Per Kristian Lehre

According to our database, Per Kristian Lehre authored at least 92 papers between 2003 and 2024.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of three.

2024

More Precise Runtime Analyses of Non-elitist Evolutionary Algorithms in Uncertain Environments.

Per Kristian Lehre, Xiaoyu Qin

Algorithmica, February, 2024

2023

Special Issue on Theoretical Foundations of Evolutionary Computation.

Per Kristian Lehre, Aneta Neumann, Chao Qian

Theor. Comput. Sci., March, 2023

Non-Elitist Evolutionary Multi-Objective Optimisation: Proof-of-Principle Results.

Zimin Liang, Miqing Li, Per Kristian Lehre

Proceedings of the Companion Proceedings of the Conference on Genetic and Evolutionary Computation, 2023

Runtime Analysis with Variable Cost.

Per Kristian Lehre, Andrew M. Sutton

Proceedings of the Genetic and Evolutionary Computation Conference, 2023

Self-adaptation Can Help Evolutionary Algorithms Track Dynamic Optima.

Per Kristian Lehre, Xiaoyu Qin

Proceedings of the Genetic and Evolutionary Computation Conference, 2023

Runtime Analysis of Population-based Evolutionary Algorithms - Part I: Steady State EAs.

Per Kristian Lehre, Pietro Simone Oliveto

Proceedings of the Companion Proceedings of the Conference on Genetic and Evolutionary Computation, 2023

Analysis of a Pairwise Dominance Coevolutionary Algorithm And DefendIt.

Per Kristian Lehre, Mario Alejandro Hevia Fajardo, Jamal Toutouh, Erik Hemberg, Una-May O'Reilly

Proceedings of the Genetic and Evolutionary Computation Conference, 2023

Runtime Analysis of a Co-Evolutionary Algorithm: Overcoming Negative Drift in Maximin-Optimisation.

Mario Alejandro Hevia Fajardo, Per Kristian Lehre, Shishen Lin

Proceedings of the Companion Proceedings of the Conference on Genetic and Evolutionary Computation, 2023

How Fitness Aggregation Methods Affect the Performance of Competitive CoEAs on Bilinear Problems.

Mario Alejandro Hevia Fajardo, Per Kristian Lehre

Proceedings of the Genetic and Evolutionary Computation Conference, 2023

Self-adaptation Can Improve the Noise-tolerance of Evolutionary Algorithms.

Per Kristian Lehre, Xiaoyu Qin

Proceedings of the 17th ACM/SIGEVO Conference on Foundations of Genetic Algorithms, 2023

Is CC-(1+1) EA More Efficient than (1+1) EA on Separable and Inseparable Problems?

Per Kristian Lehre, Shishen Lin

Proceedings of the IEEE Congress on Evolutionary Computation, 2023

2022

Self-adaptation via Multi-objectivisation: An Empirical Study.

Xiaoyu Qin, Per Kristian Lehre

Proceedings of the Parallel Problem Solving from Nature - PPSN XVII, 2022

Self-adaptation via multi-objectivisation: a theoretical study.

Per Kristian Lehre, Xiaoyu Qin

Proceedings of the GECCO '22: Genetic and Evolutionary Computation Conference, Boston, Massachusetts, USA, July 9, 2022

Runtime analysis of competitive co-evolutionary algorithms for maximin optimisation of a bilinear function.

Per Kristian Lehre

Proceedings of the GECCO '22: Genetic and Evolutionary Computation Conference, Boston, Massachusetts, USA, July 9, 2022

Fast non-elitist evolutionary algorithms with power-law ranking selection.

Duc-Cuong Dang, Anton V. Eremeev, Per Kristian Lehre, Xiaoyu Qin

Proceedings of the GECCO '22: Genetic and Evolutionary Computation Conference, Boston, Massachusetts, USA, July 9, 2022

2021

Tail bounds on hitting times of randomized search heuristics using variable drift analysis.

