DocumentCode :
3176444
Title :
A multiple ant colonies optimization algorithm based on immunity for solving TSP
Author :
Xue, Hongquan ; Hang, Peng Z. ; Ang, Lm Y.
Author_Institution :
Sch. of Econ. & Manage., Xi´´an Univ. of Technol., Xi´´an, China
fYear :
2010
fDate :
29-30 Oct. 2010
Firstpage :
289
Lastpage :
293
Abstract :
The traveling salesman problem (TSP) is a wellknown NP-hard problem and extensively studied problems in combinatorial optimization. Ant colony optimization algorithm (ACOA) has been used to solve many optimization problems in various fields of engineering. In this paper, a new algorithm was presented for solving TSP using ACOA based on immunity and multiple ant colonies. The new algorithm was tested on benchmark problems from TSPLIB and the test results were presented. The experimental results show that the new algorithm effectively relieves the tensions such as the premature, the convergence and the stagnation.
Keywords :
computational complexity; travelling salesman problems; NP-hard problem; ant colonies optimization algorithm; ant colony optimization algorithm; combinatorial optimization; traveling salesman problem; Propulsion; Ant Colony Optimization; Immune Algorithm; Immune Multiple Ant Colonies Algorithm; Multiple Ant Colonies; Traveling Salesman Problem;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Artificial Intelligence and Education (ICAIE), 2010 International Conference on
Conference_Location :
Hangzhou
Print_ISBN :
978-1-4244-6935-2
Type :
conf
DOI :
10.1109/ICAIE.2010.5641516
Filename :
5641516
Link To Document :
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