1. A Developed Artificial Bee Colony Algorithm Based on Cloud Model
- Author
-
Yuehong Sun, Hongjiao Ma, and Ye Jin
- Subjects
0209 industrial biotechnology ,Computer science ,General Mathematics ,Computer Science::Neural and Evolutionary Computation ,Cloud computing ,02 engineering and technology ,020901 industrial engineering & automation ,Local optimum ,Probability theory ,Convergence (routing) ,0202 electrical engineering, electronic engineering, information engineering ,Computer Science (miscellaneous) ,Quantitative expression ,Y conditional cloud generator ,Engineering (miscellaneous) ,artificial bee colony algorithm (ABC) ,cloud model ,normal cloud model ,global optimum ,business.industry ,lcsh:Mathematics ,lcsh:QA1-939 ,Statistics::Computation ,Artificial bee colony algorithm ,Global optimum ,Fuzzy mathematics ,020201 artificial intelligence & image processing ,Artificial intelligence ,business - Abstract
The Artificial Bee Colony (ABC) algorithm is a bionic intelligent optimization method. The cloud model is a kind of uncertainty conversion model between a qualitative concept T ˜ that is presented by nature language and its quantitative expression, which integrates probability theory and the fuzzy mathematics. A developed ABC algorithm based on cloud model is proposed to enhance accuracy of the basic ABC algorithm and avoid getting trapped into local optima by introducing a new select mechanism, replacing the onlooker bees’ search formula and changing the scout bees’ updating formula. Experiments on CEC15 show that the new algorithm has a faster convergence speed and higher accuracy than the basic ABC and some cloud model based ABC variants.
- Published
- 2018