Title

Efficacy Of Genetic Operators And Dna Fragment Assembly

Abstract

Genetic algorithms rapidly evolve very good solutions to problems, but often spend a large proportion of the run fine-tuning. One possible solution to this problem is to apply different operators (or the same operators at different rates) over the course of the run. This paper presents a series of experiments designed to measure the effectiveness of various genetic operators at different stages of the genetic algorithm execution. The relationship between the fitness distribution and the operator effectiveness is also explored. We discovered a transition point for both operator effectiveness and fitness distribution. Finally, we performed experiments that altered the operator rates after the genetic algorithm has completed its rapid fitness climb. These preliminary results are promising.

Publication Date

12-1-1999

Publication Title

Intelligent Engineering Systems Through Artificial Neural Networks

Volume

9

Number of Pages

387-392

Document Type

Article; Proceedings Paper

Personal Identifier

scopus

Socpus ID

0033340306 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/0033340306

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