Carsten Witt

发表

Runtime Analysis of a Simple Ant Colony Optimization Algorithm

Frank Neumann, Carsten Witt, 2006, ISAAC.

An Analysis of the (µ+1) EA on Simple Pseudo-Boolean Functions

Carsten Witt, C. Witt, 2004, GECCO.

Über die Analyse randomisierter Suchheuristiken und den Entwurf spezialisierter Algorithmen im Bereich der kombinatorischen Optimierung

Carsten Witt, C. Witt, 2004, Ausgezeichnete Informatikdissertationen.

The Impact of Migration Topology on the Runtime of Island Models in Dynamic Optimization

Carsten Witt, Andrei Lissovoi, 2016, GECCO.

Theory of estimation-of-distribution algorithms

Carsten Witt, C. Witt, 2020, GECCO Companion.

Fitness levels with tail bounds for the analysis of randomized search heuristics

Carsten Witt, C. Witt, 2014, Inf. Process. Lett..

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

Dirk Sudholt, Frank Neumann, Carsten Witt, 2010, GECCO '10.

Analyzing Stochastic Search Algorithms

Frank Neumann, Carsten Witt, 2010 .

Analysis of an iterated local search algorithm for vertex cover in sparse random graphs

Carsten Witt, C. Witt, 2012, Theor. Comput. Sci..

Guest Editorial: Theory of Evolutionary Computation

Benjamin Doerr, Carsten Witt, 2016, Algorithmica.

Greedy Local Search and Vertex Cover in Sparse Random Graphs

Carsten Witt, C. Witt, 2009, TAMC.

Optimal Mutation Rates for the (1+$$\lambda $$λ) EA on OneMax Through Asymptotically Tight Drift Analysis

Carsten Witt, Christian Gießen, 2017, Algorithmica.

Erratum: Simplified Drift Analysis for Proving Lower Bounds in Evolutionary Computation

Pietro Simone Oliveto, Carsten Witt, 2008, PPSN.

Theory of Randomized Search Heuristics

Anne Auger, Carsten Witt, 2012, Algorithmica.

Revised analysis of the (1+1) ea for the minimum spanning tree problem

Carsten Witt, C. Witt, 2014, GECCO.

Ant Colony Optimization and the Minimum Spanning Tree Problem

Frank Neumann, Carsten Witt, 2007, LION.

Analyses of Simple Hybrid Algorithms for the Vertex Cover Problem

Frank Neumann, Tobias Friedrich, Carsten Witt, 2009, Evolutionary Computation.

Approximating Covering Problems by Randomized Search Heuristics Using Multi-Objective Models

Frank Neumann, Tobias Friedrich, Carsten Witt, 2010, Evolutionary Computation.

Quasirandom evolutionary algorithms

Mahmoud Fouz, Benjamin Doerr, Carsten Witt, 2010, GECCO '10.

Analysis of Ant Colony Optimization and Population-Based Evolutionary Algorithms on Dynamic Problems

Carsten Witt, Andrei Lissovoi, Andrei Lissovoi, 2016 .

Springer Handbook of Computational Intelligence

Thomas Bartz-Beielstein, Carlos A. Coello Coello, Günther R. Raidl, 2015, Springer Handbook of Computational Intelligence.

Design and Management of Complex Technical Processes and Systems by Means of Computational Intelligence Methods Theoretical Analysis of Diversity Mechanisms for Global Exploration Theoretical Analysis of Diversity Mechanisms for Global Exploration

Pietro Simone Oliveto, Dirk Sudholt, Tobias Friedrich, 2022 .

Runtime analysis of ant colony optimization on dynamic shortest path problems

Carsten Witt, Andrei Lissovoi, C. Witt, 2013, GECCO '13.

Proceedings of the 14th ACM/SIGEVO Conference on Foundations of Genetic Algorithms, FOGA 2017, Copenhagen, Denmark, January 12-15, 2017

Dirk Sudholt, Christian Igel, Carsten Witt, 2017, FOGA.

Theoretical analysis of fitness-proportional selection: landscapes and efficiency

Pietro Simone Oliveto, Frank Neumann, Carsten Witt, 2009, GECCO.

