遺傳演算法AllOnesGA

標籤：problems   confirm   str   end   div   out   loop   package   cas   

package chapter2;/** * This is our main class used to run the genetic algorithm. *  * This case is one of the simplest problems we can solve: the objective is to * end up with an individual whose chromosome is all ones. *  * The simplicity of this problem makes the GeneticAlgorithm class‘ * "calcFitness" method very simple. We‘ll just count the number of ones in the * chromosome and use that as the fitness score. Similarly, the * "isTerminationConditionMet" method in the GeneticAlgorithm class for this * example is very simple: if the fitness score (ie, number of ones) is the same * as the length of the chromosome (ie, we‘re all ones), we‘re done! *  * @author bkanber * */public class AllOnesGA {    public static void main(String[] args) {        // Create GA object        GeneticAlgorithm ga = new GeneticAlgorithm(100, 0.001, 0.95, 2);        // Initialize population        Population population = ga.initPopulation(50);        // Evaluate population        ga.evalPopulation(population);        // Keep track of current generation        int generation = 1;        /**         * Start the evolution loop         *          * Every genetic algorithm problem has different criteria for finishing.         * In this case, we know what a perfect solution looks like (we don‘t         * always!), so our isTerminationConditionMet method is very         * straightforward: if there‘s a member of the population whose         * chromosome is all ones, we‘re done!         */        while (ga.isTerminationConditionMet(population) == false) {            // Print fittest individual from population            System.out.println("Best solution: " + population.getFittest(0).toString());            // Apply crossover            population = ga.crossoverPopulation(population);            // Apply mutation            population = ga.mutatePopulation(population);            // Evaluate population            ga.evalPopulation(population);            // Increment the current generation            generation++;        }        /**         * We‘re out of the loop now, which means we have a perfect solution on         * our hands. Let‘s print it out to confirm that it is actually all         * ones, as promised.         */        System.out.println("Found solution in " + generation + " generations");        System.out.println("Best solution: " + population.getFittest(0).toString());    }}

 

遺傳演算法AllOnesGA