Accession Number : ADA294071

Title :   A Study of Crossover Operators in Genetic Programming.

Corporate Author : NAVAL RESEARCH LAB WASHINGTON DC

Personal Author(s) : Spears, William M. ; Anand, Vic

PDF Url : ADA294071

Report Date : 1991

Pagination or Media Count : 10

Abstract : Holland's analysis of the sources of power of genetic algorithms has served as guidance for the applications of genetic algorithms for more than 15 years. The technique of applying a recombination operator (crossover) to a population of individuals is a key to that power. Neverless, there have been a number of contradictory results concerning crossover operators with respect to overall performance. Recently, for example, genetic algorithms were used to design neural network modules and their control circuits. In these studies, a genetic algorithm without crossover outperformed a genetic algorithm with crossover. This report re-examines these studies, and concludes that the results were caused by a small population size. New results are presented that illustrate the effectiveness of crossover when the population size is larger. From a performance view, the results indicate that better neural networks can be evolved in a shorter time if the genetic algorithm uses crossover. (AN)

Descriptors :   *NEURAL NETS, *COMPUTER PROGRAMMING, ALGORITHMS, OPTIMIZATION, COMPUTATIONS, DATA MANAGEMENT, DISTRIBUTED DATA PROCESSING, ANALYSIS OF VARIANCE, INPUT OUTPUT PROCESSING, HEURISTIC METHODS, ARTIFICIAL INTELLIGENCE, CONTROL THEORY, FIELDS(COMPUTER PROGRAMS).

Subject Categories : Computer Programming and Software
      Cybernetics

Distribution Statement : APPROVED FOR PUBLIC RELEASE