Developmental mappings and phenotypic complexity. - Per Kristian Lehre; Pauline C. Haddow (IEEE Congress on Evolutionary Computation, 2003)

Accessibility between neutral networks in indirect genotype-phenotype mappings. - Per Kristian Lehre; Pauline C. Haddow (Congress on Evolutionary Computation, 2005)

Evolved Digital Circuits and Genome Complexity. - Morten Hartmann; Per Kristian Lehre; Pauline C. Haddow (Evolvable Hardware, 2005)

On the effect of populations in evolutionary multi-objective optimization. - Oliver Giel; Per Kristian Lehre (GECCO, 2006)

Accessibility and Runtime Between Convex Neutral Networks. - Per Kristian Lehre; Pauline C. Haddow (SEAL, 2006)

Runtime analysis of (1+l) EA on computing unique input output sequences. - Per Kristian Lehre; Xin Yao 001 (IEEE Congress on Evolutionary Computation, 2007)

The genotypic complexity of evolved fault-tolerant and noise-robust circuits. - Morten Hartmann; Pauline C. Haddow; Per Kristian Lehre (Biosyst., 2007)

Phenotypic complexity and local variations in neutral degree. - Per Kristian Lehre; Pauline C. Haddow (Biosyst., 2007)

Theoretical Runtime Analyses of Search Algorithms on the Test Data Generation for the Triangle Classification Problem. - Andrea Arcuri; Per Kristian Lehre; Xin Yao 001 (ICST Workshops, 2008)

When is an estimation of distribution algorithm better than an evolutionary algorithm? - Tianshi Chen 002; Per Kristian Lehre; Ke Tang 001; Xin Yao 001 (IEEE Congress on Evolutionary Computation, 2009)

Theoretical analysis of rank-based mutation - combining exploration and exploitation. - Pietro S. Oliveto; Per Kristian Lehre; Frank Neumann 001 (IEEE Congress on Evolutionary Computation, 2009)

Dynamic evolutionary optimisation: an analysis of frequency and magnitude of change. - Philipp Rohlfshagen; Per Kristian Lehre; Xin Yao 001 (GECCO, 2009)

Runtime analysis of search heuristics on software engineering problems. - Per Kristian Lehre; Xin Yao 001 (Frontiers Comput. Sci. China, 2009)

Ant colony optimization and the minimum cut problem. - Timo Kötzing; Per Kristian Lehre; Frank Neumann 001; Pietro S. Oliveto (GECCO, 2010)

Fixed Parameter Evolutionary Algorithms and Maximum Leaf Spanning Trees: A Matter of Mutation. - Stefan Kratsch; Per Kristian Lehre; Frank Neumann 001; Pietro Simone Oliveto (PPSN (1), 2010)

Negative Drift in Populations. - Per Kristian Lehre (PPSN (1), 2010)

On the Effect of Populations in Evolutionary Multi-Objective Optimisation. - Oliver Giel; Per Kristian Lehre (Evol. Comput., 2010)

Black-Box Search by Unbiased Variation. - Per Kristian Lehre; Carsten Witt (Electron. Colloquium Comput. Complex., 2010)

Non-uniform mutation rates for problems with unknown solution lengths. - Stephan Cathabard; Per Kristian Lehre; Xin Yao 001 (FOGA, 2011)

Faster black-box algorithms through higher arity operators. - Benjamin Doerr; Daniel Johannsen; Timo Kötzing; Per Kristian Lehre; Markus Wagner 007; Carola Winzen (FOGA, 2011)

Fitness-levels for non-elitist populations. - Per Kristian Lehre (GECCO, 2011)

Finite First Hitting Time versus Stochastic Convergence in Particle Swarm Optimisation - Per Kristian Lehre; Carsten Witt (CoRR, 2011)

Crossover can be constructive when computing unique input-output sequences. - Per Kristian Lehre; Xin Yao 001 (Soft Comput., 2011)

Drift analysis. - Per Kristian Lehre (GECCO (Companion), 2012)

Editorial to the special issue on "Theoretical Foundations of Evolutionary Computation". - Per Kristian Lehre; Frank Neumann 001; Jonathan E. Rowe; Xin Yao 001 (Theor. Comput. Sci., 2012)

On the Impact of Mutation-Selection Balance on the Runtime of Evolutionary Algorithms. - Per Kristian Lehre; Xin Yao 001 (IEEE Trans. Evol. Comput., 2012)

A runtime analysis of simple hyper-heuristics: to mix or not to mix operators. - Per Kristian Lehre; Ender Özcan (FOGA, 2013)

