Dirk Sudholt

Algorithmica, October, 2024

Analysing Equilibrium States for Population Diversity.

[BibT_eX]

[DOI]

Algorithmica, July, 2024

Self-adjusting offspring population sizes outperform fixed parameters on the cliff function.

[BibT_eX]

[DOI]

Artif. Intell., March, 2024

Self-adjusting Population Sizes for Non-elitist Evolutionary Algorithms: Why Success Rates Matter.

[BibT_eX]

[DOI]

Algorithmica, February, 2024

Evolutionary Algorithms for One-Sided Bipartite Crossing Minimisation.

[BibT_eX]

[DOI]

Jakob Baumann

Ignaz Rutter

CoRR, 2024

A Tight O(4k/pc) Runtime Bound for a (μ+1) GA on Jumpk for Realistic Crossover Probabilities.

[BibT_eX]

[DOI]

CoRR, 2024

Crossover can guarantee exponential speed-ups in evolutionary multi-objective optimisation.

[BibT_eX]

[DOI]

Artif. Intell., 2024

Level-Based Theorems for Runtime Analysis of Multi-objective Evolutionary Algorithms.

[BibT_eX]

[DOI]

Proceedings of the Parallel Problem Solving from Nature - PPSN XVIII, 2024

On the Equivalence Between Stochastic Tournament and Power-Law Ranking Selection and How to Implement Them Efficiently.

[BibT_eX]

[DOI]

Proceedings of the Parallel Problem Solving from Nature - PPSN XVIII, 2024

Guiding Quality Diversity on Monotone Submodular Functions: Customising the Feature Space by Adding Boolean Conjunctions.

[BibT_eX]

[DOI]

Proceedings of the Genetic and Evolutionary Computation Conference, 2024

A Tight O(4k/pc) Runtime Bound for a (μ+1)GA on Jumpk for Realistic Crossover Probabilities.

[BibT_eX]

[DOI]

Proceedings of the Genetic and Evolutionary Computation Conference, 2024

Hot of the Press: Crossover Can Guarantee Exponential Speed-Ups in Evolutionary Multi-Objective Optimisation.

[BibT_eX]

[DOI]

Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2024

Runtime Analyses of NSGA-III on Many-Objective Problems.

[BibT_eX]

[DOI]

Proceedings of the Genetic and Evolutionary Computation Conference, 2024

Illustrating the Efficiency of Popular Evolutionary Multi-Objective Algorithms Using Runtime Analysis.

[BibT_eX]

[DOI]

Proceedings of the Genetic and Evolutionary Computation Conference, 2024

Evolutionary Computation Meets Graph Drawing: Runtime Analysis for Crossing Minimisation on Layered Graph Drawings.

[BibT_eX]

[DOI]

Jakob Baumann

Ignaz Rutter

Proceedings of the Genetic and Evolutionary Computation Conference, 2024

Evolutionary Algorithms for One-Sided Bipartite Crossing Minimisation (Poster Abstract).

[BibT_eX]

[DOI]

Jakob Baumann

Ignaz Rutter

Proceedings of the 32nd International Symposium on Graph Drawing and Network Visualization, 2024

2023

Do additional target points speed up evolutionary algorithms?

[BibT_eX]

[DOI]

Theor. Comput. Sci., March, 2023

Theory and Practice of Population Diversity in Evolutionary Computation.

[BibT_eX]

[DOI]

Giovanni Squillero

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

Comma Selection Outperforms Plus Selection on OneMax with Randomly Planted Optima.

[BibT_eX]

[DOI]

Joost Jorritsma

Proceedings of the Genetic and Evolutionary Computation Conference, 2023

Analysing the Robustness of NSGA-II under Noise.

[BibT_eX]

[DOI]

Proceedings of the Genetic and Evolutionary Computation Conference, 2023

The Cost of Randomness in Evolutionary Algorithms: Crossover can Save Random Bits.

[BibT_eX]

[DOI]

Carlo Kneissl

Proceedings of the Evolutionary Computation in Combinatorial Optimization, 2023

A Proof That Using Crossover Can Guarantee Exponential Speed-Ups in Evolutionary Multi-Objective Optimisation.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Theoretical and Empirical Analysis of Parameter Control Mechanisms in the (1 + (λ, λ)) Genetic Algorithm.