Per Kristian Lehre, Carsten Witt

Comb. Probab. Comput., 2021

Runtime Analyses of the Population-Based Univariate Estimation of Distribution Algorithms on LeadingOnes.

Per Kristian Lehre, Phan Trung Hai Nguyen

Algorithmica, 2021

Preface to the Special Issue on Theory of Genetic and Evolutionary Computation.

Anne Auger, Per Kristian Lehre

Algorithmica, 2021

More precise runtime analyses of non-elitist EAs in uncertain environments.

Per Kristian Lehre, Xiaoyu Qin

Proceedings of the GECCO '21: Genetic and Evolutionary Computation Conference, 2021

Runtime analysis of evolutionary algorithms: basic introduction.

Per Kristian Lehre, Pietro S. Oliveto

Proceedings of the GECCO '21: Genetic and Evolutionary Computation Conference, 2021

Non-elitist evolutionary algorithms excel in fitness landscapes with sparse deceptive regions and dense valleys.

Duc-Cuong Dang, Anton V. Eremeev, Per Kristian Lehre

Proceedings of the GECCO '21: Genetic and Evolutionary Computation Conference, 2021

Escaping Local Optima with Non-Elitist Evolutionary Algorithms.

Duc-Cuong Dang, Anton V. Eremeev, Per Kristian Lehre

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Parallel Black-Box Complexity With Tail Bounds.

Per Kristian Lehre, Dirk Sudholt

IEEE Trans. Evol. Comput., 2020

Self-Adaptation in Nonelitist Evolutionary Algorithms on Discrete Problems With Unknown Structure.

Brendan Case, Per Kristian Lehre

IEEE Trans. Evol. Comput., 2020

Self-adaptation in non-Elitist Evolutionary Algorithms on Discrete Problems with Unknown Structure.

Brendan Case, Per Kristian Lehre

CoRR, 2020

Runtime analysis of population-based evolutionary algorithms: introductory tutorial at GECCO 2020.

Per Kristian Lehre, Pietro S. Oliveto

Proceedings of the GECCO '20: Genetic and Evolutionary Computation Conference, 2020

2019

Runtime Analysis of Fitness-Proportionate Selection on Linear Functions.

Duc-Cuong Dang, Anton V. Eremeev, Per Kristian Lehre

CoRR, 2019

Level-Based Analysis of the Univariate Marginal Distribution Algorithm.

Duc-Cuong Dang, Per Kristian Lehre, Phan Trung Hai Nguyen

Algorithmica, 2019

Runtime analysis of evolutionary algorithms: basic introduction: introductory tutorial at GECCO 2019.

Per Kristian Lehre, Pietro S. Oliveto

Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2019

Runtime analysis of the univariate marginal distribution algorithm under low selective pressure and prior noise.

Per Kristian Lehre, Phan Trung Hai Nguyen

Proceedings of the Genetic and Evolutionary Computation Conference, 2019

On the limitations of the univariate marginal distribution algorithm to deception and where bivariate EDAs might help.

Per Kristian Lehre, Phan Trung Hai Nguyen

Proceedings of the 15th ACM/SIGEVO Conference on Foundations of Genetic Algorithms, 2019

2018

Theoretical Analysis of Stochastic Search Algorithms.

Per Kristian Lehre, Pietro S. Oliveto

Proceedings of the Handbook of Heuristics., 2018

Escaping Local Optima Using Crossover With Emergent Diversity.

Duc-Cuong Dang, Tobias Friedrich, Timo Kötzing, Martin S. Krejca, Per Kristian Lehre, Pietro S. Oliveto, Dirk Sudholt, Andrew M. Sutton

IEEE Trans. Evol. Comput., 2018

Level-Based Analysis of Genetic Algorithms and Other Search Processes.

Dogan Corus, Duc-Cuong Dang, Anton V. Eremeev, Per Kristian Lehre

IEEE Trans. Evol. Comput., 2018

Tutorials at PPSN 2018.

