Title :
Genetic Ant Algorithm for Continuous Function Optimization and Its MATLAB Implementation
Author :
Li, Yan ; Chen, Yuanyi
Author_Institution :
Coll. of Mech. & Electr. Eng., Central South Univ., Changsha, China
Abstract :
Due to low accuracy of genetic algorithm and slow speed of ant algorithm for solving the problem, a hybrid algorithm based on genetic algorithm and ant algorithm is promoted and its MATLAB implementation is introduced in this paper. Using the hybrid algorithm to solve the problems of continuous function optimization, the results show that the hybrid algorithm has faster convergence and better optimization performance than genetic algorithm and ant algorithm.
Keywords :
genetic algorithms; mathematics computing; Matlab implementation; ant algorithm; continuous function optimization; genetic algorithm; Algorithm design and analysis; Cities and towns; Genetic algorithms; Genetics; MATLAB; Optimization; Probability; MATLAB; algorithm programming; continuous function; genetic ant algorithm;
Conference_Titel :
Intelligent System Design and Engineering Application (ISDEA), 2010 International Conference on
Conference_Location :
Changsha
Print_ISBN :
978-1-4244-8333-4
DOI :
10.1109/ISDEA.2010.135
