Paper Info
Title
Evolutionary Process: Parallelism Analysis of Differential Evolution Algorithm Based on Graph Theory.
Abstract
Computation intelligence is becoming an essential technology during the development of human society. There are many family members in computation intelligence. Many researchers have already studied the mathematical inherent rules of these biology-inspired algorithms to found methods to improve the capacity of the algorithms. In the family of computation intelligence, differential evolution (DE) algorithm shows performance optimization ability. In order to explore the reason why DE could have stable and robust quality. We analyzed the parallelism of the evolutionary process in the iterative process of DE algorithm based on graph theory. By the knowledge of graph theory, it will directly exhibit the essential reason of differential evolution in the algorithm. The research will reveal that the superior DE algorithm have more extent parallelism ability than the elementary algorithm.
Year
Venue
Field
2016
BIC-TA
Graph theory,Population,Iterative and incremental development,Computer science,Theoretical computer science,Differential evolution,Evolution strategy,Artificial intelligence,Evolutionary programming,Machine learning,Computation,Evolutionary graph theory
DocType
Citations 
PageRank 
Conference
0
0.34
References 
Authors
0
5
Name
Order
Citations
PageRank
Xiaoqi Peng100.34
Zhifeng Hao265378.36
han huang3174.73
Hongyue Wu421.39
Fangqing Liu5114.50