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

Proceedings of the Parallel Problem Solving from Nature - PPSN XV, 2018

Level-Based Analysis of the Population-Based Incremental Learning Algorithm.

Per Kristian Lehre, Phan Trung Hai Nguyen

Proceedings of the Parallel Problem Solving from Nature - PPSN XV, 2018

2017

Theoretical Analysis of Stochastic Search Algorithms.

Per Kristian Lehre, Pietro S. Oliveto

CoRR, 2017

Populations Can Be Essential in Tracking Dynamic Optima.

Duc-Cuong Dang, Thomas Jansen, Per Kristian Lehre

Algorithmica, 2017

Runtime analysis of population-based evolutionary algorithms: introductory tutorial at GECCO 2017.

Per Kristian Lehre, Pietro S. Oliveto

Proceedings of the Genetic and Evolutionary Computation Conference, 2017

Improved runtime bounds for the univariate marginal distribution algorithm via anti-concentration.

Per Kristian Lehre, Phan Trung Hai Nguyen

Proceedings of the Genetic and Evolutionary Computation Conference, 2017

2016

A Parameterised Complexity Analysis of Bi-level Optimisation with Evolutionary Algorithms.

Dogan Corus, Per Kristian Lehre, Frank Neumann, Mojgan Pourhassan

Evol. Comput., 2016

Evolution and Computing (Dagstuhl Seminar 16011).

Nick Barton, Per Kristian Lehre, Nisheeth K. Vishnoi

Dagstuhl Reports, 2016

Escaping Local Optima using Crossover with Emergent or Reinforced Diversity.

Duc-Cuong Dang, Tobias Friedrich, Timo Kötzing, Martin S. Krejca, Per Kristian Lehre, Pietro S. Oliveto, Dirk Sudholt, Andrew M. Sutton

CoRR, 2016

Runtime Analysis of Non-elitist Populations: From Classical Optimisation to Partial Information.

Duc-Cuong Dang, Per Kristian Lehre

Algorithmica, 2016

Tutorials at PPSN 2016.

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

Proceedings of the Parallel Problem Solving from Nature - PPSN XIV, 2016

Self-adaptation of Mutation Rates in Non-elitist Populations.

Duc-Cuong Dang, Per Kristian Lehre

Proceedings of the Parallel Problem Solving from Nature - PPSN XIV, 2016

Emergence of Diversity and Its Benefits for Crossover in Genetic Algorithms.

Duc-Cuong Dang, Tobias Friedrich, Timo Kötzing, Martin S. Krejca, Per Kristian Lehre, Pietro S. Oliveto, Dirk Sudholt, Andrew M. Sutton

Proceedings of the Parallel Problem Solving from Nature - PPSN XIV, 2016

Runtime Analysis of Population-based Evolutionary Algorithms.

Per Kristian Lehre, Pietro S. Oliveto

Proceedings of the Genetic and Evolutionary Computation Conference, 2016

Escaping Local Optima with Diversity Mechanisms and Crossover.

Duc-Cuong Dang, Tobias Friedrich, Timo Kötzing, Martin S. Krejca, Per Kristian Lehre, Pietro S. Oliveto, Dirk Sudholt, Andrew M. Sutton

Proceedings of the 2016 on Genetic and Evolutionary Computation Conference, Denver, CO, USA, July 20, 2016

Limits to Learning in Reinforcement Learning Hyper-heuristics.

Fawaz Alanazi, Per Kristian Lehre

Proceedings of the Evolutionary Computation in Combinatorial Optimization, 2016

2015

Level-Based Analysis of Genetic Algorithms for Combinatorial Optimization.

Duc-Cuong Dang, Anton V. Eremeev, Per Kristian Lehre

CoRR, 2015

Simplified Runtime Analysis of Estimation of Distribution Algorithms.

Duc-Cuong Dang, Per Kristian Lehre

Proceedings of the Genetic and Evolutionary Computation Conference, 2015

Populations can be Essential in Dynamic Optimisation.

