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Practice of optimization theory in g...

Yin, Zhen-Yu.

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Practice of optimization theory in geotechnical engineering

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Practice of optimization theory in geotechnical engineering/ by Zhen-Yu Yin, Yin-Fu Jin.
作者:	Yin, Zhen-Yu.
其他作者:	Jin, Yin-Fu.
出版者:	Singapore :Springer Singapore : : 2019.,
面頁冊數:	xxxvii, 356 p. :ill., digital ;24 cm.
內容註:	Introduction -- Methodology of parameter identification -- Optimisation algorithms -- Laboratory tests for mechanical behaviours of soils -- Constitutive modeling of soils -- ErosOpt platform -- Appendix A: NMS -- Appendix B: NMGA -- Appendix C: NMDE.
Contained By:	Springer eBooks
標題:	Geotechnical engineering. -
電子資源:	https://doi.org/10.1007/978-981-13-3408-5
ISBN:	9789811334085

Practice of optimization theory in geotechnical engineering
Yin, Zhen-Yu.

Practice of optimization theory in geotechnical engineering[electronic resource] /by Zhen-Yu Yin, Yin-Fu Jin. - Singapore :Springer Singapore :2019. - xxxvii, 356 p. :ill., digital ;24 cm.

Introduction -- Methodology of parameter identification -- Optimisation algorithms -- Laboratory tests for mechanical behaviours of soils -- Constitutive modeling of soils -- ErosOpt platform -- Appendix A: NMS -- Appendix B: NMGA -- Appendix C: NMDE.

This book presents the development of optimization platform for geotechnical engineering which is one of the key components in smart geotechnics. The book discusses the fundamentals of the optimization algorithm with constitutive models of soils. Helping readers easily understand the optimization algorithm applied in geotechnical engineering, this book first introduces the methodology of the optimization-based parameter identification, and then elaborates the principle of three newly developed efficient optimization algorithms, followed by the ideas of a variety of laboratory tests and formulations of constitutive models. Moving on to the application of optimization methods in geotechnical engineering, this book presents an optimization-based parameter identification platform with a practical and concise interface based on the above theories. The book is intended for undergraduate and graduate-level teaching in soil mechanics and geotechnical engineering and other related engineering specialties. It is also of use to industry practitioners, due to the inclusion of real-world applications, opening the door to advanced courses on both modeling and algorithm development within the industrial engineering and operations research fields.

ISBN: 9789811334085

Standard No.: 10.1007/978-981-13-3408-5doiSubjects--Topical Terms:

2058689
Geotechnical engineering.

LC Class. No.: TA705 / .Y569 2019

Dewey Class. No.: 624.151

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505 0 $a Introduction -- Methodology of parameter identification -- Optimisation algorithms -- Laboratory tests for mechanical behaviours of soils -- Constitutive modeling of soils -- ErosOpt platform -- Appendix A: NMS -- Appendix B: NMGA -- Appendix C: NMDE.
520 $a This book presents the development of optimization platform for geotechnical engineering which is one of the key components in smart geotechnics. The book discusses the fundamentals of the optimization algorithm with constitutive models of soils. Helping readers easily understand the optimization algorithm applied in geotechnical engineering, this book first introduces the methodology of the optimization-based parameter identification, and then elaborates the principle of three newly developed efficient optimization algorithms, followed by the ideas of a variety of laboratory tests and formulations of constitutive models. Moving on to the application of optimization methods in geotechnical engineering, this book presents an optimization-based parameter identification platform with a practical and concise interface based on the above theories. The book is intended for undergraduate and graduate-level teaching in soil mechanics and geotechnical engineering and other related engineering specialties. It is also of use to industry practitioners, due to the inclusion of real-world applications, opening the door to advanced courses on both modeling and algorithm development within the industrial engineering and operations research fields.
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