Group Search Optimization for Applications in Structural Design [electronic resource] /
Li, Lijuan.author.
Liu, Feng.author.
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.  .
Description based upon print version of record.
Includes bibliographical references.
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.
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.  .
Computational intelligence.
Artificial intelligence.
Civil engineering.
Mechanics.
Mechanics, Applied.
Computational Intelligence.
Artificial Intelligence.
Civil Engineering.
Solid Mechanics.
Adaptation, Learning, and Optimization