We consider a simple setting in neuroevolution where an evolutionary
alg...
Pareto optimization using evolutionary multi-objective algorithms has be...
The Metropolis algorithm (MA) is a classic stochastic local search heuri...
Evolutionary multi-objective algorithms have successfully been used in t...
Linear functions play a key role in the runtime analysis of evolutionary...
The compact genetic algorithm (cGA) is an non-elitist estimation of
dist...
We prove that Simulated Annealing with an appropriate cooling schedule
c...
Chance constrained optimization problems allow to model problems where
c...
Stagnation detection has been proposed as a mechanism for randomized sea...
We analyse the impact of the selective pressure for the global optimisat...
Recently a mechanism called stagnation detection was proposed that
autom...
In the last decade remarkable progress has been made in development of
s...
Evolutionary Algorithms (EAs) and other randomized search heuristics are...
Fixed-budget theory is concerned with computing or bounding the fitness ...
Recent theoretical research has shown that self-adjusting and self-adapt...
The expected running time of the classical (1+1) EA on the OneMax benchm...
We propose and analyze a self-adaptive version of the (1,λ)
evolutionary...
Estimation-of-distribution algorithms (EDAs) are general metaheuristics ...
We propose a new way to self-adjust the mutation rate in population-base...
A runtime analysis of the Univariate Marginal Distribution Algorithm (UM...
We provide a rigorous runtime analysis concerning the update strength, a...
Evolutionary algorithms have been frequently used for dynamic optimizati...
The fitness-level method, also called the method of f-based partitions, ...
Drift analysis is one of the state-of-the-art techniques for the runtime...
This erratum points out an error in the simplified drift theorem (SDT)
[...
The analysis of randomized search heuristics on classes of functions is
...
We reconsider stochastic convergence analyses of particle swarm optimisa...