Title :
Research on parameters optimization and simulation of the Ant Colony Algorithm
Author :
Xing Wei ; Zhiyuan Li ; Jingjing Qu
Author_Institution :
Guilin Univ. of Aerosp. Technol., Guilin, China
Abstract :
Parameters optimization are studied to improve the speed of computing in the Ant Colony Algorithm, Preferences unreasonable takes a long time and search is slow. In order to improve search efficiency of the algorithm, Parameter optimization rules are proposed in the Ant Colony Algorithm, The algorithm improves the basic ant colony algorithm in the parameter selection rules of α.β.ρ. and m, by improving, the ant colony effectively avoid falling into local optimum, speed up the convergence and improve the search efficiency. Simulation results show that parameters optimization effectively improve the performance of the algorithm, the works are feasible and beneficial to the application and development of the ant colony algorithm.
Keywords :
ant colony optimisation; convergence; ant colony algorithm; convergence; parameter optimization rules; search efficiency improvement; ACA; Parameters optimization; optimization;
Conference_Titel :
Cyberspace Technology (CCT 2014), International Conference on
Print_ISBN :
978-1-84919-928-5
DOI :
10.1049/cp.2014.1364