Overview
- Recent research on Group Search Optimization with Applications in Structural Design
- Latest research work related with particle swarm optimizer algorithm and group search optimizer algorithm as well as their application to structure optimal design
- Written by leading experts in the field
Part of the book series: Adaptation, Learning, and Optimization (ALO, volume 9)
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Table of contents (8 chapters)
Keywords
About this book
Civil engineering structures such as buildings, bridges, stadiums, and offshore structures play an import role in our daily life. However, constructing these structures requires lots of budget. Thus, how to cost-efficiently design structures satisfying all required design constraints is an important factor to structural engineers. Traditionally, mathematical gradient-based optimal techniques have been applied to the design of optimal structures. While, many practical engineering optimal problems are very complex and hard to solve by traditional method. In the past few decades, swarm intelligence algorithms, which were inspired by the social behaviour of natural animals such as fish schooling and bird flocking, were developed  because they do not require conventional mathematical assumptions and thus possess better global search abilities than the traditional optimization algorithms and  have attracted more and more attention. These intelligent basedalgorithms are very suitable for continuous and discrete design variable problems such as ready-made structural members and have been vigorously applied to various structural design problems and obtained good results. This book gathers the authors’ latest research work related with particle swarm optimizer algorithm and group search optimizer algorithm as well as their application to structural optimal design. The readers can understand the full spectrum of the algorithms and apply the algorithms to their own research problems.
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Authors and Affiliations
Bibliographic Information
Book Title: Group Search Optimization for Applications in Structural Design
Authors: Lijuan Li, Feng Liu
Series Title: Adaptation, Learning, and Optimization
DOI: https://doi.org/10.1007/978-3-642-20536-1
Publisher: Springer Berlin, Heidelberg
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer Berlin Heidelberg 2011
Hardcover ISBN: 978-3-642-20535-4Published: 27 May 2011
Softcover ISBN: 978-3-642-26847-2Published: 15 July 2013
eBook ISBN: 978-3-642-20536-1Published: 27 May 2011
Series ISSN: 1867-4534
Series E-ISSN: 1867-4542
Edition Number: 1
Number of Pages: X, 250
Topics: Computational Intelligence, Artificial Intelligence, Civil Engineering, Solid Mechanics