Search results

Genetic algorithms are a class of non‐deterministic algorithms that derive from Darwinian evolution and that provide good, though not necessarily optimal, solutions to combinatorial problems. We describe their application to the identification of characteristics that occur approximately equifrequently in a database, using two different methods for the creation of the chromosome data structures that lie at the heart of a genetic algorithm. Experiments with files of English and Turkish text suggest that the genetic algorithm developed here can produce results superior to those produced by existing non‐deterministic algorithms; however, the results are inferior to those produced by an existing deterministic algorithm.