Title :
The immune evolutionary algorithm
Author :
Lei, Wang ; Licheng, Jiao
Author_Institution :
Key Lab. for Radar Signal Process., Xidian Univ., Xi´´an, China
Abstract :
A novel algorithm, the immune evolutionary algorithm (IEA), is proposed based on immune theory in biology, which constructs an immune operator accomplished by two steps: a vaccination and an immune selection. IEA is shown to converge to the global optimum with probability 1. Strategies of selecting vaccines and methods of constructing an immune operator are also given, with an example of TSP. A simulation test on the 75-city TSP shows that IEA can not only restrain the degenerate phenomenon during the evolutionary process, but can also improve the searching ability and the adaptability greatly, therefore increasing the convergent speed
Keywords :
evolutionary computation; probability; search problems; travelling salesman problems; IEA; TSP; adaptability; biology; convergent speed; degenerate phenomenon; evolutionary process; global optimum; immune evolutionary algorithm; immune operator; immune selection; immune theory; probability; searching ability; simulation test; travelling salesman problem; vaccination; Biology computing; Convergence; Design optimization; Evolution (biology); Evolutionary computation; Genetic algorithms; Immune system; Radar signal processing; Signal processing algorithms; Vaccines;
Conference_Titel :
Knowledge-Based Intelligent Information Engineering Systems, 1999. Third International Conference
Conference_Location :
Adelaide, SA
Print_ISBN :
0-7803-5578-4
DOI :
10.1109/KES.1999.820129