Duc-Cuong Dang, Thomas Jansen, Per Kristian Lehre

Proceedings of the Genetic and Evolutionary Computation Conference, 2015

Efficient Optimisation of Noisy Fitness Functions with Population-based Evolutionary Algorithms.

Duc-Cuong Dang, Per Kristian Lehre

Proceedings of the 2015 ACM Conference on Foundations of Genetic Algorithms XIII, Aberystwyth, United Kingdom, January 17, 2015

Black-box Complexity of Parallel Search with Distributed Populations.

Golnaz Badkobeh, Per Kristian Lehre, Dirk Sudholt

Proceedings of the 2015 ACM Conference on Foundations of Genetic Algorithms XIII, Aberystwyth, United Kingdom, January 17, 2015

2014

Editorial for the Special Issue on Theoretical Foundations of Evolutionary Computation.

Frank Neumann, Benjamin Doerr, Per Kristian Lehre, Pauline C. Haddow

IEEE Trans. Evol. Comput., 2014

Runtime analysis of the (1 + 1) EA on computing unique input output sequences.

Per Kristian Lehre, Xin Yao

Inf. Sci., 2014

A Parameterized Complexity Analysis of Bi-level Optimisation with Evolutionary Algorithms.

Dogan Corus, Per Kristian Lehre, Frank Neumann, Mojgan Pourhassan

CoRR, 2014

Unbiased Black-Box Complexity of Parallel Search.

Golnaz Badkobeh, Per Kristian Lehre, Dirk Sudholt

Proceedings of the Parallel Problem Solving from Nature - PPSN XIII, 2014

Concentrated Hitting Times of Randomized Search Heuristics with Variable Drift.

Per Kristian Lehre, Carsten Witt

Proceedings of the Algorithms and Computation - 25th International Symposium, 2014

Refined upper bounds on the expected runtime of non-elitist populations from fitness-levels.

Duc-Cuong Dang, Per Kristian Lehre

Proceedings of the Genetic and Evolutionary Computation Conference, 2014

Evolution under partial information.

Duc-Cuong Dang, Per Kristian Lehre

Proceedings of the Genetic and Evolutionary Computation Conference, 2014

Runtime analysis of selection hyper-heuristics with classical learning mechanisms.

Fawaz Alanazi, Per Kristian Lehre

Proceedings of the IEEE Congress on Evolutionary Computation, 2014

2013

General Drift Analysis with Tail Bounds.

Per Kristian Lehre, Carsten Witt

CoRR, 2013

The generalized minimum spanning tree problem: a parameterized complexity analysis of bi-level optimisation.

Dogan Corus, Per Kristian Lehre, Frank Neumann

Proceedings of the Genetic and Evolutionary Computation Conference, 2013

A runtime analysis of simple hyper-heuristics: to mix or not to mix operators.

Per Kristian Lehre, Ender Özcan

Proceedings of the Foundations of Genetic Algorithms XII, 2013

2012

On the Impact of Mutation-Selection Balance on the Runtime of Evolutionary Algorithms.

Per Kristian Lehre, Xin Yao

IEEE Trans. Evol. Comput., 2012

Editorial to the special issue on "Theoretical Foundations of Evolutionary Computation".

Per Kristian Lehre, Frank Neumann, Jonathan E. Rowe, Xin Yao

Theor. Comput. Sci., 2012

Black-Box Search by Unbiased Variation.

Per Kristian Lehre, Carsten Witt

Algorithmica, 2012

Drift analysis.

Per Kristian Lehre

Proceedings of the Genetic and Evolutionary Computation Conference, 2012

2011

Crossover can be constructive when computing unique input-output sequences.

Per Kristian Lehre, Xin Yao

Soft Comput., 2011

Finite First Hitting Time versus Stochastic Convergence in Particle Swarm Optimisation

Per Kristian Lehre, Carsten Witt

CoRR, 2011

Fitness-levels for non-elitist populations.

Per Kristian Lehre

Proceedings of the 13th Annual Genetic and Evolutionary Computation Conference, 2011

Faster black-box algorithms through higher arity operators.

