Paper Info
Title
Enhanced Archive for SHADE.
Abstract
This research paper analyses an external archive of inferior solutions used in Success-History based Adaptive Differential Evolution (SHADE) and its variant with a linear decrease in population size L-SHADE. A novel implementation of an archive is proposed and compared to the original one on CEC2015 benchmark set of test functions for two distinctive dimensionality settings. The proposed archive implementation is referred to as Enhanced Archive (EA) and therefore two Differential Evolution (DE) variants are titled EA-SHADE and EA-L-SHADE. The results on CEC2015 benchmark set are analyzed and discussed.
Year
Venue
Field
2017
MENDEL
Computer science,Differential evolution,Curse of dimensionality,Theoretical computer science,Population size,Artificial intelligence,Machine learning
DocType
Citations 
PageRank 
Conference
0
0.34
References 
Authors
10
4
Name
Order
Citations
PageRank
Adam Viktorin158.23
Roman Senkerik237574.92
Michal Pluhacek321747.34
Tomas Kadavy42020.97