Turnitin
降AI改写
早检测系统
早降重系统
Turnitin-UK版
万方检测-期刊版
维普编辑部版
Grammarly检测
Paperpass检测
checkpass检测
PaperYY检测
Theory of parameter control for discrete black-box optimization: Provable performance gains through dynamic parameter choices
Parameter control is aimed at realizing performance gains through a dynamic choice of the
parameters which determine the behavior of the underlying optimization algorithm. In the …
parameters which determine the behavior of the underlying optimization algorithm. In the …
A survey on recent progress in the theory of evolutionary algorithms for discrete optimization
The theory of evolutionary computation for discrete search spaces has made significant
progress since the early 2010s. This survey summarizes some of the most important recent …
progress since the early 2010s. This survey summarizes some of the most important recent …
Optimal parameter choices via precise black-box analysis
In classical runtime analysis it has been observed that certain working principles of an
evolutionary algorithm cannot be understood by only looking at the asymptotic order of the …
evolutionary algorithm cannot be understood by only looking at the asymptotic order of the …
Does comma selection help to cope with local optima?
One hope of using non-elitism in evolutionary computation is that it aids leaving local
optima. We perform a rigorous runtime analysis of a basic non-elitist evolutionary algorithm …
optima. We perform a rigorous runtime analysis of a basic non-elitist evolutionary algorithm …
The (1+λ) evolutionary algorithm with self-adjusting mutation rate
We propose a new way to self-adjust the mutation rate in population-based evolutionary
algorithms. Roughly speaking, it consists of creating half the offspring with a mutation rate …
algorithms. Roughly speaking, it consists of creating half the offspring with a mutation rate …
Self-adjusting mutation rates with provably optimal success rules
The one-fifth success rule is one of the best-known and most widely accepted techniques to
control the parameters of evolutionary algorithms. While it is often applied in the literal …
control the parameters of evolutionary algorithms. While it is often applied in the literal …
Runtime analysis for self-adaptive mutation rates
We propose and analyze a self-adaptive version of the (1, λ) evolutionary algorithm in which
the current mutation rate is part of the individual and thus also subject to mutation. A rigorous …
the current mutation rate is part of the individual and thus also subject to mutation. A rigorous …
A high-efficiency adaptive artificial bee colony algorithm using two strategies for continuous optimization
X Song, M Zhao, Q Yan, S **ng - Swarm and Evolutionary Computation, 2019 - Elsevier
It has always been a problem faced by Artificial Bee Colony (ABC) algorithm that how to
adjust exploration and exploitation dynamically in the evolution process. In order to …
adjust exploration and exploitation dynamically in the evolution process. In order to …
Stagnation detection with randomized local search
Recently a mechanism called stagnation detection was proposed that automatically adjusts
the mutation rate of evolutionary algorithms when they encounter local optima. The so-called …
the mutation rate of evolutionary algorithms when they encounter local optima. The so-called …
Significance-based estimation-of-distribution algorithms
Estimation-of-distribution algorithms (EDAs) are randomized search heuristics that maintain
a stochastic model of the solution space. This model is updated from iteration to iteration …
a stochastic model of the solution space. This model is updated from iteration to iteration …