The generalized minimum spanning tree problem: a parameterized complexity analysis of bi-level optimisation. - Dogan Corus; Per Kristian Lehre; Frank Neumann 001 (GECCO, 2013)

General Drift Analysis with Tail Bounds. - Per Kristian Lehre; Carsten Witt (CoRR, 2013)

Runtime analysis of selection hyper-heuristics with classical learning mechanisms. - Fawaz Alanazi; Per Kristian Lehre (IEEE Congress on Evolutionary Computation, 2014)

Evolution under partial information. - Duc-Cuong Dang; Per Kristian Lehre (GECCO, 2014)

Refined upper bounds on the expected runtime of non-elitist populations from fitness-levels. - Duc-Cuong Dang; Per Kristian Lehre (GECCO, 2014)

Runtime analysis of evolutionary algorithms: basic introduction. - Per Kristian Lehre; Pietro S. Oliveto (GECCO (Companion), 2014)

Concentrated Hitting Times of Randomized Search Heuristics with Variable Drift. - Per Kristian Lehre; Carsten Witt (ISAAC, 2014)

Unbiased Black-Box Complexity of Parallel Search. - Golnaz Badkobeh; Per Kristian Lehre; Dirk Sudholt (PPSN, 2014)

A Parameterized Complexity Analysis of Bi-level Optimisation with Evolutionary Algorithms. - Dogan Corus; Per Kristian Lehre; Frank Neumann 001; Mojgan Pourhassan (CoRR, 2014)

Runtime analysis of the (1 + 1) EA on computing unique input output sequences. - Per Kristian Lehre; Xin Yao 001 (Inf. Sci., 2014)

Editorial for the Special Issue on Theoretical Foundations of Evolutionary Computation. - Frank Neumann 001; Benjamin Doerr; Per Kristian Lehre; Pauline C. Haddow (IEEE Trans. Evol. Comput., 2014)

Black-box Complexity of Parallel Search with Distributed Populations. - Golnaz Badkobeh; Per Kristian Lehre; Dirk Sudholt (FOGA, 2015)

Efficient Optimisation of Noisy Fitness Functions with Population-based Evolutionary Algorithms. - Duc-Cuong Dang; Per Kristian Lehre (FOGA, 2015)

Populations can be Essential in Dynamic Optimisation. - Duc-Cuong Dang; Thomas Jansen 001; Per Kristian Lehre (GECCO, 2015)

Simplified Runtime Analysis of Estimation of Distribution Algorithms. - Duc-Cuong Dang; Per Kristian Lehre (GECCO, 2015)

Level-Based Analysis of Genetic Algorithms for Combinatorial Optimization. - Duc-Cuong Dang; Anton V. Eremeev; Per Kristian Lehre (CoRR, 2015)

Limits to Learning in Reinforcement Learning Hyper-heuristics. - Fawaz Alanazi; Per Kristian Lehre (EvoCOP, 2016)

Escaping Local Optima with Diversity Mechanisms and Crossover. - Duc-Cuong Dang; Tobias Friedrich 001; Timo Kötzing; Martin S. Krejca; Per Kristian Lehre; Pietro S. Oliveto; Dirk Sudholt; Andrew M. Sutton (GECCO, 2016)

Emergence of Diversity and Its Benefits for Crossover in Genetic Algorithms. - Duc-Cuong Dang; Tobias Friedrich 001; Timo Kötzing; Martin S. Krejca; Per Kristian Lehre; Pietro S. Oliveto; Dirk Sudholt; Andrew M. Sutton (PPSN, 2016)

Self-adaptation of Mutation Rates in Non-elitist Populations. - Duc-Cuong Dang; Per Kristian Lehre (PPSN, 2016)

Tutorials at PPSN 2016. - Carola Doerr; Nicolas Bredèche; Enrique Alba 001; Thomas Bartz-Beielstein; Dimo Brockhoff; Benjamin Doerr; Gusz Eiben; Michael G. Epitropakis; Carlos M. Fonseca; Andreia P. Guerreiro; Evert Haasdijk; Jacqueline Heinerman; et al. (PPSN, 2016)

Runtime Analysis of Non-elitist Populations: From Classical Optimisation to Partial Information. - Duc-Cuong Dang; Per Kristian Lehre (Algorithmica, 2016)

Escaping Local Optima using Crossover with Emergent or Reinforced Diversity. - Duc-Cuong Dang; Tobias Friedrich 001; Timo Kötzing; Martin S. Krejca; Per Kristian Lehre; Pietro S. Oliveto; Dirk Sudholt; Andrew M. Sutton (CoRR, 2016)

