Title :
The Extension-Based Ant Colony Optimization of Finding Rough Set Reducts
Author :
Sujuan, Zhao ; Tao, Zeng ; Yu Yongquan
Author_Institution :
Fac. of Comput., Guangdong Univ. of Technol., Guangzhou, China
Abstract :
Ant colony algorithm is a simulated evolutionary algorithm, which shows many excellent characters and has succeeded in solving many difficult combinatorial optimization problems. However, it is not perfect now. Inspired by dependent function of extension theory, a new statue transition rule and local updating rule based on dependent function have been presented in this paper. And experimental results show that our algorithm is effective and useful.
Keywords :
combinatorial mathematics; evolutionary computation; rough set theory; combinatorial optimization problem; extension theory dependent function; extension-based ant colony optimization; local updating rule; rough set reduct; simulated evolutionary algorithm; statue transition rule; Ant colony optimization; Application software; Computational modeling; Computer simulation; Evolutionary computation; Information technology; Ant colony algorithm; Dependent Function; local updating rule; rough set attributes reductions; statue transition rule;
Conference_Titel :
Information Technology and Applications, 2009. IFITA '09. International Forum on
Conference_Location :
Chengdu
Print_ISBN :
978-0-7695-3600-2
DOI :
10.1109/IFITA.2009.336
