Niching techniques: a study on the cluster geometry optimization problem
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Structured population genetic algorithms: a literature survey
Artificial Intelligence Review
| Hi-index | 0.02 |
Spatially structured population models improve the performance of genetic algorithms by assisting the selection scheme in maintaining diversity. A significant concern with these systems is that they need to be carefully configured in order to operate at their optimum. Failure to do so can often result in performance that is significantly under that of an equivalent non-spatial implementation. This paper introduces a GA that uses a population structure that requires no additional configuration. Early experimentation with this paradigm indicates that it is able to improve the searching abilities of the genetic algorithm on some problem domains.