[BibT_eX]

[DOI]

ACM Trans. Evol. Learn. Optim., 2022

Runtime Analysis of Restricted Tournament Selection for Bimodal Optimisation.

[BibT_eX]

[DOI]

Evol. Comput., 2022

Tight Bounds on the Expected Runtime of a Standard Steady State Genetic Algorithm.

[BibT_eX]

[DOI]

Algorithmica, 2022

On the impact of the performance metric on efficient algorithm configuration.

[BibT_eX]

[DOI]

Artif. Intell., 2022

Evolutionary Algorithms for Cardinality-Constrained Ising Models.

[BibT_eX]

[DOI]

Vijay Dhanjibhai Bhuva

Liam Huber

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

Hard problems are easier for success-based parameter control.

[BibT_eX]

[DOI]

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

The compact genetic algorithm struggles on Cliff functions.

[BibT_eX]

[DOI]

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

2021

Analysing the Robustness of Evolutionary Algorithms to Noise: Refined Runtime Bounds and an Example Where Noise is Beneficial.

[BibT_eX]

[DOI]

Algorithmica, 2021

The Complex Parameter Landscape of the Compact Genetic Algorithm.

[BibT_eX]

[DOI]

Algorithmica, 2021

Time Complexity Analysis of Randomized Search Heuristics for the Dynamic Graph Coloring Problem.

[BibT_eX]

[DOI]

Algorithmica, 2021

Do additional optima speed up evolutionary algorithms?

[BibT_eX]

[DOI]

Proceedings of the FOGA '21: Foundations of Genetic Algorithms XVI, 2021

2020

The Benefits of Population Diversity in Evolutionary Algorithms: A Survey of Rigorous Runtime Analyses.

[BibT_eX]

[DOI]

Proceedings of the Theory of Evolutionary Computation, 2020

Runtime Analysis of Crowding Mechanisms for Multimodal Optimization.

[BibT_eX]

[DOI]

IEEE Trans. Evol. Comput., 2020

Parallel Black-Box Complexity With Tail Bounds.

[BibT_eX]

[DOI]

Per Kristian Lehre

IEEE Trans. Evol. Comput., 2020

Design and analysis of diversity-based parent selection schemes for speeding up evolutionary multi-objective optimisation.

[BibT_eX]

[DOI]

Theor. Comput. Sci., 2020

Memetic algorithms outperform evolutionary algorithms in multimodal optimisation.

[BibT_eX]

[DOI]

Phan Trung Hai Nguyen

Artif. Intell., 2020

Measuring and Maintaining Population Diversity in Search-Based Unit Test Generation.

[BibT_eX]

[DOI]

Nasser M. Albunian

Gordon Fraser

Proceedings of the Search-Based Software Engineering - 12th International Symposium, 2020

Fast Perturbative Algorithm Configurators.

[BibT_eX]

[DOI]

Proceedings of the Parallel Problem Solving from Nature - PPSN XVI, 2020

A tight lower bound on the expected runtime of standard steady state genetic algorithms.

[BibT_eX]

[DOI]

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

Analysis of the performance of algorithm configurators for search heuristics with global mutation operators.

[BibT_eX]

[DOI]

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

On the choice of the parameter control mechanism in the (1+(λ, λ)) genetic algorithm.

[BibT_eX]

[DOI]

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

More effective randomized search heuristics for graph coloring through dynamic optimization.

[BibT_eX]

[DOI]

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

Causes and effects of fitness landscapes in unit test generation.

[BibT_eX]

[DOI]

Nasser M. Albunian

Gordon Fraser

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

Do sophisticated evolutionary algorithms perform better than simple ones?

[BibT_eX]

[DOI]

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

2019

On the benefits and risks of using fitness sharing for multimodal optimisation.

[BibT_eX]

[DOI]

Christine Zarges

Theor. Comput. Sci., 2019

On the Runtime Analysis of the Clearing Diversity-Preserving Mechanism.

[BibT_eX]

[DOI]

Evol. Comput., 2019

On the Choice of the Update Strength in Estimation-of-Distribution Algorithms and Ant Colony Optimization.

