eprintid: 10129908
rev_number: 17
eprint_status: archive
userid: 608
dir: disk0/10/12/99/08
datestamp: 2021-06-22 11:06:06
lastmod: 2021-10-19 22:12:16
status_changed: 2021-06-22 11:06:06
type: proceedings_section
metadata_visibility: show
creators_name: Hort, M
creators_name: Sarro, F
title: The Effect of Offspring Population Size on NSGA-II: A Preliminary Study
ispublished: inpress
divisions: UCL
divisions: B04
divisions: C05
divisions: F48
keywords: Genetic algorithms, multi-objective optimization, NSGA-II, offspring population
note: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
abstract: Non-Dominated Sorting Genetic Algorithm (NSGA-II) is one of the
most popular Multi-Objective Evolutionary Algorithms (MOEA)
and has been applied to a large range of problems.
Previous studies have shown that parameter tuning can improve
NSGA-II performance. However, the tuning of the offspring population size, which guides the exploration-exploitation trade-off in
NSGA-II, has been overlooked so far. Previous work has generally
used the population size as the default offspring population size for
NSGA-II.
We therefore investigate the impact of offspring population size
on the performance of NSGA-II. We carry out an empirical study by
comparing the effectiveness of three configurations vs. the default
NSGA-II configuration on six optimization problems based on four
Pareto front quality indicators and statistical tests.
Our findings show that the performance of NSGA-II can be improved by reducing the offspring population size and in turn increasing the number of generations. This leads to similar or statistically
significant better results than those obtained by using the default
NSGA-II configuration in 92% of the experiments performed.
date: 2021-07-14
date_type: published
publisher: Association for Computing Machinery (ACM)
official_url: https://gecco-2021.sigevo.org/HomePage
oa_status: green
full_text_type: other
language: eng
primo: open
primo_central: open_green
verified: verified_manual
elements_id: 1871805
lyricists_name: Hort, Max
lyricists_name: Sarro, Federica
lyricists_id: MBHOR72
lyricists_id: FSSAR72
actors_name: Hort, Max
actors_id: MBHOR72
actors_role: owner
full_text_status: public
series: Genetic and Evolutionary Computation Conference (GECCO)
volume: 2021
place_of_pub: New York, NY, USA
event_title: 2021 Genetic and Evolutionary Computation Conference (GECCO 2021)
institution: Genetic and Evolutionary Computation Conference
book_title: Proceedings of the 2021 Genetic and Evolutionary Computation Conference (GECCO 2021)
citation:        Hort, M;    Sarro, F;      (2021)    The Effect of Offspring Population Size on NSGA-II: A Preliminary Study.                     In:  Proceedings of the 2021 Genetic and Evolutionary Computation Conference (GECCO 2021).    Association for Computing Machinery (ACM): New York, NY, USA.    (In press).    Green open access   
 
document_url: https://discovery.ucl.ac.uk/id/eprint/10129908/1/NSGA-II_Offspring.pdf