Wind-resistant optimal design of tall buildings based on improved genetic algorithm

Structures ◽  
2020 ◽  
Vol 27 ◽  
pp. 2182-2191
Author(s):  
Yi Li ◽  
Ru-Biao Duan ◽  
Qiu-Sheng Li ◽  
Yong-Gui Li ◽  
Xuan Huang
Keyword(s):  
Genetic Algorithm ◽  
Optimal Design ◽  
Tall Buildings ◽  
Improved Genetic Algorithm

A Novel Improved Genetic Algorithm and Application in Mechanical Optimal Design

2009 ◽  
Vol 628-629 ◽  
pp. 263-268 ◽  
Author(s):  
Zhong Min Wang ◽  
Yu Jun Cai ◽  
D.H. Miao
Keyword(s):  
Neural Network ◽  
Genetic Algorithm ◽  
Optimal Design ◽  
Hybrid Genetic Algorithm ◽  
Pso Algorithm ◽  
Improved Genetic Algorithm ◽  
Neural Network Method ◽  
Random Direction ◽  
Network Method ◽  
Species Population

A new improved genetic algorithm (IGA) based on floating point encoding is proposed. Firstly, IGA uses information entropy to produce better initialized species population. Secondly, after synthetically studying the searching properties of crossover operator in GA, it designs a new crossover strategy that effectively increases searching efficiencies of IGA. Thirdly, to avoid searching being trapped in local minimum, it designs a chaos degenerate mutation operator that makes the searching fast converge to a global minimum. At last IGA is used to solve the problem of the optimal design to crane girder, which is a typical problem of mechanical optimal design. Compared with the traditional random direction method, neural network method, genetic-neural network method, hybrid genetic algorithm, chaos-GA, PSO algorithm, chaos-PSO algorithm and standard GA, IGA shows better performance at the aspect of solution precision and convergence speed than that of these algorithms.

Investigation of Roll Pass Optimal Design Based on IGA

2011 ◽  
Vol 211-212 ◽  
pp. 195-199 ◽  
Author(s):  
Bin Huang ◽  
Ke Xing ◽  
Kazem Abhary ◽  
Sead Spuzic
Keyword(s):  
Genetic Algorithm ◽  
Optimal Design ◽  
Roll Pass Design ◽  
Improved Genetic Algorithm ◽  
Pass Design ◽  
Roll Pass ◽  
Empirical Formulas ◽  
Design And Optimization ◽  
Rolling System ◽  
Rod Rolling

The primary purpose of this study is to develop a genetic algorithm based computer-aided roll pass optimal design (CAROD) system to support the generalized roll pass design for rod rolling, where the final products are round bars with different sizes. The system was developed to minimize the number of roll passes, decrease the trails and errors in industry, as well as extend the work range of multi-pass rolling systems for rod rolling. Parametric equations were established for geometrical modeling and graphic plotting, which can realize to the parametric transformation for roll pass design and optimization. A methodology based on a hybrid model was proposed to choose passes with different profiles for the multi-pass rod rolling system. In addition, an improved genetic algorithm (IGA) was employed for the optimization of roll passes. A MATLAB program was designed to achieve all these objectives. To reduce the complexity and computational burden of the software, some reliable empirical formulas were applied in this system. Finally, the proposed approach has been applied in a rod rolling system; through simulation and comparison of results against analytical solutions, numerical analysis and experimental data presented by other researchers, it was found that this system is reliable, effective and easier to use.

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