Multi-objective evolutionary algorithms' performance in a support role

Matthew J. Woodruff; Timothy W. Simpson; Patrick M. Reed

doi:10.1115/DETC201546891

Multi-objective evolutionary algorithms' performance in a support role

Matthew J. Woodruff, Timothy W. Simpson, Patrick M. Reed

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

5 Scopus citations

Abstract

This paper presents a diagnostic assessment study, evaluating five leading multi-objective evolutionary algorithms (MOEAs) on their effectiveness, efficiency, reliability, and controllability on four different formulations of the same benchmark conceptual design problem, using the same underlying model. This assessment entails a broad sampling of the parameter space of each MOEA, for each problem formulation, requiring millions of optimization runs and trillions of model evaluations. The results of this assessment show the strengths and limitations of these MOEAs, establishing the Borg MOEA as a leading algorithm.

Original language	English (US)
Title of host publication	41st Design Automation Conference
Publisher	American Society of Mechanical Engineers (ASME)
ISBN (Electronic)	9780791857083
DOIs	https://doi.org/10.1115/DETC201546891
State	Published - 2015
Event	ASME 2015 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE 2015 - Boston, United States Duration: Aug 2 2015 → Aug 5 2015

Publication series

Name	Proceedings of the ASME Design Engineering Technical Conference
Volume	2B-2015

Other

Other	ASME 2015 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE 2015
Country/Territory	United States
City	Boston
Period	8/2/15 → 8/5/15

All Science Journal Classification (ASJC) codes

Modeling and Simulation
Mechanical Engineering
Computer Science Applications
Computer Graphics and Computer-Aided Design

Access to Document

10.1115/DETC201546891

Cite this

@inproceedings{f7e385ea21744f01afe8a9bb8a5a9f03,

title = "Multi-objective evolutionary algorithms' performance in a support role",

abstract = "This paper presents a diagnostic assessment study, evaluating five leading multi-objective evolutionary algorithms (MOEAs) on their effectiveness, efficiency, reliability, and controllability on four different formulations of the same benchmark conceptual design problem, using the same underlying model. This assessment entails a broad sampling of the parameter space of each MOEA, for each problem formulation, requiring millions of optimization runs and trillions of model evaluations. The results of this assessment show the strengths and limitations of these MOEAs, establishing the Borg MOEA as a leading algorithm.",

author = "Woodruff, {Matthew J.} and Simpson, {Timothy W.} and Reed, {Patrick M.}",

note = "Publisher Copyright: Copyright {\textcopyright} 2015 by ASME.; ASME 2015 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE 2015 ; Conference date: 02-08-2015 Through 05-08-2015",

year = "2015",

doi = "10.1115/DETC201546891",

language = "English (US)",

series = "Proceedings of the ASME Design Engineering Technical Conference",

publisher = "American Society of Mechanical Engineers (ASME)",

booktitle = "41st Design Automation Conference",

}

Woodruff, MJ, Simpson, TW & Reed, PM 2015, Multi-objective evolutionary algorithms' performance in a support role. in 41st Design Automation Conference. Proceedings of the ASME Design Engineering Technical Conference, vol. 2B-2015, American Society of Mechanical Engineers (ASME), ASME 2015 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE 2015, Boston, United States, 8/2/15. https://doi.org/10.1115/DETC201546891

Multi-objective evolutionary algorithms' performance in a support role. / Woodruff, Matthew J.; Simpson, Timothy W.; Reed, Patrick M.
41st Design Automation Conference. American Society of Mechanical Engineers (ASME), 2015. (Proceedings of the ASME Design Engineering Technical Conference; Vol. 2B-2015).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Multi-objective evolutionary algorithms' performance in a support role

AU - Woodruff, Matthew J.

AU - Simpson, Timothy W.

AU - Reed, Patrick M.

PY - 2015

Y1 - 2015

N2 - This paper presents a diagnostic assessment study, evaluating five leading multi-objective evolutionary algorithms (MOEAs) on their effectiveness, efficiency, reliability, and controllability on four different formulations of the same benchmark conceptual design problem, using the same underlying model. This assessment entails a broad sampling of the parameter space of each MOEA, for each problem formulation, requiring millions of optimization runs and trillions of model evaluations. The results of this assessment show the strengths and limitations of these MOEAs, establishing the Borg MOEA as a leading algorithm.

AB - This paper presents a diagnostic assessment study, evaluating five leading multi-objective evolutionary algorithms (MOEAs) on their effectiveness, efficiency, reliability, and controllability on four different formulations of the same benchmark conceptual design problem, using the same underlying model. This assessment entails a broad sampling of the parameter space of each MOEA, for each problem formulation, requiring millions of optimization runs and trillions of model evaluations. The results of this assessment show the strengths and limitations of these MOEAs, establishing the Borg MOEA as a leading algorithm.

UR - http://www.scopus.com/inward/record.url?scp=84978976569&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84978976569&partnerID=8YFLogxK

U2 - 10.1115/DETC201546891

DO - 10.1115/DETC201546891

M3 - Conference contribution

AN - SCOPUS:84978976569

T3 - Proceedings of the ASME Design Engineering Technical Conference

BT - 41st Design Automation Conference

PB - American Society of Mechanical Engineers (ASME)

T2 - ASME 2015 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE 2015

Y2 - 2 August 2015 through 5 August 2015

ER -

Multi-objective evolutionary algorithms' performance in a support role

Abstract

Publication series

Other

All Science Journal Classification (ASJC) codes

Access to Document

Other files and links

Fingerprint

Cite this