Accelerating sampling-based tolerance–cost optimization by adaptive surrogate models

IF 2.2 3区 工程技术 Q2 ENGINEERING, MULTIDISCIPLINARY Engineering Optimization Pub Date : 2024-03-14 DOI:10.1080/0305215x.2024.2306142
Martin Roth, Stephan Freitag, Michael Franz, Stefan Goetz, Sandro Wartzack
{"title":"Accelerating sampling-based tolerance–cost optimization by adaptive surrogate models","authors":"Martin Roth, Stephan Freitag, Michael Franz, Stefan Goetz, Sandro Wartzack","doi":"10.1080/0305215x.2024.2306142","DOIUrl":null,"url":null,"abstract":"High numbers of function evaluations are inevitable to guarantee the reliability and optimality of sampling-based tolerance–cost optimization. Despite using different countermeasures to increase it...","PeriodicalId":50521,"journal":{"name":"Engineering Optimization","volume":"17 1","pages":""},"PeriodicalIF":2.2000,"publicationDate":"2024-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Engineering Optimization","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1080/0305215x.2024.2306142","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0

Abstract

High numbers of function evaluations are inevitable to guarantee the reliability and optimality of sampling-based tolerance–cost optimization. Despite using different countermeasures to increase it...
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
通过自适应代理模型加速基于抽样的容差成本优化
要保证基于采样的容限成本优化的可靠性和最优性,大量的函数评估是不可避免的。尽管采用了不同的对策来增加函数评估次数,但仍有许多问题需要解决。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Engineering Optimization
Engineering Optimization 管理科学-工程:综合
CiteScore
5.90
自引率
7.40%
发文量
74
审稿时长
3.5 months
期刊介绍: Engineering Optimization is an interdisciplinary engineering journal which serves the large technical community concerned with quantitative computational methods of optimization, and their application to engineering planning, design, manufacture and operational processes. The policy of the journal treats optimization as any formalized numerical process for improvement. Algorithms for numerical optimization are therefore mainstream for the journal, but equally welcome are papers which use the methods of operations research, decision support, statistical decision theory, systems theory, logical inference, knowledge-based systems, artificial intelligence, information theory and processing, and all methods which can be used in the quantitative modelling of the decision-making process. Innovation in optimization is an essential attribute of all papers but engineering applicability is equally vital. Engineering Optimization aims to cover all disciplines within the engineering community though its main focus is in the areas of environmental, civil, mechanical, aerospace and manufacturing engineering. Papers on both research aspects and practical industrial implementations are welcomed.
期刊最新文献
Hybrid machine learning and optimization method for solar irradiance forecasting An improved whale optimization algorithm for multi-robot path planning A pointwise weighting prediction variance–high-dimensional model representation model-based global optimization approach for ship hull parametric design Optimization of reliable vehicle routing problem for medical waste collection with time windows in stochastic transportation networks Contrastive loss with dynamic margin for rubber-recipe physical-property prediction
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1