Parallel evolutionary algorithms can achieve super-linear performance
type: Item
instance of: scholarly article
title: Parallel evolutionary algorithms can achieve super-linear performance
zbMATH Open document ID: 1013.68292
DOI: 10.1016/S0020-0190(01)00281-2
author: Enrique Alba
published in: Information Processing Letters
publication date: 2002-07-14T00:00:00Z
Mathematics Subject Classification ID: 68W10
zbMATH DE Number: 1767632
zbMATH Keywords: evolutionary algorithms
zbMATH Keywords: parallel algorithms
zbMATH Keywords: performance evaluation
zbMATH Keywords: super-linear speedup
zbMATH Keywords: serial fraction
MaRDI profile type: Publication
cites work: Analyzing synchronous and asynchronous parallel distributed genetic algorithms
cites work: Heterogeneous computing and parallel genetic algorithms.
cites work: Q5687948
cites work: Anomalies in parallel branch-and-bound algorithms
full work available at URL: s0020-0190(01)00281-2
OpenAlex ID: W2104805479
Recommended article: Achieving super-linear performance in parallel multi-objective evolutionary algorithms by means of cooperative coevolution
Recommended article: Q3491371
Recommended article: Q4945605
Recommended article: Parallel Evolutionary Algorithms Performing Pairwise Comparisons
Recommended article: Parallel evolutionary computations.
Recommended article: Q4523517
Recommended article: Q3362436
Recommended article: Parallel implementation of evolution strategy optimization algorithm on multicore processors
Recommended article: Efficient parallel genetic algorithms: Theory and practice
description: scientific article; zbMATH DE number 1767632