Analysing the scalability of multiobjective evolutionary algorithms when solving the motif discovery problem
type: Item
instance of: scholarly article
title: Analysing the scalability of multiobjective evolutionary algorithms when solving the motif discovery problem
zbMATH Open document ID: 1315.90044
author: David L. González-Álvarez
author: Miguel A. Vega-Rodríguez
published in: Journal of Global Optimization
publication date: 2013-11-07T00:00:00Z
Mathematics Subject Classification ID: 90C29
Mathematics Subject Classification ID: 92D10
Mathematics Subject Classification ID: 92D20
zbMATH DE Number: 6223488
zbMATH Keywords: computer science
zbMATH Keywords: scalability analysis
zbMATH Keywords: multiobjective programming
zbMATH Keywords: evolutionary algorithm
zbMATH Keywords: DNA
describes a project that uses: SPEA2
describes a project that uses: GSA
describes a project that uses: ABC
MaRDI profile type: Publication
full work available at URL: s10898-013-0069-7
OpenAlex ID: W2136127214
cites work: Multi-objective optimization using evolutionary algorithms
cites work: Variable neighborhood search
cites work: GSA: A gravitational search algorithm
cites work: Q4667603
cites work: Q3416765
cites work: Differential evolution -- a simple and efficient heuristic for global optimization over continuous spaces
cites work: Firefly Algorithms for Multimodal Optimization
DOI: 10.1007/S10898-013-0069-7
description: scientific article; zbMATH DE number 6223488