海鸥优化算法用java怎么实现
时间: 2024-04-30 07:20:05 浏览: 13
海鸥优化算法(Seagull Optimization Algorithm)是一种群体智能算法,其实现可以使用Java语言。以下是一个简单的Java实现示例:
```java
import java.util.Random;
public class SeagullOptimizationAlgorithm {
// 种群大小
private static final int POPULATION_SIZE = 50;
// 迭代次数
private static final int MAX_ITERATIONS = 100;
// 最小值
private static final double MIN_VALUE = -10;
// 最大值
private static final double MAX_VALUE = 10;
public static void main(String[] args) {
// 初始化种群
double[][] population = new double[POPULATION_SIZE][2];
Random rand = new Random();
for (int i = 0; i < POPULATION_SIZE; i++) {
population[i][0] = MIN_VALUE + (MAX_VALUE - MIN_VALUE) * rand.nextDouble();
population[i][1] = MIN_VALUE + (MAX_VALUE - MIN_VALUE) * rand.nextDouble();
}
// 迭代
int iteration = 1;
while (iteration <= MAX_ITERATIONS) {
// 计算每个个体的适应度值
double[] fitness = new double[POPULATION_SIZE];
for (int i = 0; i < POPULATION_SIZE; i++) {
fitness[i] = calculateFitness(population[i]);
}
// 找到适应度最优的个体
int bestIndex = findBestIndex(fitness);
// 更新种群
for (int i = 0; i < POPULATION_SIZE; i++) {
if (i != bestIndex) {
for (int j = 0; j < 2; j++) {
population[i][j] = population[i][j] + rand.nextDouble() * (population[bestIndex][j] - population[i][j]);
}
}
}
iteration++;
}
// 打印最优解
double[] bestSolution = population[findBestIndex(calculateFitness(population))];
System.out.println("Best solution: (" + bestSolution[0] + ", " + bestSolution[1] + ")");
}
// 计算适应度值
private static double calculateFitness(double[] x) {
double fitness = x[0] * x[0] + x[1] * x[1];
return 1 / fitness;
}
// 找到适应度最优的个体的索引
private static int findBestIndex(double[] fitness) {
int bestIndex = 0;
for (int i = 1; i < POPULATION_SIZE; i++) {
if (fitness[i] > fitness[bestIndex]) {
bestIndex = i;
}
}
return bestIndex;
}
}
```
在这个示例中,首先初始化了一个大小为50的种群,每个个体包含两个参数。然后进行迭代,计算每个个体的适应度值,找到适应度最优的个体,使用该个体更新其他个体的参数。最后输出最优解。这是一个简单的实现,你可以根据自己的需求进行修改和优化。
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