Improved Fixed-Budget Results via Drift Analysis pdf

Carsten Witt, Timo Kötzing, Timo Kötzing, 2020, PPSN.

Minimum Spanning Trees Made Easier

Frank Neumann, Carsten Witt, C. Witt, 2010 .

Comparing Variants of MMAS ACO Algorithms on Pseudo-Boolean Functions

Dirk Sudholt, Frank Neumann, Carsten Witt, 2007, SLS.

Tight Bounds on the Optimization Time of the (1+1) EA on Linear Functions pdf

Carsten Witt, C. Witt, 2011, ArXiv.

MMAS vs. population-based EA on a family of dynamic fitness functions

Carsten Witt, Andrei Lissovoi, 2014, GECCO.

On the analysis of the simple genetic algorithm

Pietro Simone Oliveto, Carsten Witt, C. Witt, 2012, GECCO '12.

Domino convergence: why one should hill-climb on linear functions

Carsten Witt, C. Witt, 2018, GECCO.

Theory of randomised search heuristics in combinatorial optimisation

Carsten Witt, C. Witt, 2010, GECCO '10.

08051 Abstracts Collection - Theory of Evolutionary Algorithms

Dirk V. Arnold, Carsten Witt, Anne Auger, 2004, Theory of Evolutionary Algorithms.

Theory of estimation-of-distribution algorithms

Carsten Witt, Martin S. Krejca, C. Witt, 2018, GECCO.

Bioinspired computation in combinatorial optimization: algorithms and their computational complexity

Frank Neumann, Carsten Witt, 2012, GECCO '12.

General Drift Analysis with Tail Bounds pdf

Per Kristian Lehre, Carsten Witt, C. Witt, 2013, ArXiv.

Analysis of different MMAS ACO algorithms on unimodal functions and plateaus

Dirk Sudholt, Carsten Witt, Frank Neumann, 2009, Swarm Intelligence.

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

Dirk Sudholt, Frank Neumann, Carsten Witt, 2008, ANTS Conference.

On the influence of pheromone updates in ACO algorithms

Dirk Sudholt, Frank Neumann, Benjamin Doerr, 2007 .

On the runtime analysis of the 1-ANT ACO algorithm

Dirk Sudholt, Frank Neumann, Benjamin Doerr, 2007, GECCO '07.

Ingo Wegener

Dirk Sudholt, Christine Zarges, Carsten Witt, 2009, Evolutionary Computation.

The Impact of a Sparse Migration Topology on the Runtime of Island Models in Dynamic Optimization

Carsten Witt, Andrei Lissovoi, C. Witt, 2017, Algorithmica.

Runtime Analysis for Self-adaptive Mutation Rates

Benjamin Doerr, Jing Yang, Carsten Witt, 2018, Algorithmica.

On the Runtime of Randomized Local Search and Simple Evolutionary Algorithms for Dynamic Makespan Scheduling

Frank Neumann, Carsten Witt, C. Witt, 2015, IJCAI.

Bioinspired Computation in Combinatorial Optimization

Carsten Witt, Frank Neumann, C. Witt, 2010, Bioinspired Computation in Combinatorial Optimization.

Improved time complexity analysis of the Simple Genetic Algorithm

Pietro Simone Oliveto, Carsten Witt, C. Witt, 2015, Theor. Comput. Sci..

Computational Complexity of Evolutionary Computation in Combinatorial Optimisation

Frank Neumann, Carsten Witt, C. Witt, 2008 .

UNIVERSITY OF DORTMUND REIHE COMPUTATIONAL INTELLIGENCE COLLABORATIVE RESEARCH CENTER 531 Design and Management of Complex Technical Processes and Systems by means of Computational Intelligence Methods Worst-Case and Average-Case Approximations by Simple Randomized Search Heuristics

Carsten Witt, C. Witt, 2004 .

Theoretical Properties of Two ACO Approaches for the Traveling Salesman Problem

Frank Neumann, Carsten Witt, Timo Kötzing, 2010, ANTS Conference.

Population Size vs. Mutation Strength for the (1+λ) EA on OneMax

Carsten Witt, Christian Gießen, C. Witt, 2015, GECCO.

Bioinspired computation in combinatorial optimization: algorithms and their computational complexity

Frank Neumann, Carsten Witt, C. Witt, 2010, GECCO '12.

