Surrogate-based Global Optimization Methods for Expensive Black-Box Problems: Recent Advances and Future Challenges

Pengcheng Ye, Guang Pan

科研成果: 书/报告/会议事项章节会议稿件同行评审

3 引用 (Scopus)

摘要

The great computational burden caused by complicated and unknown analysis restricts the use of simulation based optimization. In order to mitigate this challenge, surrogate-based global optimization methods have gained popularity for their capability in handling expensive black-box problems. This paper surveys the fundamental issues that arise in surrogate-based global optimization (SBGO) from a practitioner's perspective, including highlighting concepts, methods, techniques as well as engineering applications. To provide a brief discussion on the issues involved, recent advances in design of experiments, surrogate modeling techniques, infill criteria and design space reduction are investigated. Future challenges and research is also analyzed and discussed.

源语言英语
主期刊名Proceedings - 2019 2nd International Conference of Intelligent Robotic and Control Engineering, IRCE 2019
出版商Institute of Electrical and Electronics Engineers Inc.
96-100
页数5
ISBN(电子版)9781728141923
DOI
出版状态已出版 - 8月 2019
活动2nd International Conference of Intelligent Robotic and Control Engineering, IRCE 2019 - Singapore, 新加坡
期限: 26 8月 201929 8月 2019

出版系列

姓名Proceedings - 2019 2nd International Conference of Intelligent Robotic and Control Engineering, IRCE 2019

会议

会议2nd International Conference of Intelligent Robotic and Control Engineering, IRCE 2019
国家/地区新加坡
Singapore
时期26/08/1929/08/19

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