Offspring Population Size Matters when Comparing Evolutionary Algorithms
with Self-Adjusting Mutation Rates

v1v2 (latest)

Offspring Population Size Matters when Comparing Evolutionary Algorithms with Self-Adjusting Mutation Rates

17 April 2019

Arina Buzdalova

ArXiv (abs)PDF HTML

Papers citing "Offspring Population Size Matters when Comparing Evolutionary Algorithms with Self-Adjusting Mutation Rates"

6 / 6 papers shown

Title
Self-adjusting Population Sizes for the $(1, λ)$ -EA on Monotone Functions Marc Kaufmann Maxime Larcher Johannes Lengler Xun Zou 115 10 0 01 Apr 2022
Hybridizing the 1/5-th Success Rule with Q-Learning for Controlling the Mutation Rate of an Evolutionary Algorithm Arina Buzdalova Carola Doerr A. Rodionova 31 3 0 19 Jun 2020
Evolutionary Algorithms with Self-adjusting Asymmetric Mutation A. Rajabi Carsten Witt 94 7 0 16 Jun 2020
Self-Adjusting Evolutionary Algorithms for Multimodal Optimization A. Rajabi Carsten Witt 91 63 0 07 Apr 2020
Benchmarking Discrete Optimization Heuristics with IOHprofiler Carola Doerr Furong Ye Naama Horesh Hao Wang O. M. Shir Thomas Bäck 91 73 0 19 Dec 2019
Self-Adjusting Mutation Rates with Provably Optimal Success Rules Benjamin Doerr Carola Doerr Johannes Lengler 161 50 0 07 Feb 2019