DocumentCode
352736
Title
Problems in GA and necessities of importing immune function
Author
Shenglian, Han ; Meng, Ni ; Wancheng, Ge
Author_Institution
Tongji Univ., Shanghai, China
Volume
1
fYear
2000
fDate
2000
Firstpage
542
Abstract
Genetic algorithm (GA), as an effective method of functional optimization and combinatorial optimization for planning and scheduling problems, is showing its wider application prospects. However, the average GAs are confronted with a few inevitable issues. These issues not only seriously influence the efficiency of GA operations, but also seriously limit the application range of GAs. This article put forward a kind of GA with immune function, and its efficiency is showed by an example
Keywords
genetic algorithms; code crossover mutation; efficiency; genetic algorithm; immune function; infeasible genes; optimization; Electrostatic precipitators; Genetics; Optimization methods; Scheduling algorithm;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Control and Automation, 2000. Proceedings of the 3rd World Congress on
Conference_Location
Hefei
Print_ISBN
0-7803-5995-X
Type
conf
DOI
10.1109/WCICA.2000.860027
Filename
860027
Link To Document