Self-adaptation in non-Elitist Evolutionary Algorithms on Discrete Problems with Unknown Structure

IEEE Transactions on Evolutionary Computation (TEVC), 2020

1 April 2020

B. Case

Per Kristian Lehre

ArXiv (abs)PDF HTML

Papers citing "Self-adaptation in non-Elitist Evolutionary Algorithms on Discrete Problems with Unknown Structure"

9 / 9 papers shown

Concentration Tail-Bound Analysis of Coevolutionary and Bandit Learning Algorithms

Per Kristian Lehre

Shishen Lin

350

07 May 2024

Fast Estimations of Hitting Time of Elitist Evolutionary Algorithms from Fitness Levels

Jun He

Siang Yew Chong

Xin Yao

452

17 Nov 2023

Drift Analysis with Fitness Levels for Elitist Evolutionary AlgorithmsEvolutionary Computation (Evol. Comput.), 2023

Jun He

Yuren Zhou

455

02 Sep 2023

Crossover Can Guarantee Exponential Speed-Ups in Evolutionary Multi-Objective OptimisationArtificial Intelligence (AIJ), 2023

D. Dang

Andre Opris

Dirk Sudholt

373

31 Jan 2023

Self-adjusting Population Sizes for the

(1, λ)

-EA on Monotone FunctionsParallel Problem Solving from Nature (PPSN), 2022

335

01 Apr 2022

Self-Adjusting Population Sizes for Non-Elitist Evolutionary Algorithms: Why Success Rates MatterAnnual Conference on Genetic and Evolutionary Computation (GECCO), 2021

Mario Alejandro Hevia Fajardo

Dirk Sudholt

330

12 Apr 2021

Modelling SARS-CoV-2 coevolution with genetic algorithms

A. Vié

213

24 Feb 2021

Qualities, challenges and future of genetic algorithms: a literature review

A. Vié

Alissa M. Kleinnijenhuis

Doyne, J Farmer

AI4CE

335

05 Nov 2020

A Survey on Recent Progress in the Theory of Evolutionary Algorithms for Discrete Optimization

Benjamin Doerr

Frank Neumann

392

30 Jun 2020