A Fuzzy-based Adaptive Genetic Algorithm and Its Case Study in Chemical Engineering

杨传鑫; 颜学峰

doi:10.1016/S1004-9541(11)60169-9

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A Fuzzy-based Adaptive Genetic Algorithm and Its Case Study in Chemical Engineering

Updated：2026-01-06

- A Fuzzy-based Adaptive Genetic Algorithm and Its Case Study in Chemical Engineering
- A Fuzzy-based Adaptive Genetic Algorithm and Its Case Study in Chemical Engineering
- 中国化学工程学报（英文版） 2011年19卷第2期页码：299-307
- Affiliations：
  
  Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education, East China University of Science and Technology,Shanghai,China,200237
- Author bio：
- Funds：
  
  Supported by the National Natural Science Foundation of China(20776042);the National High Technology Research and Development Program of China(2007AA04Z164);the Doctoral Fund of Ministry of Education of China(20090074110005);the Program for New Century Excellent Talents in University(NCET-09-0346);the"Shu Guang"Project(095G29);Shanghai Leading Academic Discipline Project(B504)
- DOI：10.1016/S1004-9541(11)60169-9
  中图分类号：
- 纸质出版：2011
- Accepted：
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杨传鑫, 颜学峰. A Fuzzy-based Adaptive Genetic Algorithm and Its Case Study in Chemical Engineering[J]. 中国化学工程学报（英文版）, 2011,19(2):299-307.

YANG Chuanxin, YAN Xuefeng. A Fuzzy-based Adaptive Genetic Algorithm and Its Case Study in Chemical Engineering[J]. , 2011, 19(2): 299-307.
杨传鑫, 颜学峰. A Fuzzy-based Adaptive Genetic Algorithm and Its Case Study in Chemical Engineering[J]. 中国化学工程学报（英文版）, 2011,19(2):299-307. DOI： 10.1016/S1004-9541(11)60169-9.

YANG Chuanxin, YAN Xuefeng. A Fuzzy-based Adaptive Genetic Algorithm and Its Case Study in Chemical Engineering[J]. , 2011, 19(2): 299-307. DOI： 10.1016/S1004-9541(11)60169-9.

摘要

Abstract

Considering that the performance of a genetic algorithm (GA) is affected by many factors and their relationships are complex and hard to be described

a novel fuzzy-based adaptive genetic algorithm (FAGA) combined a new artificial immune system with fuzzy system theory is proposed due to the fact fuzzy theory can describe high complex problems.In FAGA

immune theory is used to improve the performance of selection operation.And

crossover probability and mutation probability are adjusted dynamically by fuzzy inferences

which are developed according to the heuristic fuzzy relationship between algorithm performances and control parameters.The experiments show that FAGA can efficiently overcome shortcomings of GA

i.e.

premature and slow

and obtain better results than two typical fuzzy GAs.Finally

FAGA was used for the parameters estimation of reaction kinetics model and the satisfactory result was obtained.

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