[BibT_eX]

[DOI]

Algorithmica, 2019

On the Analysis of Trajectory-Based Search Algorithms: When is it Beneficial to Reject Improvements?

[BibT_eX]

[DOI]

Algorithmica, 2019

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

[BibT_eX]

[DOI]

Carola Doerr

Algorithmica, 2019

On the impact of the cutoff time on the performance of algorithm configurators.

[BibT_eX]

[DOI]

Proceedings of the Genetic and Evolutionary Computation Conference, 2019

Runtime analysis of randomized search heuristics for dynamic graph coloring.

[BibT_eX]

[DOI]

Proceedings of the Genetic and Evolutionary Computation Conference, 2019

Time complexity analysis of RLS and (1 + 1) EA for the edge coloring problem.

[BibT_eX]

[DOI]

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

2018

Escaping Local Optima Using Crossover With Emergent Diversity.

[BibT_eX]

[DOI]

IEEE Trans. Evol. Comput., 2018

The Benefits of Population Diversity in Evolutionary Algorithms: A Survey of Rigorous Runtime Analyses.

[BibT_eX]

[DOI]

CoRR, 2018

How to Escape Local Optima in Black Box Optimisation: When Non-elitism Outperforms Elitism.

[BibT_eX]

[DOI]

Algorithmica, 2018

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

[BibT_eX]

[DOI]

Timo Kötzing

Algorithmica, 2018

Tutorials at PPSN 2018.

[BibT_eX]

[DOI]

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

Empirical Analysis of Diversity-Preserving Mechanisms on Example Landscapes for Multimodal Optimisation.

[BibT_eX]

[DOI]

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

On the robustness of evolutionary algorithms to noise: refined results and an example where noise helps.

[BibT_eX]

[DOI]

Proceedings of the Genetic and Evolutionary Computation Conference, 2018

Runtime analysis of probabilistic crowding and restricted tournament selection for bimodal optimisation.

[BibT_eX]

[DOI]

Proceedings of the Genetic and Evolutionary Computation Conference, 2018

Memetic algorithms beat evolutionary algorithms on the class of hurdle problems.

[BibT_eX]

[DOI]

Phan Trung Hai Nguyen

Proceedings of the Genetic and Evolutionary Computation Conference, 2018

Medium step sizes are harmful for the compact genetic algorithm.

[BibT_eX]

[DOI]

Proceedings of the Genetic and Evolutionary Computation Conference, 2018

2017

How Crossover Speeds up Building Block Assembly in Genetic Algorithms.

[BibT_eX]

[DOI]

Evol. Comput., 2017

Expected Fitness Gains of Randomized Search Heuristics for the Traveling Salesperson Problem.

[BibT_eX]

[DOI]

Samadhi Nallaperuma

Evol. Comput., 2017

Principled Design and Runtime Analysis of Abstract Convex Evolutionary Search.

[BibT_eX]

[DOI]

Alberto Moraglio

Evol. Comput., 2017

Towards a Runtime Comparison of Natural and Artificial Evolution.

[BibT_eX]

[DOI]

Algorithmica, 2017

On Easiest Functions for Mutation Operators in Bio-Inspired Optimisation.

[BibT_eX]

[DOI]

Algorithmica, 2017

Theory of swarm intelligence: tutorial at GECCO 2017.

[BibT_eX]

[DOI]

Proceedings of the Genetic and Evolutionary Computation Conference, 2017

Speeding up evolutionary multi-objective optimisation through diversity-based parent selection.

[BibT_eX]

[DOI]

Proceedings of the Genetic and Evolutionary Computation Conference, 2017

When is it beneficial to reject improvements?

[BibT_eX]

[DOI]

Proceedings of the Genetic and Evolutionary Computation Conference, 2017

Theoretical results on bet-and-run as an initialisation strategy.

[BibT_eX]

[DOI]

Proceedings of the Genetic and Evolutionary Computation Conference, 2017

Analysis of the Clearing Diversity-Preserving Mechanism.

[BibT_eX]

[DOI]

Proceedings of the 14th ACM/SIGEVO Conference on Foundations of Genetic Algorithms, 2017

2016

Escaping Local Optima using Crossover with Emergent or Reinforced Diversity.