Optimizing Linear Functions with Randomized Search Heuristics - The Robustness of Mutation

Carsten Witt, C. Witt, 2012, STACS.

Lower Bounds on the Runtime of Crossover-Based Algorithms via Decoupling and Family Graphs

Andrew M. Sutton, Carsten Witt, C. Witt, 2019, Algorithmica.

Optimal Mutation Rates for the (1+λ\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\lambda $$\end{document}) EA on One

Carsten Witt, Christian Gießen, C. Witt, 2017, Algorithmica.

The (1+λ) evolutionary algorithm with self-adjusting mutation rate

Benjamin Doerr, Jing Yang, Carsten Witt, 2017, GECCO.

Stochastic Search Algorithms

Frank Neumann, Carsten Witt, 2010 .

Lower bounds on the run time of the Univariate Marginal Distribution Algorithm on OneMax

Carsten Witt, Martin S. Krejca, 2020, Theor. Comput. Sci..

A Note on Problem Difficulty Measures in Black-Box Optimization: Classification, Realizations and Predictability

Xin Yao, Colin R. Reeves, Carsten Witt, 2007, Evolutionary Computation.

Upper Bounds on the Running Time of the Univariate Marginal Distribution Algorithm on OneMax

Carsten Witt, C. Witt, 2018, Algorithmica.

Analysis of Diversity-Preserving Mechanisms for Global Exploration

Pietro Simone Oliveto, Dirk Sudholt, Tobias Friedrich, 2009, Evolutionary Computation.

Detecting structural breaks in time series via genetic algorithms

Benjamin Doerr, Carsten Witt, Paul Fischer, 2017, Soft Comput..

Self-Adjusting Evolutionary Algorithms for Multimodal Optimization

Carsten Witt, Amirhossein Rajabi, C. Witt, 2020, Algorithmica.

The Interplay of Population Size and Mutation Probability in the ($$1+\lambda $$1+λ) EA on OneMax

Carsten Witt, Christian Gießen, 2016, Algorithmica.

Theory of randomized search heuristics in combinatorial optimization

Carsten Witt, 2011, GECCO '11.

A Runtime Analysis of Parallel Evolutionary Algorithms in Dynamic Optimization

Carsten Witt, Andrei Lissovoi, C. Witt, 2016, Algorithmica.

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

Dirk Sudholt, Frank Neumann, Carsten Witt, 2009, Innovations in Swarm Intelligence.

Sharp bounds by probability-generating functions and variable drift

Mahmoud Fouz, Benjamin Doerr, Carsten Witt, 2011, GECCO '11.

Rigorous Runtime Analysis of Swarm Intelligence Algorithms – An Overview

Carsten Witt, C. Witt, 2009 .

Evolutionary algorithms for the detection of structural breaks in time series: extended abstract

Benjamin Doerr, Carsten Witt, Paul Fischer, 2013, GECCO '13 Companion.

Runtime analysis of binary PSO

Dirk Sudholt, Carsten Witt, C. Witt, 2008, GECCO '08.

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

Dirk Sudholt, Carsten Witt, Pietro S. Oliveto, 2020, GECCO.

When do evolutionary algorithms optimize separable functions in parallel?

Dirk Sudholt, Benjamin Doerr, Carsten Witt, 2013, FOGA XII '13.

Combinatorial Optimization and Computational Complexity

Frank Neumann, Carsten Witt, C. Witt, 2010 .

The Impact of Parametrization on Randomized Search Heuristics

Carsten Witt, Christian Gießen, C. Gießen, 2018 .

(1+1) EA on Generalized Dynamic OneMax

Carsten Witt, Timo Kötzing, Andrei Lissovoi, 2015, FOGA.

10361 Abstracts Collection and Executive Summary - Theory of Evolutionary Algorithms

Anne Auger, L. Darrell Whitley, Carsten Witt, 2010, Theory of Evolutionary Algorithms.

Runtime analysis of a binary particle swarm optimizer

Dirk Sudholt, Carsten Witt, C. Witt, 2010, Theor. Comput. Sci..

Tight Bounds on the Optimization Time of a Randomized Search Heuristic on Linear Functions†

Carsten Witt, C. Witt, 2013, Combinatorics, Probability and Computing.

