DocumentCode :
1600696
Title :
A Novel Immunity-Growth Genetic Algorithm for Traveling Salesman Problem
Author :
Zeng, Cong-wen ; Gu, Tian-long
Author_Institution :
Guilin Univ. of Electron. Technol., Guilin
Volume :
5
fYear :
2007
Firstpage :
394
Lastpage :
398
Abstract :
A novel genetic algorithm based on immunity and growth for the traveling salesman problem is presented in the paper. To start with, a reversal exchange crossover and mutation operator is proposed to preserve the good sub tours and to make individuals various. Next, a new immune operator is proposed to restrain individuals´ degeneracy. In addition, a novel growth operator is proposed to obtain the optimal solution with more chances. Finally, we test the convergent rate of the algorithm and the best solution obtained by the algorithm after some generators. Experimental results show that the algorithm is feasible and effective.
Keywords :
genetic algorithms; mathematical operators; travelling salesman problems; growth operator; immune operator; immunity-growth genetic algorithm; mutation operator; reversal exchange crossover operator; traveling salesman problem; Blindness; Computer science; Concurrent computing; Equations; Genetic algorithms; Genetic mutations; Testing; Traveling salesman problems; Vaccines;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Natural Computation, 2007. ICNC 2007. Third International Conference on
Conference_Location :
Haikou
Print_ISBN :
978-0-7695-2875-5
Type :
conf
DOI :
10.1109/ICNC.2007.114
Filename :
4344872
Link To Document :
بازگشت