Memorias de investigación
Communications at congresses:
Quantitative Genetics in Multi-Objective Optimization Algorithms: From Useful Insights to Effective Methods
Year:2011

Research Areas
  • Artificial intelligence

Information
Abstract
This paper shows that statistical algorithms proposed for the quantitative trait loci (QTL) mapping problem, and the equation of the multivariate response to selection can be of application in multi-objective optimization. We introduce the conditional dominance relationships between the objectives and propose the use of results from QTL analysis and G-matrix theory to the analysis of multi-objective evolutionary algorithms (MOEAs).
International
Si
Congress
13th annual conference on Genetic and evolutionary computation (GECCO'11)
960
Place
Dublin, Ireland
Reviewers
Si
ISBN/ISSN
978-1-4503-0690-4
Start Date
12/07/2011
End Date
16/07/2011
From page
91
To page
92
Proceedings of the 13th annual conference on Genetic and evolutionary computation
Participants

Research Group, Departaments and Institutes related
  • Creador: Grupo de Investigación: COMPUTATIONAL INTELLIGENCE GROUP
  • Centro o Instituto I+D+i: Centro de tecnología Biomédica CTB
  • Departamento: Inteligencia Artificial