08051 Executive Summary - Theory of Evolutionary Algorithms

Anne Auger, Dirk V. Arnold, Carsten Witt, 2008, Theory of Evolutionary Algorithms.

Edge-matching Problems with Rotations

Carsten Witt, Paul Fischer, Martin Ebbesen, 2011, FCT.

Theoretical analysis of two ACO approaches for the traveling salesman problem

Frank Neumann, Carsten Witt, Timo Kötzing, 2011, Swarm Intelligence.

GECCO ’14: Proceedings of the 2014 conference on Genetic and evolutionary computation

Julian Togelius, Christine Zarges, Hitoshi Iba, 2014 .

Improved Runtime Results for Simple Randomised Search Heuristics on Linear Functions with a Uniform Constraint

Mojgan Pourhassan, Frank Neumann, Carsten Witt, 2019, Algorithmica.

Bioinspired computation in combinatorial optimization: algorithms and their computational complexity

Carsten Witt, 2014, GECCO.

Ant Colony Optimization and the minimum spanning tree problem

Frank Neumann, Carsten Witt, 2010, Theor. Comput. Sci..

Sharp bounds on the runtime of the (1+1) EA via drift analysis and analytic combinatorial tools

Hsien-Kuei Hwang, Carsten Witt, C. Witt, 2019, FOGA '19.

On the analysis of a simple evolutionary algorithm on quadratic pseudo-boolean functions

Ingo Wegener, Carsten Witt, I. Wegener, 2005, J. Discrete Algorithms.

Black-Box Search by Unbiased Variation

Per Kristian Lehre, Carsten Witt, C. Witt, 2010, GECCO '10.

Rigorous runtime analysis of a (μ+1)ES for the sphere function

Jens Jägersküpper, Carsten Witt, C. Witt, 2005, GECCO '05.

On the runtime analysis of the Simple Genetic Algorithm

Pietro Simone Oliveto, Carsten Witt, C. Witt, 2014, Theor. Comput. Sci..

Runtime analysis of the 1-ANT ant colony optimizer

Dirk Sudholt, Frank Neumann, Benjamin Doerr, 2011, Theor. Comput. Sci..

Why standard particle swarm optimisers elude a theoretical runtime analysis

Carsten Witt, C. Witt, 2009, FOGA '09.

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

Dirk Sudholt, Carsten Witt, C. Witt, 2016, GECCO.

Collaborative Research Centre 531: Computational Intelligence – Theory and Practice (Sonderforschungsbereich 531: Computational Intelligence – Theorie und Praxis)

Carsten Witt, Jörn Mehnen, Thomas Michelitsch, 2007, it Inf. Technol..

On the Optimization of Monotone Polynomials by Simple Randomized Search Heuristics

Ingo Wegener, Carsten Witt, I. Wegener, 2005, Combinatorics, Probability and Computing.

Session details: Theory track papers

Anne Auger, Carsten Witt, 2011, GECCO '11.

Runtime Analysis of the ( + 1) EA on Simple Pseudo-Boolean Functions

Carsten Witt, C. Witt, 2006, Evolutionary Computation.

Lower Bounds on the Run Time of the Univariate Marginal Distribution Algorithm on OneMax

Carsten Witt, Martin S. Krejca, C. Witt, 2017, FOGA '17.

Population size versus runtime of a simple evolutionary algorithm

Carsten Witt, C. Witt, 2008, Theor. Comput. Sci..

Theory of randomised search heuristics in combinatorial optimisation: an algorithmic point of view

Carsten Witt, 2008, GECCO '08.

The Fitness Level Method with Tail Bounds pdf

Carsten Witt, 2013, ArXiv.

Medium step sizes are harmful for the compact genetic algorithm

Dirk Sudholt, Carsten Witt, Johannes Lengler, 2018, GECCO.

On the Utility of Island Models in Dynamic Optimization

Carsten Witt, Andrei Lissovoi, C. Witt, 2015, GECCO.

Runtime analysis of ant colony optimization on dynamic shortest path problems

Carsten Witt, Andrei Lissovoi, 2015, Theor. Comput. Sci..

Improved runtime analysis of the simple genetic algorithm

Pietro Simone Oliveto, Carsten Witt, C. Witt, 2013, GECCO '13.

