修復陣列越界異常新陣列異常

Question

當我嘗試運行我的代碼時，它告訴我在Caluclate Fitness中有多個數組超出範圍異常，並且選擇了任何想法來幫助我感謝。它說錯誤在第67行，我相信我的主類（遺傳算法）中的一個錯誤和37個錯誤。個人類似乎很好我希望問題在於我如何定義我的功能，但我不知道要解決這個錯誤。我已經出演了它是選擇數組的錯誤。在選擇線路，它說數組越界50我猜意味着它認爲在數組中的我沒有聲明，但我已經宣佈它

package genetic.algorithm; 

import static genetic.algorithm.GeneticAlgorithm.Selection; 
import static genetic.algorithm.GeneticAlgorithm.n_population; 
import static genetic.algorithm.Individual.N; 
import static genetic.algorithm.Individual.fitness; 
import static genetic.algorithm.Individual.gene; 
import java.util.Random; 

public class GeneticAlgorithm { 

    static int P = 50; 
    static int i = 0; 
    static int j = 0; 
    static Random rand = new Random(); 
    static Individual[] n_population = new Individual[P]; 
    static Individual[] offspring = new Individual[P]; 

    public static Individual[] population() { 
     int rn = rand.nextInt(); 

     for (i = 0; i < P; i++) { 
      for (j = 0; j < N; j++) { 
       n_population[i].gene[j] = rn % 2; 
      } 
      n_population[i].fitness = 0; 
     } 
     return n_population; 
    } 

    public static int CalculateFitness(int[] gene) { 
     gene = new int[N]; 
     fitness = 0; 
     for (j = 0; j < N;) { 
      for (i = 0; i < P;) { 
       if (n_population[i].gene[j] != 0) n_population[i].fitness++; 
      } 
     } 
     return fitness; 
    } 

    public static Individual[] Selection(Individual[] n_population) { 
     n_population = new Individual[P]; 
     offspring = new Individual[P]; 
     fitness = 0; 
     int rands = rand.nextInt(); 
     int parent1 = rands % P; 
     int parent2 = rands % P; 
     for (i = 0; i < P; i++) { 
      **if (n_population[parent2].fitness >= n_population[parent1].fitness)** 
       offspring[i] = n_population[parent1]; 
      else { 
       offspring[i] = n_population[parent2];** 
      } 
     } 
     return offspring; 
    } 

    public static Individual[] Crossover(Individual[] n_population) { 
     int rands = rand.nextInt(); 
     n_population = new Individual[P]; 
     offspring = new Individual[P]; 
     gene = new int[N]; 
     int[] temp_gene1 = new int[N]; 
     int[] temp_gene2 = new int[N]; 
     int parent1 = rands % P; 
     int parent2 = rands % P; 
     int crossoverPoint = rands % N; 

     for (j = 0; j < N; j++) { 
      if (j > crossoverPoint) { 
       temp_gene1[j] = n_population[parent2].gene[j]; 
       temp_gene2[j] = n_population[parent1].gene[j]; 
      } else { 
       * temp_gene1[j] = n_population[parent1].gene[j]*; 
       temp_gene2[j] = n_population[parent2].gene[j]; 
      } 
     } 

     if (CalculateFitness(temp_gene1) >= CalculateFitness(temp_gene2)) 
      offspring[i] = n_population[parent1]; 
     else { 
      offspring[i] = n_population[parent2]; 
     } 
     return offspring; 
    } 

    public static Individual[] Mutation(Individual[] n_population) { 
     double x = 0.1; 
     double y = 0.107; 
     double randoms = rand.nextDouble(); 
     for (i = 0; i < P;) { 
      for (j = 0; j < N;) { 
       if ((x < randoms) && (randoms < y)) { 
        if (n_population[i].gene[j] == 0) 
         n_population[i].gene[j] = 1; 
        else { 
         n_population[i].gene[j] = 0; 
        } 
       } 
       offspring[i] = n_population[i]; 
      } 
     } 
     return offspring; 
    } 

    public static int Mean(Individual[] n_population) { 
     int mean_fitness = 0; 
     for (i = 0; i < P;) { 
      mean_fitness += n_population[i].fitness; 
     } 
     return (mean_fitness/P); 
    } 

    public static void main(String[] args) { 

     n_population = population(); 

     for (i = 0; i < 50; i++) { 
      n_population = Selection(n_population); 
      n_population = Crossover(n_population); 
      n_population = Mutation(n_population); 
     } 
    } 
} 

Answer 1

您有：

public static Individual[] Selection(Individual[] n_population) { 
    n_population = new Individual[P]; 

所以，你傳入n_population，然後立即隱藏它，並聲明一個數組，其中包含所有空值。所以，其中的任何n_population[i]都是空的。我希望你得到一個NullPointerException異常，當你在後來檢查.fitness（未出界）

我想你應該刪除n_population = new Individual[P];