Title :
Problems in GA and necessities of importing immune function
Author :
Shenglian, Han ; Meng, Ni ; Wancheng, Ge
Author_Institution :
Tongji Univ., Shanghai, China
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;
Conference_Titel :
Intelligent Control and Automation, 2000. Proceedings of the 3rd World Congress on
Conference_Location :
Hefei
Print_ISBN :
0-7803-5995-X
DOI :
10.1109/WCICA.2000.860027
