Title :
The Improved Ant Colony Algorithm Based on Immunity System Genetic Algorithm and Application
Author :
Zhang, Caiqing ; Lu, Yanchao
Author_Institution :
Dept. of Economic Manage., North China Electr. Power Univ., Baoding
Abstract :
In this paper, aims at the weakness of ant colony algorithm that leads to converge rashly to the non-overall superior solution and its calculating time is long, when deals with resolving large optimization problem, a improved ant colony algorithm is presented. The algorithm combines the overall hunting ability with expansibility of the genetic algorithm and the character of immunity system in guiding partial hunting for particular problem. It is applied to the process of searching for the optimization in TSP, compares with the result of GA and ACA, the result of the new algorithm closes to superior solution much more, the validity of the algorithm is verified
Keywords :
genetic algorithms; search problems; travelling salesman problems; ant colony algorithm; genetic algorithm; immunity system; optimization problem; traveling salesman problem; Algorithm design and analysis; Ant colony optimization; Encoding; Energy management; Extraterrestrial phenomena; Feedback; Genetic algorithms; Power generation economics; Power system economics; Topology; Ant Colony Algorithm (ACA); Genetic Algorithm (GA); Immunity System (IS); TSP;
Conference_Titel :
Cognitive Informatics, 2006. ICCI 2006. 5th IEEE International Conference on
Conference_Location :
Beijing
Print_ISBN :
1-4244-0475-4
DOI :
10.1109/COGINF.2006.365579