[BibT_eX]

[DOI]

CoRR, 2016

Tutorials at PPSN 2016.

[BibT_eX]

[DOI]

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

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

[BibT_eX]

[DOI]

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

Update Strength in EDAs and ACO: How to Avoid Genetic Drift.

[BibT_eX]

[DOI]

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

Theory of Swarm Intelligence.

[BibT_eX]

[DOI]

Proceedings of the Genetic and Evolutionary Computation Conference, 2016

When Non-Elitism Outperforms Elitism for Crossing Fitness Valleys.

[BibT_eX]

[DOI]

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

Runtime Analysis for the Parameter-less Population Pyramid.

[BibT_eX]

[DOI]

Brian W. Goldman

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

Escaping Local Optima with Diversity Mechanisms and Crossover.

[BibT_eX]

[DOI]

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

2015

Parallel Evolutionary Algorithms.

[BibT_eX]

[DOI]

Proceedings of the Springer Handbook of Computational Intelligence, 2015

Design and analysis of different alternating variable searches for search-based software testing.

[BibT_eX]

[DOI]

Joseph Kempka

Phil McMinn

Theor. Comput. Sci., 2015

Design and Analysis of Schemes for Adapting Migration Intervals in Parallel Evolutionary Algorithms.

[BibT_eX]

[DOI]

Andrea Mambrini

Evol. Comput., 2015

First Steps Towards a Runtime Comparison of Natural and Artificial Evolution.

[BibT_eX]

[DOI]

Proceedings of the Genetic and Evolutionary Computation Conference, 2015

On Easiest Functions for Somatic Contiguous Hypermutations And Standard Bit Mutations.

[BibT_eX]

[DOI]

Proceedings of the Genetic and Evolutionary Computation Conference, 2015

Black-box Complexity of Parallel Search with Distributed Populations.

[BibT_eX]

[DOI]

Golnaz Badkobeh

Per Kristian Lehre

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

2014

Improved Evolutionary Algorithm Design for the Project Scheduling Problem Based on Runtime Analysis.

[BibT_eX]

[DOI]

Leandro L. Minku

Xin Yao

IEEE Trans. Software Eng., 2014

The choice of the offspring population size in the (1, λ) evolutionary algorithm.

[BibT_eX]

[DOI]

Jonathan E. Rowe

Theor. Comput. Sci., 2014

Analysis of speedups in parallel evolutionary algorithms and (1+λ) EAs for combinatorial optimization.

[BibT_eX]

[DOI]

Theor. Comput. Sci., 2014

General Upper Bounds on the Runtime of Parallel Evolutionary Algorithms.

[BibT_eX]

[DOI]

Evol. Comput., 2014

On the Runtime Analysis of Fitness Sharing Mechanisms.

[BibT_eX]

[DOI]

Christine Zarges

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

Unbiased Black-Box Complexity of Parallel Search.

[BibT_eX]

[DOI]

Golnaz Badkobeh

Per Kristian Lehre

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

On the runtime analysis of stochastic ageing mechanisms.

[BibT_eX]

[DOI]

Proceedings of the Genetic and Evolutionary Computation Conference, 2014

A fixed budget analysis of randomized search heuristics for the traveling salesperson problem.

[BibT_eX]

[DOI]

Samadhi Nallaperuma

Proceedings of the Genetic and Evolutionary Computation Conference, 2014

Design and analysis of adaptive migration intervals in parallel evolutionary algorithms.

[BibT_eX]

[DOI]

Andrea Mambrini

Proceedings of the Genetic and Evolutionary Computation Conference, 2014

2013

A New Method for Lower Bounds on the Running Time of Evolutionary Algorithms.

[BibT_eX]

[DOI]

IEEE Trans. Evol. Comput., 2013

Design and analysis of migration in parallel evolutionary algorithms.

[BibT_eX]

[DOI]

Soft Comput., 2013

Mutation Rate Matters Even When Optimizing Monotonic Functions.

[BibT_eX]

[DOI]

Evol. Comput., 2013

A theoretical runtime and empirical analysis of different alternating variable searches for search-based testing.

