Optimization of boiler's convection tubes based on Genetic Algorithm

被引：0

作者：

Zhang, Tianyu ^{[1
]}

Zhang, Qingfeng ^{[1
]}

Zhao, Zhenning ^{[1
]}

Cheng, Liang ^{[1
]}

Liu, Gaojun ^{[1
]}

机构：

[1] North China Elect Power Res Inst, Beijing 100032, Peoples R China

来源：

PROCEEDINGS OF THE 2016 4TH INTERNATIONAL CONFERENCE ON ELECTRICAL & ELECTRONICS ENGINEERING AND COMPUTER SCIENCE (ICEEECS 2016) | 2016年 / 50卷

关键词：

Genetic Algorithm; convection tube; optimization; binary code; HEAT-EXCHANGERS; OPTIMAL-DESIGN;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Genetic Algorithm (GA) is created by Prof. John Holland from Michigan University, deriving from the Darwin's theory of evolution, Weizmann's theory of species selection, and Mendel's theory of inheritance. In present study, the Genetic Algorithm is introduced to optimize the boiler convection tube bank of SHL32-2.5/AI and the method of programing group for optimization binary code, is achieved. Constraints are considered by means of penalty functions. Based on the data obtained in our case, the result shows in the almost equal amount of heat absorbed, the structure with optimization can economize on steel by 10%. The idea of present study can also applied in economizer and other heat transfer array of tubes and can be used as a reference for further study.

引用

页码：230 / 235

页数：6

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