Local dominance and controlling dominance area of solutions in multi and many objectives EAs

Authors:
Hiroyuki Sato;Hernan E. Aguirre;Kiyoshi Tanaka
Affiliations:
Shinshu University, Nagano, Japan;Shinshu University, Nagano, Japan;Shinshu University, Nagano, Japan
Venue:
Proceedings of the 10th annual conference companion on Genetic and evolutionary computation
Year:
2008

Citing 3
Cited 1

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Abstract

This work presents local dominance with alignment of principle search direction and control of dominance area of solutions to enhance selection of MOEAs, aiming to improve their performance on multi and many objectives combinatorial problems. We show that the methods used independently can substantially improve either diversity or convergence. Also, by including control of dominance area of solutions within the local dominance algorithm, we show that diversity and convergence can improve simultaneously while reducing the computational cost of the algorithm.