[BibT_eX]

[DOI]

Joseph Kempka

Phil McMinn

Proceedings of the Genetic and Evolutionary Computation Conference, 2013

When do evolutionary algorithms optimize separable functions in parallel?

[BibT_eX]

[DOI]

Benjamin Doerr

Proceedings of the Foundations of Genetic Algorithms XII, 2013

2012

Parametrization and Balancing Local and Global Search.

[BibT_eX]

[DOI]

Proceedings of the Handbook of Memetic Algorithms, 2012

Running time analysis of Ant Colony Optimization for shortest path problems.

[BibT_eX]

[DOI]

Christian Thyssen

J. Discrete Algorithms, 2012

General Upper Bounds on the Running Time of Parallel Evolutionary Algorithms

[BibT_eX]

[DOI]

CoRR, 2012

A Simple Ant Colony Optimizer for Stochastic Shortest Path Problems.

[BibT_eX]

[DOI]

Christian Thyssen

Algorithmica, 2012

Homogeneous and Heterogeneous Island Models for the Set Cover Problem.

[BibT_eX]

[DOI]

Andrea Mambrini

Xin Yao

Proceedings of the Parallel Problem Solving from Nature - PPSN XII, 2012

Crossover speeds up building-block assembly.

[BibT_eX]

[DOI]

Proceedings of the Genetic and Evolutionary Computation Conference, 2012

The choice of the offspring population size in the (1, λ) EA.

[BibT_eX]

[DOI]

Jonathan E. Rowe

Proceedings of the Genetic and Evolutionary Computation Conference, 2012

Runtime analysis of convex evolutionary search.

[BibT_eX]

[DOI]

Alberto Moraglio

Proceedings of the Genetic and Evolutionary Computation Conference, 2012

Evolutionary algorithms for the project scheduling problem: runtime analysis and improved design.

[BibT_eX]

[DOI]

Leandro L. Minku

Xin Yao

Proceedings of the Genetic and Evolutionary Computation Conference, 2012

2011

Runtime analysis of the 1-ANT ant colony optimizer.

[BibT_eX]

[DOI]

Theor. Comput. Sci., 2011

Memetic Algorithms: Parametrization and Balancing Local and Global Search

[BibT_eX]

[DOI]

CoRR, 2011

Analysis of Speedups in Parallel Evolutionary Algorithms for Combinatorial Optimization

[BibT_eX]

[DOI]

CoRR, 2011

Hybridizing Evolutionary Algorithms with Variable-Depth Search to Overcome Local Optima.

[BibT_eX]

[DOI]

Algorithmica, 2011

Analysis of Speedups in Parallel Evolutionary Algorithms for Combinatorial Optimization - (Extended Abstract).

[BibT_eX]

[DOI]

Proceedings of the Algorithms and Computation - 22nd International Symposium, 2011

On the effectiveness of crossover for migration in parallel evolutionary algorithms.

[BibT_eX]

[DOI]

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

How crossover helps in pseudo-boolean optimization.

[BibT_eX]

[DOI]

Timo Kötzing

Madeleine Theile

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

Using markov-chain mixing time estimates for the analysis of ant colony optimization.

[BibT_eX]

[DOI]

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

Adaptive population models for offspring populations and parallel evolutionary algorithms.

[BibT_eX]

[DOI]

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

Simple max-min ant systems and the optimization of linear pseudo-boolean functions.

[BibT_eX]

[DOI]

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

Memetic Evolutionary Algorithms.

[BibT_eX]

[DOI]

Proceedings of the Theory of Randomized Search Heuristics: Foundations and Recent Developments., 2011

2010

Runtime analysis of a binary particle swarm optimizer.

[BibT_eX]

[DOI]

Theor. Comput. Sci., 2010

A self-stabilizing algorithm for cut problems in synchronous networks.

[BibT_eX]

[DOI]

Thomas Sauerwald

Theor. Comput. Sci., 2010

Analysis of an Asymmetric Mutation Operator.

[BibT_eX]

[DOI]

Thomas Jansen

Evol. Comput., 2010

General Lower Bounds for the Running Time of Evolutionary Algorithms.

[BibT_eX]

[DOI]

Proceedings of the Parallel Problem Solving from Nature, 2010

General Scheme for Analyzing Running Times of Parallel Evolutionary Algorithms.

