Quantitative genetics in multi-objective optimization algorithms: from useful insights to effective methods

Authors:
Roberto Santana;Hossein Karshenas;Concha Bielza;Pedro Larrañaga
Affiliations:
Universidad Politécnica de Madrid, Madrid, Spain;Universidad Politécnica de Madrid, Madrid, Spain;Universidad Politécnica de Madrid, Madrid, Spain;Universidad Politécnica de Madrid, Madrid, Spain
Venue:
Proceedings of the 13th annual conference companion on Genetic and evolutionary computation
Year:
2011

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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).