Genetic Clustering with Constraints
Saeed Parsa, Omid Bushehrian · 2008
The aim is to facilitate the application of user defined constraints to the genetic clustering algorithm. This is achieved by presenting a general penalty function. The penalty function is defined as a normal distribution. The function is augmented to an extensible environment to assemble genetic clustering algorithms, called DAGC. The main idea behind the design of DAGC is to provide the researches with an environment to develop and investigate genetic clustering algorithms by selecting the building blocks from an extensible library. It also provides the user with some templates to build their own building blocks. This new version of DAGC is equipped with some interfaces to define new constraints or to apply existing ones.