Evolution and Computing (Dagstuhl Seminar 16011). - Nick Barton; Per Kristian Lehre; Nisheeth K. Vishnoi (Dagstuhl Reports, 2016)

A Parameterised Complexity Analysis of Bi-level Optimisation with Evolutionary Algorithms. - Dogan Corus; Per Kristian Lehre; Frank Neumann 001; Mojgan Pourhassan (Evol. Comput., 2016)

Improved runtime bounds for the univariate marginal distribution algorithm via anti-concentration. - Per Kristian Lehre; Phan Trung Hai Nguyen (GECCO, 2017)

Runtime analysis of population-based evolutionary algorithms: introductory tutorial at GECCO 2017. - Per Kristian Lehre; Pietro S. Oliveto (GECCO (Companion), 2017)

Populations Can Be Essential in Tracking Dynamic Optima. - Duc-Cuong Dang; Thomas Jansen 001; Per Kristian Lehre (Algorithmica, 2017)

Theoretical Analysis of Stochastic Search Algorithms. - Per Kristian Lehre; Pietro S. Oliveto (CoRR, 2017)

Level-Based Analysis of the Population-Based Incremental Learning Algorithm. - Per Kristian Lehre; Phan Trung Hai Nguyen (PPSN (2), 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; et al. (PPSN (2), 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)

Escaping Local Optima Using Crossover With Emergent Diversity. - Duc-Cuong Dang; Tobias Friedrich 001; Timo Kötzing; Martin S. Krejca; Per Kristian Lehre; Pietro S. Oliveto; Dirk Sudholt; Andrew M. Sutton (IEEE Trans. Evol. Comput., 2018)

Theoretical Analysis of Stochastic Search Algorithms. - Per Kristian Lehre; Pietro S. Oliveto (Handbook of Heuristics, 2018)

On the limitations of the univariate marginal distribution algorithm to deception and where bivariate EDAs might help. - Per Kristian Lehre; Phan Trung Hai Nguyen (FOGA, 2019)

Runtime analysis of the univariate marginal distribution algorithm under low selective pressure and prior noise. - Per Kristian Lehre; Phan Trung Hai Nguyen (GECCO, 2019)

Runtime analysis of evolutionary algorithms: basic introduction: introductory tutorial at GECCO 2019. - Per Kristian Lehre; Pietro S. Oliveto (GECCO (Companion), 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 Fitness-Proportionate Selection on Linear Functions. - Duc-Cuong Dang; Anton V. Eremeev; Per Kristian Lehre (CoRR, 2019)

Runtime analysis of population-based evolutionary algorithms: introductory tutorial at GECCO 2020. - Per Kristian Lehre; Pietro S. Oliveto (GECCO Companion, 2020)

Self-adaptation in non-Elitist Evolutionary Algorithms on Discrete Problems with Unknown Structure. - Brendan Case; Per Kristian Lehre (CoRR, 2020)

Self-Adaptation in Nonelitist Evolutionary Algorithms on Discrete Problems With Unknown Structure. - Brendan Case; Per Kristian Lehre (IEEE Trans. Evol. Comput., 2020)

Parallel Black-Box Complexity With Tail Bounds. - Per Kristian Lehre; Dirk Sudholt (IEEE Trans. Evol. Comput., 2020)

Escaping Local Optima with Non-Elitist Evolutionary Algorithms. - Duc-Cuong Dang; Anton V. Eremeev; Per Kristian Lehre (AAAI, 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 (GECCO, 2021)

More precise runtime analyses of non-elitist EAs in uncertain environments. - Per Kristian Lehre; Xiaoyu Qin (GECCO, 2021)

Preface to the Special Issue on Theory of Genetic and Evolutionary Computation. - Anne Auger; Per Kristian Lehre (Algorithmica, 2021)

Runtime Analyses of the Population-Based Univariate Estimation of Distribution Algorithms on LeadingOnes. - Per Kristian Lehre; Phan Trung Hai Nguyen (Algorithmica, 2021)

Tail bounds on hitting times of randomized search heuristics using variable drift analysis. - Per Kristian Lehre; Carsten Witt (Comb. Probab. Comput., 2021)

Fast non-elitist evolutionary algorithms with power-law ranking selection. - Duc-Cuong Dang; Anton V. Eremeev; Per Kristian Lehre; Xiaoyu Qin (GECCO, 2022)

Runtime analysis of population-based evolutionary algorithms. - Per Kristian Lehre; Pietro S. Oliveto (GECCO Companion, 2022)

Self-adaptation via multi-objectivisation: a theoretical study. - Per Kristian Lehre; Xiaoyu Qin (GECCO, 2022)