Benjamin Doerr, Daniel Johannsen, Timo Kötzing, Per Kristian Lehre, Markus Wagner, Carola Winzen

Proceedings of the Foundations of Genetic Algorithms, 11th International Workshop, 2011

Non-uniform mutation rates for problems with unknown solution lengths.

Stephan Cathabard, Per Kristian Lehre, Xin Yao

Proceedings of the Foundations of Genetic Algorithms, 11th International Workshop, 2011

2010

On the Effect of Populations in Evolutionary Multi-Objective Optimisation.

Oliver Giel, Per Kristian Lehre

Evol. Comput., 2010

Negative Drift in Populations.

Per Kristian Lehre

Proceedings of the Parallel Problem Solving from Nature, 2010

Fixed Parameter Evolutionary Algorithms and Maximum Leaf Spanning Trees: A Matter of Mutation.

Stefan Kratsch, Per Kristian Lehre, Frank Neumann, Pietro Simone Oliveto

Proceedings of the Parallel Problem Solving from Nature, 2010

Ant colony optimization and the minimum cut problem.

Timo Kötzing, Per Kristian Lehre, Frank Neumann, Pietro S. Oliveto

Proceedings of the Genetic and Evolutionary Computation Conference, 2010

2009

Runtime analysis of search heuristics on software engineering problems.

Per Kristian Lehre, Xin Yao

Frontiers Comput. Sci. China, 2009

Dynamic evolutionary optimisation: an analysis of frequency and magnitude of change.

Philipp Rohlfshagen, Per Kristian Lehre, Xin Yao

Proceedings of the Genetic and Evolutionary Computation Conference, 2009

Theoretical analysis of rank-based mutation - combining exploration and exploitation.

Pietro S. Oliveto, Per Kristian Lehre, Frank Neumann

Proceedings of the IEEE Congress on Evolutionary Computation, 2009

When is an estimation of distribution algorithm better than an evolutionary algorithm?

Tianshi Chen, Per Kristian Lehre, Ke Tang, Xin Yao

Proceedings of the IEEE Congress on Evolutionary Computation, 2009

2008

Theoretical Runtime Analyses of Search Algorithms on the Test Data Generation for the Triangle Classification Problem.

Andrea Arcuri, Per Kristian Lehre, Xin Yao

Proceedings of the First International Conference on Software Testing Verification and Validation, 2008

2007

Phenotypic complexity and local variations in neutral degree.

Per Kristian Lehre, Pauline C. Haddow

Biosyst., 2007

The genotypic complexity of evolved fault-tolerant and noise-robust circuits.

Morten Hartmann, Pauline C. Haddow, Per Kristian Lehre

Biosyst., 2007

Runtime analysis of (1+l) EA on computing unique input output sequences.

Per Kristian Lehre, Xin Yao

Proceedings of the IEEE Congress on Evolutionary Computation, 2007

2006

Accessibility and Runtime Between Convex Neutral Networks.

Per Kristian Lehre, Pauline C. Haddow

Proceedings of the Simulated Evolution and Learning, 6th International Conference, 2006

On the effect of populations in evolutionary multi-objective optimization.

Oliver Giel, Per Kristian Lehre

Proceedings of the Genetic and Evolutionary Computation Conference, 2006

2005

Evolved Digital Circuits and Genome Complexity.

Morten Hartmann, Per Kristian Lehre, Pauline C. Haddow

Proceedings of the 2005 NASA / DoD Conference on Evolvable Hardware (EH 2005), 29 June, 2005

Accessibility between neutral networks in indirect genotype-phenotype mappings.

Per Kristian Lehre, Pauline C. Haddow

Proceedings of the IEEE Congress on Evolutionary Computation, 2005

2003

Developmental mappings and phenotypic complexity.

Per Kristian Lehre, Pauline C. Haddow

Proceedings of the IEEE Congress on Evolutionary Computation, 2003