Frank Neumann, Pietro Simone Oliveto:
Fixed Parameter Evolutionary Algorithms and Maximum Leaf Spanning Trees: A Matter of Mutation. PPSN (1) 2010: 204-213 - [c13]Per Kristian Lehre:
Negative Drift in Populations. PPSN (1) 2010: 244-253 - [i3]Benjamin Doerr, Daniel Johannsen, Timo Kötzing, Per Kristian Lehre, Markus Wagner, Carola Winzen:
Faster Black-Box Algorithms Through Higher Arity Operators. CoRR abs/1012.0952 (2010) - [i2]Per Kristian Lehre, Xin Yao:
On the Impact of Mutation-Selection Balance on the Runtime of Evolutionary Algorithms. CoRR abs/1012.3098 (2010) - [i1]Per Kristian Lehre, Carsten Witt:
Black-Box Search by Unbiased Variation. Electron. Colloquium Comput. Complex. TR10 (2010)
2000 – 2009
- 2009
- [j3]Per Kristian Lehre, Xin Yao:
Runtime analysis of search heuristics on software engineering problems. Frontiers Comput. Sci. China 3(1): 64-72 (2009) - [c12]Pietro S. Oliveto, Per Kristian Lehre, Frank Neumann:
Theoretical analysis of rank-based mutation - combining exploration and exploitation. IEEE Congress on Evolutionary Computation 2009: 1455-1462 - [c11]Tianshi Chen, Per Kristian Lehre, Ke Tang, Xin Yao:
When is an estimation of distribution algorithm better than an evolutionary algorithm? IEEE Congress on Evolutionary Computation 2009: 1470-1477 - [c10]Per Kristian Lehre, Xin Yao:
On the impact of the mutation-selection balance on the runtime of evolutionary algorithms. FOGA 2009: 47-58 - [c9]Philipp Rohlfshagen, Per Kristian Lehre, Xin Yao:
Dynamic evolutionary optimisation: an analysis of frequency and magnitude of change. GECCO 2009: 1713-1720 - 2008
- [c8]Andrea Arcuri, Per Kristian Lehre, Xin Yao:
Theoretical Runtime Analyses of Search Algorithms on the Test Data Generation for the Triangle Classification Problem. ICST Workshops 2008: 161-169 - [c7]Per Kristian Lehre, Xin Yao:
Crossover Can Be Constructive When Computing Unique Input Output Sequences. SEAL 2008: 595-604 - 2007
- [j2]Morten Hartmann, Pauline C. Haddow, Per Kristian Lehre:
The genotypic complexity of evolved fault-tolerant and noise-robust circuits. Biosyst. 87(2-3): 224-232 (2007) - [j1]Per Kristian Lehre, Pauline C. Haddow:
Phenotypic complexity and local variations in neutral degree. Biosyst. 87(2-3): 233-242 (2007) - [c6]Per Kristian Lehre, Xin Yao:
Runtime analysis of (1+l) EA on computing unique input output sequences. IEEE Congress on Evolutionary Computation 2007: 1882-1889 - 2006
- [c5]Oliver Giel, Per Kristian Lehre:
On the effect of populations in evolutionary multi-objective optimization. GECCO 2006: 651-658 - [c4]Per Kristian Lehre, Pauline C. Haddow:
Accessibility and Runtime Between Convex Neutral Networks. SEAL 2006: 734-741 - 2005
- [c3]Per Kristian Lehre, Pauline C. Haddow:
Accessibility between neutral networks in indirect genotype-phenotype mappings. Congress on Evolutionary Computation 2005: 419-426 - [c2]Morten Hartmann, Per Kristian Lehre, Pauline C. Haddow:
Evolved Digital Circuits and Genome Complexity. Evolvable Hardware 2005: 79-86 - 2003
- [c1]Per Kristian Lehre, Pauline C. Haddow:
Developmental mappings and phenotypic complexity. IEEE Congress on Evolutionary Computation 2003: 62-68
Coauthor Index
Pietro S. Oliveto
aka: Pietro Simone Oliveto
aka: Pietro Simone Oliveto
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