Optimization of boiler's convection tubes based on Genetic Algorithm
Tianyu Zhang, Qingfeng Zhang, Zhenning Zhao, Liang Cheng, Gaojun Liu
Available Online December 2016.
- https://doi.org/10.2991/iceeecs-16.2016.51How to use a DOI?
- Genetic Algorithm, convection tube, optimization, binary code.
- 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.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Tianyu Zhang AU - Qingfeng Zhang AU - Zhenning Zhao AU - Liang Cheng AU - Gaojun Liu PY - 2016/12 DA - 2016/12 TI - Optimization of boiler's convection tubes based on Genetic Algorithm BT - 2016 4th International Conference on Electrical & Electronics Engineering and Computer Science (ICEEECS 2016) PB - Atlantis Press SP - 230 EP - 235 SN - 2352-538X UR - https://doi.org/10.2991/iceeecs-16.2016.51 DO - https://doi.org/10.2991/iceeecs-16.2016.51 ID - Zhang2016/12 ER -