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03913nam a22005175i 4500 |
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978-3-642-20536-1 |
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110707s2011 gw | s |||| 0|eng d |
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|a 9783642205361
|9 978-3-642-20536-1
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|a 10.1007/978-3-642-20536-1
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|a Li, Lijuan.
|e author.
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|a Group Search Optimization for Applications in Structural Design
|h [electronic resource] /
|c by Lijuan Li, Feng Liu.
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|a Berlin, Heidelberg :
|b Springer Berlin Heidelberg,
|c 2011.
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|a X, 250 p.
|b online resource.
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|a text
|b txt
|2 rdacontent
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|a computer
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|a online resource
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|a text file
|b PDF
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|a Adaptation, Learning, and Optimization,
|x 1867-4534 ;
|v 9
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|a Chapter 1 Introduction of swarm intelligent algorithms -- Chapter 2 Application of particle swarm optimization algorithm to engineering structures -- Chapter 3 Optimum design of structures with heuristic particle swarm optimization algorithm .-Chapter 4 Optimum design of structures with group search optimizer algorithm .-Chapter 5 Improvements and applications of group search optimizer in structural optimal design .-Chapter 6 Optimum design of structures with quick group search optimization algorithm .-Chapter 7 Group search optimizer and its applications on multi-objective structural optimal design .-Chapter 8 Prospecting swarm intelligent algorithms.
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|a 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 based algorithms 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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|a Engineering.
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|a Artificial intelligence.
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|a Computational intelligence.
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|a Structural mechanics.
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|a Civil engineering.
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|a Engineering.
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|a Computational Intelligence.
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|a Artificial Intelligence (incl. Robotics).
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|a Civil Engineering.
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| 650 |
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|a Structural Mechanics.
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| 700 |
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|a Liu, Feng.
|e author.
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| 710 |
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|a SpringerLink (Online service)
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|t Springer eBooks
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| 776 |
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|i Printed edition:
|z 9783642205354
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| 830 |
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|a Adaptation, Learning, and Optimization,
|x 1867-4534 ;
|v 9
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| 856 |
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|u http://dx.doi.org/10.1007/978-3-642-20536-1
|z Full Text via HEAL-Link
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| 912 |
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|a ZDB-2-ENG
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| 950 |
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|a Engineering (Springer-11647)
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