Title :
New continuous Ant Colony Algorithm
Author_Institution :
Wuhan Polytech. Univ., Wuhan
Abstract :
Ant Colony Algorithm is a very good combination optimization method from mimic the swarm intelligence of ant colony behaviours. To extend the traditional Ant Colony Algorithm to continuous optimization problems, from the connections of continuous optimization and searching process of Ant Colony Algorithm, here one new Continuous Ant Colony Algorithm is proposed. To verify the new algorithm, the typical functions, such as Schaffer function and Percy function, are all used. And then, the results of new Continuous Ant Colony Algorithm are compared with that of traditional Continuous Ant Colony Algorithm and immunized evolutionary programming proposed by author. The results show that, the convergent speed and computing precision of the new algorithm are all very good.
Keywords :
evolutionary computation; optimisation; search problems; ant colony behaviours; continuous ant colony algorithm; continuous optimization problems; immunized evolutionary programming; optimization method; searching process; swarm intelligence; Ant colony optimization; Automation; Genetic programming; Intelligent control; Optimization methods; Particle swarm optimization; Ant Colony Algorithm; Continuous Ant Colony Algorithm; combination optimization; continuous optimization;
Conference_Titel :
Intelligent Control and Automation, 2008. WCICA 2008. 7th World Congress on
Conference_Location :
Chongqing
Print_ISBN :
978-1-4244-2113-8
Electronic_ISBN :
978-1-4244-2114-5
DOI :
10.1109/WCICA.2008.4594448