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List of works by Carsten Witt

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

Runtime analysis of the (mu+1) EA on simple Pseudo-Boolean functions

scientific article published in January 2006
On the Optimization of Monotone Polynomials by Simple Randomized Search Heuristics

article by INGO WEGENER & Carsten Witt published January 2005 in Combinatorics, Probability and Computing
Sharp bounds by probability-generating functions and variable drift

article
(1+1) EA on Generalized Dynamic OneMax

article
Black-Box Search by Unbiased Variation

Simplified Drift Analysis for Proving Lower Bounds in Evolutionary Computation

Improved time complexity analysis of the Simple Genetic Algorithm

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

Approximating covering problems by randomized search heuristics using multi-objective models

scientific article published on 28 June 2010
Black-box search by unbiased variation

A note on problem difficulty measures in black-box optimization: classification, realizations and predictability

scientific article published in January 2007
Ant Colony Optimization and the minimum spanning tree problem

Quasirandom evolutionary algorithms

scholarly article published 2010
Fitness levels with tail bounds for the analysis of randomized search heuristics

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

article
Population size versus runtime of a simple evolutionary algorithm

article by Carsten Witt published August 2008 in Theoretical Computer Science
On the runtime analysis of the Simple Genetic Algorithm

article
Theoretical analysis of fitness-proportional selection

article
A method to derive fixed budget results from expected optimisation times

A few ants are enough

article published in 2010
Update Strength in EDAs and ACO

article published in 2016
On the analysis of a simple evolutionary algorithm on quadratic pseudo-boolean functions

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

Why standard particle swarm optimisers elude a theoretical runtime analysis

article
Concentrated Hitting Times of Randomized Search Heuristics with Variable Drift

On the Utility of Island Models in Dynamic Optimization

Analysis of diversity-preserving mechanisms for global exploration

scientific article published in January 2009
Theoretical analysis of two ACO approaches for the traveling salesman problem

article
Runtime Analysis of a Simple Ant Colony Optimization Algorithm

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

Runtime analysis of a binary particle swarm optimizer

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

Runtime Analysis of a Simple Ant Colony Optimization Algorithm

article by Frank Neumann & Carsten Witt published 2006 in Lecture Notes in Computer Science
Optimal Mutation Rates for the (1+λ) EA on OneMax

Improved runtime analysis of the simple genetic algorithm

article
Runtime analysis of ant colony optimization on dynamic shortest path problems

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

article
Theoretical Properties of Two ACO Approaches for the Traveling Salesman Problem

A Runtime Analysis of Parallel Evolutionary Algorithms in Dynamic Optimization

scientific article published on 07 December 2016
Ant Colony Optimization and the Minimum Spanning Tree Problem

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

Runtime analysis of ant colony optimization on dynamic shortest path problems

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

Runtime analysis of the 1-ANT ant colony optimizer

Simplified Drift Analysis for Proving Lower Bounds in Evolutionary Computation

On the analysis of the simple genetic algorithm

The compact genetic algorithm struggles on Cliff functions

scientific article published on 08 July 2022
The (1+λ) evolutionary algorithm with self-adjusting mutation rate

On improving approximate solutions by evolutionary algorithms

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