Nonlinear Interval Optimization for Uncertain Problems (Hardcover, 1st ed. 2021)

This book systematically discusses nonlinear interval optimization design theory and methods. Firstly, adopting a mathematical programming theory perspective, it develops an innovative mathematical transformation model to deal with general nonlinear interval uncertain optimization problems, which is able to equivalently convert complex interval uncertain optimization problems to simple deterministic optimization problems. This model is then used as the basis for various interval uncertain optimization algorithms for engineering applications, which address the low efficiency caused by double-layer nested optimization. Further, the book extends the nonlinear interval optimization theory to design problems associated with multiple optimization objectives, multiple disciplines, and parameter dependence, and establishes the corresponding interval optimization models and solution algorithms. Lastly, it uses the proposed interval uncertain optimization models and methods to deal with practical problems in mechanical engineering and related fields, demonstrating the effectiveness of the models and methods.

General

Imprint:	Springer Verlag, Singapore
Country of origin:	Singapore
Series:	Springer Tracts in Mechanical Engineering
Release date:	December 2020
First published:	2021
Authors:	Chao Jiang • Xu Han • Huichao Xie
Dimensions:	235 x 155mm (L x W)
Format:	Hardcover
Pages:	284
Edition:	1st ed. 2021
ISBN-13:	978-981-15-8545-6
Languages:	English
Subtitles:	Chinese
Categories:	Books > Science & Mathematics > Mathematics > Optimization > General Books > Science & Mathematics > Mathematics > Applied mathematics > Mathematics for scientists & engineers Books > Professional & Technical > Technology: general issues > Technical design > General Books > Professional & Technical > Transport technology > Aerospace & aviation technology > General
LSN:	981-15-8545-8
Barcode:	9789811585456

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