[BibT_eX]

[DOI]

Proceedings of the Parallel Problem Solving from Nature, 2010

Experimental Supplements to the Theoretical Analysis of Migration in the Island Model.

[BibT_eX]

[DOI]

Proceedings of the Parallel Problem Solving from Nature, 2010

Optimizing Monotone Functions Can Be Difficult.

[BibT_eX]

[DOI]

Proceedings of the Parallel Problem Solving from Nature, 2010

Analysis of an Iterated Local Search Algorithm for Vertex Coloring.

[BibT_eX]

[DOI]

Christine Zarges

Proceedings of the Algorithms and Computation - 21st International Symposium, 2010

A few ants are enough: ACO with iteration-best update.

[BibT_eX]

[DOI]

Proceedings of the Genetic and Evolutionary Computation Conference, 2010

The benefit of migration in parallel evolutionary algorithms.

[BibT_eX]

[DOI]

Proceedings of the Genetic and Evolutionary Computation Conference, 2010

Ant colony optimization for stochastic shortest path problems.

[BibT_eX]

[DOI]

Christian Horoba

Proceedings of the Genetic and Evolutionary Computation Conference, 2010

2009

Computational Complexity of Ant Colony Optimization and Its Hybridization with Local Search.

[BibT_eX]

[DOI]

Proceedings of the Innovations in Swarm Intelligence, 2009

The impact of parametrization in memetic evolutionary algorithms.

[BibT_eX]

[DOI]

Theor. Comput. Sci., 2009

Analysis of different MMAS ACO algorithms on unimodal functions and plateaus.

[BibT_eX]

[DOI]

Swarm Intell., 2009

Ingo Wegener.

[BibT_eX]

[DOI]

Evol. Comput., 2009

Analysis of Diversity-Preserving Mechanisms for Global Exploration.

[BibT_eX]

[DOI]

Evol. Comput., 2009

Running Time Analysis of ACO Systems for Shortest Path Problems.

[BibT_eX]

[DOI]

Christian Horoba

Proceedings of the Engineering Stochastic Local Search Algorithms. Designing, 2009

2008

Computational complexity of evolutionary algorithms, hybridizations, and swarm intelligence.

[BibT_eX]

[DOI]

PhD thesis, 2008

Self-stabilizing Cuts in Synchronous Networks.

[BibT_eX]

[DOI]

Thomas Sauerwald

Proceedings of the Structural Information and Communication Complexity, 2008

Runtime analysis of binary PSO.

[BibT_eX]

[DOI]

Proceedings of the Genetic and Evolutionary Computation Conference, 2008

Memetic algorithms with variable-depth search to overcome local optima.

[BibT_eX]

[DOI]

Proceedings of the Genetic and Evolutionary Computation Conference, 2008

Theoretical analysis of diversity mechanisms for global exploration.

[BibT_eX]

[DOI]

Proceedings of the Genetic and Evolutionary Computation Conference, 2008

Rigorous Analyses for the Combination of Ant Colony Optimization and Local Search.

[BibT_eX]

[DOI]

Proceedings of the Ant Colony Optimization and Swarm Intelligence, 2008

2007

Comparing Variants of MMAS ACO Algorithms on Pseudo-Boolean Functions.

[BibT_eX]

[DOI]

Proceedings of the Engineering Stochastic Local Search Algorithms. Designing, 2007

On the runtime analysis of the 1-ANT ACO algorithm.

[BibT_eX]

[DOI]

Proceedings of the Genetic and Evolutionary Computation Conference, 2007

2006

Local Search in Evolutionary Algorithms: The Impact of the Local Search Frequency.

[BibT_eX]

[DOI]

Proceedings of the Algorithms and Computation, 17th International Symposium, 2006

On the analysis of the (1+1) memetic algorithm.

[BibT_eX]

[DOI]

Proceedings of the Genetic and Evolutionary Computation Conference, 2006

2005

Crossover is provably essential for the ising model on trees.

[BibT_eX]

[DOI]

Proceedings of the Genetic and Evolutionary Computation Conference, 2005

Design and analysis of an asymmetric mutation operator.

[BibT_eX]

[DOI]

Thomas Jansen