Kriging metamodel management in the design optimization of a CNG injection system

被引：45

作者：

Dellino, G. ^{[1
]}

Lino, P. ^{[2
]}

Meloni, C. ^{[2
]}

Rizzo, A. ^{[2
]}

机构：

[1] Univ Siena, Dipartimento Ingn Informaz, I-53100 Siena, Italy

[2] Dipartimento Elettrotecn & Elettron, I-70125 Bari, Italy

来源：

MATHEMATICS AND COMPUTERS IN SIMULATION | 2009年 / 79卷 / 08期

关键词：

Optimization; Evolutionary algorithms; Kriging metamodels; Design of Experiments; Metamodel management; EVOLUTIONARY ALGORITHMS; APPROXIMATION; MODELS;

D O I：

10.1016/j.matcom.2009.01.013

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

This paper deals with the use of Kriging metamodels in multi-objective engineering design optimization. The metamodel management issue to find the tradeoff between accuracy and efficiency is addressed. A comparative analysis of different strategies is conducted for a case study devoted to the design of a component of the injection system for Compressed Natural Gas (CNG) engines. The computational results are reported and analyzed for a performance assessment conducted with a data envelopment analysis approach. (C) 2009 IMACS. Published by Elsevier B.V. All rights reserved.

引用

页码：2345 / 2360

页数：16

共 24 条

[1]

[Anonymous], 2003, QUAL ENG

[2] Accelerating evolutionary algorithms with Gaussian process fitness function models [J].