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

Pengcheng Ye; Guang Pan

doi:10.1109/IRCE.2019.00026

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

Pengcheng Ye, Guang Pan

School of Marine Science and Technology

Northwestern Polytechnical University Xian

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

3 Scopus citations

Abstract

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.

Original language	English
Title of host publication	Proceedings - 2019 2nd International Conference of Intelligent Robotic and Control Engineering, IRCE 2019
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	96-100
Number of pages	5
ISBN (Electronic)	9781728141923
DOIs	https://doi.org/10.1109/IRCE.2019.00026
State	Published - Aug 2019
Event	2nd International Conference of Intelligent Robotic and Control Engineering, IRCE 2019 - Singapore, Singapore Duration: 26 Aug 2019 → 29 Aug 2019

Publication series

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

Conference

Conference	2nd International Conference of Intelligent Robotic and Control Engineering, IRCE 2019
Country/Territory	Singapore
City	Singapore
Period	26/08/19 → 29/08/19

Keywords

expensive black-box problems
future challengest
global optimization
recent advances
surrogate models

Access to Document

10.1109/IRCE.2019.00026

Cite this

Ye, P., & Pan, G. (2019). Surrogate-based Global Optimization Methods for Expensive Black-Box Problems: Recent Advances and Future Challenges. In Proceedings - 2019 2nd International Conference of Intelligent Robotic and Control Engineering, IRCE 2019 (pp. 96-100). Article 9107593 (Proceedings - 2019 2nd International Conference of Intelligent Robotic and Control Engineering, IRCE 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IRCE.2019.00026

Ye, Pengcheng ; Pan, Guang. / Surrogate-based Global Optimization Methods for Expensive Black-Box Problems : Recent Advances and Future Challenges. Proceedings - 2019 2nd International Conference of Intelligent Robotic and Control Engineering, IRCE 2019. Institute of Electrical and Electronics Engineers Inc., 2019. pp. 96-100 (Proceedings - 2019 2nd International Conference of Intelligent Robotic and Control Engineering, IRCE 2019).

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

abstract = "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.",

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author = "Pengcheng Ye and Guang Pan",

note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 2nd International Conference of Intelligent Robotic and Control Engineering, IRCE 2019 ; Conference date: 26-08-2019 Through 29-08-2019",

year = "2019",

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doi = "10.1109/IRCE.2019.00026",

language = "英语",

series = "Proceedings - 2019 2nd International Conference of Intelligent Robotic and Control Engineering, IRCE 2019",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

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Ye, P & Pan, G 2019, Surrogate-based Global Optimization Methods for Expensive Black-Box Problems: Recent Advances and Future Challenges. in Proceedings - 2019 2nd International Conference of Intelligent Robotic and Control Engineering, IRCE 2019., 9107593, Proceedings - 2019 2nd International Conference of Intelligent Robotic and Control Engineering, IRCE 2019, Institute of Electrical and Electronics Engineers Inc., pp. 96-100, 2nd International Conference of Intelligent Robotic and Control Engineering, IRCE 2019, Singapore, Singapore, 26/08/19. https://doi.org/10.1109/IRCE.2019.00026

Surrogate-based Global Optimization Methods for Expensive Black-Box Problems: Recent Advances and Future Challenges. / Ye, Pengcheng; Pan, Guang.
Proceedings - 2019 2nd International Conference of Intelligent Robotic and Control Engineering, IRCE 2019. Institute of Electrical and Electronics Engineers Inc., 2019. p. 96-100 9107593 (Proceedings - 2019 2nd International Conference of Intelligent Robotic and Control Engineering, IRCE 2019).

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

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Ye P, Pan G. Surrogate-based Global Optimization Methods for Expensive Black-Box Problems: Recent Advances and Future Challenges. In Proceedings - 2019 2nd International Conference of Intelligent Robotic and Control Engineering, IRCE 2019. Institute of Electrical and Electronics Engineers Inc. 2019. p. 96-100. 9107593. (Proceedings - 2019 2nd International Conference of Intelligent Robotic and Control Engineering, IRCE 2019). doi: 10.1109/IRCE.2019.00026

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

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