MULTI-OBJECTIVE EVOLUTIONARY ALGORITHMS' PERFORMANCE IN A SUPPORT ROLE

被引：0

作者：

Woodruff, Matthew J. ^{[1
]}

Simpson, Timothy W. ^{[1
]}

Reed, Patrick M. ^{[2
]}

机构：

[1] Penn State Univ, Dept Ind & Mfg Engn, University Pk, PA 16802 USA

[2] Cornell Univ, Sch Civil & Environm Engn, Ithaca, NY 14853 USA

来源：

INTERNATIONAL DESIGN ENGINEERING TECHNICAL CONFERENCES AND COMPUTERS AND INFORMATION IN ENGINEERING CONFERENCE, 2015, VOL 2B | 2016年

关键词：

OPTIMIZATION; SEARCH; DESIGN;

D O I：

暂无

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

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.

引用

页数：12

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