|Table of Contents|

[1] Zhou XiaShen Jiong, Shen JianxianLi Yiguo,. New immune multiobjective optimization algorithmand its application in boiler combustion optimization [J]. Journal of Southeast University (English Edition), 2010, 26 (4): 563-568. [doi:10.3969/j.issn.1003-7985.2010.04.013]
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New immune multiobjective optimization algorithmand its application in boiler combustion optimization()
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Journal of Southeast University (English Edition)[ISSN:1003-7985/CN:32-1325/N]

Volumn:
26
Issue:
2010 4
Page:
563-568
Research Field:
Energy and Power Engineering
Publishing date:
2010-12-30

Info

Title:
New immune multiobjective optimization algorithmand its application in boiler combustion optimization
Author(s):
Zhou XiaShen Jiong Shen JianxianLi Yiguo
School of Energy and Environment, Southeast University, Nanjing 210096, China
Keywords:
combustion optimization multiobjective optimizat-ion immune cell subsets
PACS:
TK227.1
DOI:
10.3969/j.issn.1003-7985.2010.04.013
Abstract:
In order to meet the requirements of combustion optimization for saving energy and reducing pollutant emission simultaneously, an immune cell subsets based multiobjective optimization algorithm(ICSMOA)is proposed. In the ICSMOA, the subset division operator and the immunological tolerance operation are defined. Preference can be easily addressed by using the subset division operator, and the distribution of the solutions can be guaranteed by the immunological tolerance operation. Using the ICSMOA, a group of Pareto optimal solutions can be obtained. However, by the traditional weighting method(WM), only one solution can be obtained and it cannot be judged as Pareto optimal or not. In contrast to the solutions obtained by the repeatedly performed WM, the simulation results show that most solutions obtained by the ICSMOA are better than the solutions obtained by the WM. In addition, the Pareto front obtained by the ICSMOA is not as uniform as most classical multiobjective optimization algorithms. More optimal solutions which meet the preference set by the decision-maker can be obtained and they are very useful for industrial application.

References:

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Memo

Memo:
Biographies: Zhou Xia(1976—), female, graduate; Shen Jiong(corresponding author), male, doctor, professor, shenj@seu.edu.cn.
Foundation items: The National Natural Science Foundation of China(No.51036002, 51076027), the Key Project of Ministry of Education of China(No.108060).
Citation: Zhou Xia, Shen Jiong, Shen Jianxian, et al. New immune multiobjective optimization algorithm and its application in boiler combustion optimization[J].Journal of Southeast University(English Edition), 2010, 26(4):563-568.
Last Update: 2010-12-20