Genetic Algorithms are heuristic search schemes based on a model of Darwinian evolution. Although not guaranteed to find the optimal solution, genetic algorithms have been shown t...
Walter D. Potter, Robert W. Robinson, John A. Mill...
This paper describes a method for optimizing the cost matrix of any approximate string matching algorithm based on the Levenshtein distance. The method, which uses genetic algorit...
We present a hybrid Genetic Algorithm that incorporates the Generalized Partition Crossover (GPX) operator to produce an algorithm that is competitive with the state of the art for...
Physical map reconstruction in the presence of errors is a central problem in genetics of high computational complexity. A parallel genetic algorithm for a maximum likelihood esti...
Suchendra M. Bhandarkar, Jinling Huang, Jonathan A...
Crowding is a technique used in genetic algorithms to preserve diversity in the population and to prevent premature convergence to local optima. It consists of pairing each offsp...