Title :
Solving the Travelling Salesman Problem by the Program of Ant Colony Algorithm
Author :
Zhu Ju-fang ; Li Qing-yuan
Author_Institution :
Chinese Acad. of Surveying & Mapping, Chinese Univ. of Min. & Technol., Beijing, China
Abstract :
Ant colony algorithm is a novel simulated ecosystem evolutionary algorithm, which is applied to solving complex combinatorial optimization problems. The basic principle and realization about ant colony algorithm are studied in this paper. The algorithm is realized under the Visual C++ compiler environment, and applied to solving the travelling salesman problem (TSP). The result is accordance with the best route solution. This algorithm has practical worth.
Keywords :
evolutionary computation; program compilers; travelling salesman problems; Visual C++ compiler; ant colony algorithm; complex combinatorial optimization problems; simulated ecosystem evolutionary algorithm; travelling salesman problem; Ant colony optimization; Cities and towns; Ecosystems; Evolutionary computation; Genetic algorithms; Heuristic algorithms; Mathematical model; Neural networks; Robustness; Traveling salesman problems;
Conference_Titel :
Computational Intelligence and Software Engineering, 2009. CiSE 2009. International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-4507-3
Electronic_ISBN :
978-1-4244-4507-3
DOI :
10.1109/CISE.2009.5366235
