DocumentCode :
1752853
Title :
A New Algorithm for TSP Based on Swarm Intelligence
Author :
He, Xiaoxian ; Zhu, Yunlong ; Hu, Hechun ; Ben Niu
Author_Institution :
Shenyang Inst. of Autom., Chinese Acad. of Sci., Shenyang
Volume :
1
fYear :
0
fDate :
0-0 0
Firstpage :
3241
Lastpage :
3244
Abstract :
Inspired by the behavior of people, a new algorithm for the combinatorial optimization is proposed. This is a heuristic approach based on swarm intelligence, which is firstly introduced as the theoretical background in this paper. It is also a parallel algorithm, in which individuals of the swarm search the state space independently and simultaneously. When one encounters another in the process, they would communicate with each other, and utilize the more valuable experiences to improve their own fitness. A positive feedback mechanism is designed to avoid vibrations. Ten benchmarks of the TSPLIB are tested in the experiments. The results indicate that the algorithm can quickly converge to the optimal solution with quite low cost. Some conclusions about the algorithm are summarized finally
Keywords :
feedback; heuristic programming; parallel algorithms; search problems; travelling salesman problems; combinatorial optimization; parallel algorithm; positive feedback mechanism; route-exchange algorithm; swarm intelligence; swarm search; traveling salesman problem; Automation; Benchmark testing; Cities and towns; Educational institutions; Feedback; Helium; Humans; Insects; Particle swarm optimization; Traveling salesman problems; Combinatorial optimization; Positive feedback; Route-exchange algorithm; Swarm intelligence; TSP;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on
Conference_Location :
Dalian
Print_ISBN :
1-4244-0332-4
Type :
conf
DOI :
10.1109/WCICA.2006.1712966
Filename :
1712966
Link To Document :
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