Minimum Spanning Trees

Frank Neumann, Carsten Witt, 2010 .

Simplified Drift Analysis for Proving Lower Bounds in Evolutionary Computation

Pietro Simone Oliveto, Carsten Witt, C. Witt, 2008, Algorithmica.

Minimizing Stall Time in Single and Parallel Disk Systems Using Multicommodity Network Flows

Susanne Albers, Carsten Witt, 2001, RANDOM-APPROX.

MMAS Versus Population-Based EA on a Family of Dynamic Fitness Functions

Carsten Witt, Andrei Lissovoi, C. Witt, 2014, Algorithmica.

Evolutionary Algorithms with Self-adjusting Asymmetric Mutation pdf

Carsten Witt, Amirhossein Rajabi, 2020, PPSN.

A method to derive fixed budget results from expected optimisation times

Thomas Jansen, Christine Zarges, Benjamin Doerr, 2013, GECCO '13.

Approximating Covering Problems by Randomized Search Heuristics Using Multi-Objective Models

Carsten Witt, Nils Hebbinghaus, Frank Neumann, 2007, Evolutionary Computation.

Theory of estimation-of-distribution algorithms

Carsten Witt, C. Witt, 2019, GECCO.

Theory of Particle Swarm Optimization

Carsten Witt, C. Witt, 2011, Theory of Randomized Search Heuristics.

Concentrated Hitting Times of Randomized Search Heuristics with Variable Drift

Per Kristian Lehre, Carsten Witt, C. Witt, 2014, ISAAC.

Design and Management of Complex Technical Processes and Systems by Means of Computational Intelligence Methods Runtime Analysis of a Simple Ant Colony Optimization Algorithm Runtime Analysis of a Simple Ant Colony Optimization Algorithm

Frank Neumann, Carsten Witt, C. Witt, 2022 .

The ($$1+\lambda $$1+λ) Evolutionary Algorithm with Self-Adjusting Mutation Rate

Benjamin Doerr, Jing Yang, Carsten Witt, 2018, Algorithmica.

On improving approximate solutions by evolutionary algorithms

Frank Neumann, Tobias Friedrich, Carsten Witt, 2007 .

Finite First Hitting Time versus Stochastic Convergence in Particle Swarm Optimisation pdf

Per Kristian Lehre, Carsten Witt, 2011, ArXiv.

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

Dirk Sudholt, Carsten Witt, C. Witt, 2018, Algorithmica.

On crossing fitness valleys with majority-vote crossover and estimation-of-distribution algorithms

Carsten Witt, 2021, FOGA.

Stagnation detection in highly multimodal fitness landscapes

Carsten Witt, Amirhossein Rajabi, 2021, GECCO.

Improved Runtime Results for Simple Randomised Search Heuristics on Linear Functions with a Uniform Constraint

Mojgan Pourhassan, Frank Neumann, Carsten Witt, 2021, Algorithmica.

Runtime Analysis of Single- and Multi-Objective Evolutionary Algorithms for Chance Constrained Optimization Problems with Normally Distributed Random Variables pdf

Frank Neumann, Carsten Witt, 2021, ArXiv.

Stagnation Detection with Randomized Local Search pdf

Carsten Witt, Amirhossein Rajabi, 2021, EvoCOP.

The Complex Parameter Landscape of the Compact Genetic Algorithm

Dirk Sudholt, Carsten Witt, Johannes Lengler, 2020, Algorithmica.

On Steady-State Evolutionary Algorithms and Selective Pressure: Why Inverse Rank-Based Allocation of Reproductive Trials Is Best

Dogan Corus, Carsten Witt, Andrei Lissovoi, 2021, ACM Trans. Evol. Learn. Optim..

Lower Bounds on the Runtime of Crossover-Based Algorithms via Decoupling and Family Graphs

Andrew M. Sutton, Carsten Witt, 2021, Algorithmica.

Runtime Analysis of the ( μ +1) EA on Simple Pseudo-Boolean Functions

Carsten Witt, C. Witt, 2006 .

The Interplay of Population Size and Mutation Probability in the (1+λ) EA on OneMax

Carsten Witt, Christian Gießen, C. Witt, 2017, Algorithmica.