Self-adaptation via Multi-objectivisation: An Empirical Study. - Xiaoyu Qin; Per Kristian Lehre (PPSN (1), 2022)

Is CC-(1+1) EA More Efficient than (1+1) EA on Separable and Inseparable Problems? - Per Kristian Lehre; Shishen Lin (CEC, 2023)

Runtime Analysis of a Co-Evolutionary Algorithm: Overcoming Negative Drift in Maximin-Optimisation. - Mario Alejandro Hevia Fajardo; Per Kristian Lehre; Shishen Lin (FOGA, 2023)

Self-adaptation Can Improve the Noise-tolerance of Evolutionary Algorithms. - Per Kristian Lehre; Xiaoyu Qin (FOGA, 2023)

How Fitness Aggregation Methods Affect the Performance of Competitive CoEAs on Bilinear Problems. - Mario Alejandro Hevia Fajardo; Per Kristian Lehre (GECCO, 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 (GECCO, 2023)

Runtime Analysis of Population-based Evolutionary Algorithms - Part I: Steady State EAs. - Per Kristian Lehre; Pietro Simone Oliveto (GECCO Companion, 2023)

Self-adaptation Can Help Evolutionary Algorithms Track Dynamic Optima. - Per Kristian Lehre; Xiaoyu Qin (GECCO, 2023)

Runtime Analysis with Variable Cost. - Per Kristian Lehre; Andrew M. Sutton (GECCO, 2023)

Non-Elitist Evolutionary Multi-Objective Optimisation: Proof-of-Principle Results. - Zimin Liang; Miqing Li; Per Kristian Lehre (GECCO Companion, 2023)

Analysis of a Pairwise Dominance Coevolutionary Algorithm with Spatial Topology. - Mario Alejandro Hevia Fajardo; Per Kristian Lehre; Jamal Toutouh; Erik Hemberg; Una-May O'Reilly (GPTP, 2023)

Special Issue on Theoretical Foundations of Evolutionary Computation. - Per Kristian Lehre; Aneta Neumann; Chao Qian 001 (Theor. Comput. Sci., 2023)

Bicriteria Optimisation of Average and Worst-Case Performance Using Coevolutionary Algorithms. - Alistair Benford; Markus Olhofer; Tobias Rodemann; Per Kristian Lehre (CEC, 2024)

Runtime Analysis of Coevolutionary Algorithms on a Class of Symmetric Zero-Sum Games. - Alistair Benford; Per Kristian Lehre (GECCO, 2024)

The SLO Hierarchy of pseudo-Boolean Functions and Runtime of Evolutionary Algorithms. - Duc-Cuong Dang; Per Kristian Lehre (GECCO, 2024)

A Self-adaptive Coevolutionary Algorithm. - Mario Alejandro Hevia Fajardo; Erik Hemberg; Jamal Toutouh; Una-May O'Reilly; Per Kristian Lehre (GECCO, 2024)

Runtime Analysis of Population-based Evolutionary Algorithms. - Per Kristian Lehre (GECCO Companion, 2024)

Concentration Tail-Bound Analysis of Coevolutionary and Bandit Learning Algorithms. - Per Kristian Lehre; Shishen Lin (IJCAI, 2024)

No Free Lunch Theorem and Black-Box Complexity Analysis for Adversarial Optimisation. - Per Kristian Lehre; Shishen Lin (NeurIPS, 2024)

Ranking Diversity Benefits Coevolutionary Algorithms on an Intransitive Game. - Mario Alejandro Hevia Fajardo; Per Kristian Lehre (PPSN (3), 2024)

Overcoming Binary Adversarial Optimisation with Competitive Coevolution. - Per Kristian Lehre; Shishen Lin (PPSN (3), 2024)

Runtime analysis of a coevolutionary algorithm on impartial combinatorial games. - Alistair Benford; Per Kristian Lehre (CoRR, 2024)

More Precise Runtime Analyses of Non-elitist Evolutionary Algorithms in Uncertain Environments. - Per Kristian Lehre; Xiaoyu Qin (Algorithmica, 2024)

Runtime Analysis of Competitive Co-evolutionary Algorithms for Maximin Optimisation of a Bilinear Function. - Per Kristian Lehre (Algorithmica, 2024)

Towards Runtime Analysis of Population-Based Co-evolutionary Algorithms on Sparse Binary Zero-Sum Game. - Per Kristian Lehre; Shishen Lin (AAAI, 2025)

A General Upper Bound for the Runtime of a Coevolutionary Algorithm on Impartial Combinatorial Games. - Alistair Benford; Per Kristian Lehre (GECCO, 2025)