Title :
Adaptive ACO for Complicated Optimization Problems
Author :
Yancang, Li ; Shujing, Zhou
Author_Institution :
Coll. of Civil Eng., Hebei Univ. of Eng., Handan, China
Abstract :
To overcome the premature convergence deficiency of the basic Ant Colony Algorithm and find a method to deal with the continuous-space problem for ant algorithms, an improved Ant Colony Algorithm based on the information entropy was proposed. The main idea is to control the path selection and evolutional strategy by self-adjusting. Simulation study results in solving the NP-hard problems and continuous-space problem demonstrate its efficiency and robustness in solving the complicated combinatorial optimization problems.
Keywords :
optimisation; NP-hard problems; adaptive ACO; ant colony algorithm; complicated optimization problems; continuous-space problem; evolutional strategy; information entropy; path selection; Ant colony optimization; Civil engineering; Educational institutions; Feedback; Information entropy; Information technology; Job shop scheduling; Mathematics; Stochastic processes; Uncertainty; Ant Colony Algorithm; combinatorial optimization; continuous-space problem; transition strategy;
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.2009.351
