Group Search Optimization for Applications in Structural Design
Book information
Description
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.
Similar books
The Road To General Intelligence
2022 · PDF
EVOLVE - A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation IV: International Conference held at Leiden University, July 10-13, 2013
2013 · PDF
Semantic Hyper/Multimedia Adaptation: Schemes and Applications
2013 · PDF
Advanced Query Processing: Volume 1: Issues and Trends
2013 · PDF
Data Intensive Computing for Biodiversity
2013 · PDF
ICT Innovations 2012: Secure and Intelligent Systems
2013 · PDF
Handbook on Neural Information Processing
2013 · PDF
Advances in Fuzzy Implication Functions
2013 · PDF