Paper Info
Title
On Measures of Search Features
Abstract
This paper describes several measures that can be useful when analyzing features of search in genetic algorithms. Results obtained by different researchers are often hard to compare and it is often difficult to draw general conclusions from them. This means that non-experienced users of genetic algorithms have little help in constructing their own effective solutions for a particular problem. The article contains a suggestion about possible ways of investigating features of search in genetic algorithms. These features are defined together with descriptions how to measure them.
Year
DOI
Venue
1999
10.1007/BFb0095155
ISMIS
Keywords
Field
DocType
search features,genetic algorithm
Computer science,Meta-optimization,Genetic representation,Artificial intelligence,Population-based incremental learning,Machine learning
Conference
ISBN
Citations 
PageRank 
3-540-65965-X
0
0.34
References 
Authors
14
1
Name
Order
Citations
PageRank
Roger Johnson100.34