Using Dominated Solutions to the Uniformity of Non-dominated Solution Distributions in NSGA-II

Kina Yokoyama, Yuji Sato

2020

Abstract

This paper proposes a method for improving the diversity of the Pareto front in a fast elitist non-dominated sorting genetic algorithm (NSGA-II), which is an evolutionary multi-objective optimization algorithm. Conventional NSGA-II has excellent convergence to the Pareto front, but it has been reported that for some test cases, it does not produce a more diverse solution distribution than the strength Pareto evolutionary algorithm 2 (SPEA2). To avoid this problem, we propose a method that stores an archive of dominated solutions that may be effective in improving diversity in the conventional search process when used for genetic operations. We experimentally compare this approach with the conventional method on the typical multi-objective test problems ZDT1, ZDT2, and ZDT3. By evaluating the performance based on Pareto front diagrams and hypervolume values, we show that the proposed method is effective at improving the diversity at both ends of Pareto optimal front and the uniformity of the solution distribution.

Paper Citation

in Harvard Style

Yokoyama K. and Sato Y. (2020). Using Dominated Solutions to the Uniformity of Non-dominated Solution Distributions in NSGA-II. In Proceedings of the 12th International Joint Conference on Computational Intelligence (IJCCI 2020) - Volume 1: ECTA; ISBN 978-989-758-475-6, SciTePress, pages 212-219. DOI: 10.5220/0010143502120219

in Bibtex Style

@conference{ecta20,
author={Kina Yokoyama and Yuji Sato},
title={Using Dominated Solutions to the Uniformity of Non-dominated Solution Distributions in NSGA-II},
booktitle={Proceedings of the 12th International Joint Conference on Computational Intelligence (IJCCI 2020) - Volume 1: ECTA},
year={2020},
pages={212-219},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010143502120219},
isbn={978-989-758-475-6},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 12th International Joint Conference on Computational Intelligence (IJCCI 2020) - Volume 1: ECTA
TI - Using Dominated Solutions to the Uniformity of Non-dominated Solution Distributions in NSGA-II
SN - 978-989-758-475-6
AU - Yokoyama K.
AU - Sato Y.
PY - 2020
SP - 212
EP - 219
DO - 10.5220/0010143502120219
PB - SciTePress