
Runtime Analysis of Single and MultiObjective Evolutionary Algorithms for Chance Constrained Optimization Problems with Normally Distributed Random Variables
Chance constrained optimization problems allow to model problems where c...
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Stagnation Detection in Highly Multimodal Fitness Landscapes
Stagnation detection has been proposed as a mechanism for randomized sea...
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On SteadyState Evolutionary Algorithms and Selective Pressure: Why Inverse RankBased Allocation of Reproductive Trials is Best
We analyse the impact of the selective pressure for the global optimisat...
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Stagnation Detection with Randomized Local Search
Recently a mechanism called stagnation detection was proposed that autom...
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Improved Runtime Results for Simple Randomised Search Heuristics on Linear Functions with a Uniform Constraint
In the last decade remarkable progress has been made in development of s...
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Evolutionary Algorithms with Selfadjusting Asymmetric Mutation
Evolutionary Algorithms (EAs) and other randomized search heuristics are...
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Improved FixedBudget Results via Drift Analysis
Fixedbudget theory is concerned with computing or bounding the fitness ...
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SelfAdjusting Evolutionary Algorithms for Multimodal Optimization
Recent theoretical research has shown that selfadjusting and selfadapt...
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Sharp Bounds on the Runtime of the (1+1) EA via Drift Analysis and Analytic Combinatorial Tools
The expected running time of the classical (1+1) EA on the OneMax benchm...
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Runtime Analysis for Selfadaptive Mutation Rates
We propose and analyze a selfadaptive version of the (1,λ) evolutionary...
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Theory of EstimationofDistribution Algorithms
Estimationofdistribution algorithms (EDAs) are general metaheuristics ...
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The (1+λ) Evolutionary Algorithm with SelfAdjusting Mutation Rate
We propose a new way to selfadjust the mutation rate in populationbase...
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Upper Bounds on the Runtime of the Univariate Marginal Distribution Algorithm on OneMax
A runtime analysis of the Univariate Marginal Distribution Algorithm (UM...
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Update Strength in EDAs and ACO: How to Avoid Genetic Drift
We provide a rigorous runtime analysis concerning the update strength, a...
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On the Runtime of Randomized Local Search and Simple Evolutionary Algorithms for Dynamic Makespan Scheduling
Evolutionary algorithms have been frequently used for dynamic optimizati...
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The Fitness Level Method with Tail Bounds
The fitnesslevel method, also called the method of fbased partitions, ...
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General Drift Analysis with Tail Bounds
Drift analysis is one of the stateoftheart techniques for the runtime...
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Erratum: Simplified Drift Analysis for Proving Lower Bounds in Evolutionary Computation
This erratum points out an error in the simplified drift theorem (SDT) [...
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Tight Bounds on the Optimization Time of the (1+1) EA on Linear Functions
The analysis of randomized search heuristics on classes of functions is ...
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Finite First Hitting Time versus Stochastic Convergence in Particle Swarm Optimisation
We reconsider stochastic convergence analyses of particle swarm optimisa...
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Carsten Witt
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