【问题标题】:Different output release compared to debug与调试相比不同的输出版本
【发布时间】:2017-04-02 19:22:48
【问题描述】:

我有一个关于我正在创建的遗传算法的输出的问题。与在特定位置进行调试相比,我刚运行项目时似乎得到了不同的输出。

我的部分代码如下所示:

Population mutatePopulation(Population pop)
    {
        foreach(Chromosome x in pop.population)
        {
            x.mutateChromosome(x);
        }
        return pop;
    }

在上面的代码中,我希望我的一些 Chromosome 对象发生变异。这是通过以下方法完成的:

public Chromosome mutateChromosome(Chromosome x)
    {
        Chromosome result = x;
        //SWAP mutation
        Random rnd = new Random();
        double value = rnd.NextDouble();
        if (value < MUTATION_RATE)
        {
            int index1 = (int)rnd.Next(0, x.customerSequence.Count() - 1);
            int index2 = (int)rnd.Next(0, x.customerSequence.Count() - 1);
            Console.WriteLine(  "Muation at chromosome: " + x.ToString() + ", mutation at indexes [" + index1 + "," + index2+ 
                                "], values ["+x.customerSequence[index1].index+","+x.customerSequence[index2].index+"]");
            Customer cust1 = x.customerSequence[index1];
            Customer cust2 = x.customerSequence[index2];
            result.customerSequence[index1] = cust2;
            result.customerSequence[index2] = cust1;
        }
        return result;
    }

当我运行我的项目时,我(有时取决于随机变量)得到以下输出:

Generation #14 
10 12 9 5 4 2 8 13 6 3 7 11  ||  Fitness: 3209
11 6 12 3 5 9 10 4 7 2 8 13  ||  Fitness: 3252
13 8 11 4 10 3 6 5 9 2 12 7  ||  Fitness: 3301
10 9 4 11 6 13 12 3 5 8 2 7  ||  Fitness: 3315
7 3 9 10 11 4 13 8 6 2 5 12  ||  Fitness: 3354
6 10 4 8 13 2 7 12 3 5 11 9  ||  Fitness: 3361
10 7 13 5 8 9 3 6 11 4 2 12  ||  Fitness: 3394
11 12 5 8 10 4 9 13 2 7 3 6  ||  Fitness: 3499
11 13 12 9 3 4 7 5 10 6 2 8  ||  Fitness: 3708
8 9 6 5 2 13 11 7 10 3 4 12  ||  Fitness: 3819

Generation #15
Muation at chromosome: XML.Chromosome, mutation at indexes [5,7], values [2,13]
Muation at chromosome: XML.Chromosome, mutation at indexes [5,7], values [9,4]
Muation at chromosome: XML.Chromosome, mutation at indexes [5,7], values [3,5]
Muation at chromosome: XML.Chromosome, mutation at indexes [5,7], values [13,3]
Muation at chromosome: XML.Chromosome, mutation at indexes [5,7], values [4,8]
Muation at chromosome: XML.Chromosome, mutation at indexes [5,7], values [2,12]
Muation at chromosome: XML.Chromosome, mutation at indexes [5,7], values [9,6]
Muation at chromosome: XML.Chromosome, mutation at indexes [5,7], values [4,13]
Muation at chromosome: XML.Chromosome, mutation at indexes [5,7], values [4,5]
Muation at chromosome: XML.Chromosome, mutation at indexes [1,6], values [9,11]
13 8 11 4 10 5 6 3 9 2 12 7  ||  Fitness: 3025
11 6 12 3 5 4 10 9 7 2 8 13  ||  Fitness: 3088
10 7 13 5 8 6 3 9 11 4 2 12  ||  Fitness: 3112
10 12 9 5 4 13 8 2 6 3 7 11  ||  Fitness: 3315
6 10 4 8 13 12 7 2 3 5 11 9  ||  Fitness: 3381
11 13 12 9 3 5 7 4 10 6 2 8  ||  Fitness: 3689
10 9 4 11 6 3 12 13 5 8 2 7  ||  Fitness: 3730
7 3 9 10 11 8 13 4 6 2 5 12  ||  Fitness: 3733
11 12 5 8 10 13 9 4 2 7 3 6  ||  Fitness: 3755
8 11 6 5 2 13 9 7 10 3 4 12  ||  Fitness: 3808

似乎当一个染色体发生突变时,其他所有染色体也会发生突变。

但是,当我调试时,我得到了我需要的输出:

Generation #2
2 13 3 12 7 5 4 10 11 9 8 6  ||  Fitness: 2823
13 6 11 5 2 9 4 10 7 8 12 3  ||  Fitness: 3019
4 13 12 8 6 10 7 3 5 11 9 2  ||  Fitness: 3254
3 7 11 4 2 8 9 10 13 5 6 12  ||  Fitness: 3267
3 4 2 8 9 5 11 7 6 10 13 12  ||  Fitness: 3309
2 7 5 8 9 4 10 3 6 12 13 11  ||  Fitness: 3448
12 4 2 5 8 10 6 13 11 3 9 7  ||  Fitness: 3484
7 12 8 11 5 3 10 13 2 9 6 4  ||  Fitness: 3712
11 7 5 6 4 3 12 13 2 9 8 10  ||  Fitness: 3775
2 6 12 10 11 13 3 4 8 9 7 5  ||  Fitness: 3846

Generation #3
Muation at chromosome: XML.Chromosome, mutation at indexes [1,3], values [6,5]
Muation at chromosome: XML.Chromosome, mutation at indexes [8,7], values [13,10]
Muation at chromosome: XML.Chromosome, mutation at indexes [8,8], values [6,6]
Muation at chromosome: XML.Chromosome, mutation at indexes [4,6], values [9,10]
2 13 3 12 7 5 4 10 11 9 8 6  ||  Fitness: 2823
3 7 11 4 2 8 9 13 10 5 6 12  ||  Fitness: 3249
4 13 12 8 6 10 7 3 5 11 9 2  ||  Fitness: 3254
3 4 2 8 9 5 11 7 6 10 13 12  ||  Fitness: 3309
13 5 11 6 2 9 4 10 7 8 12 3  ||  Fitness: 3434
2 7 5 8 10 4 9 3 6 12 13 11  ||  Fitness: 3443
12 4 2 5 8 10 6 13 11 3 9 7  ||  Fitness: 3484
7 12 8 11 5 3 10 13 2 9 6 4  ||  Fitness: 3712
11 7 5 6 4 3 12 13 2 9 8 10  ||  Fitness: 3775
2 6 12 10 11 13 3 4 8 9 7 5  ||  Fitness: 3846

有人可以帮我解决我的问题吗?我有预感它与我正在使用的 Random 对象有关,但我似乎无法弄清楚。 谢谢!

(PS。这是我第一次在这里提出自己的问题,如果我不遵守规则,请见谅)

【问题讨论】:

  • 为什么数组索引需要双精度值?

标签: c# debugging output genetic-algorithm


【解决方案1】:

问题是您在 mutate 方法中创建了一个 new Random()。不要这样做。如果您足够快地突变足够多的染色体,每个Random 实例将获得相同的值并产生相同的随机数序列。

相反,创建Random 的单个实例并将其用于所有染色体。例如:

Population mutatePopulation(Population pop, Random random)
{
    foreach(Chromosome x in pop.population)
    {
        x.mutateChromosome(x, random);
    }
    return pop;
}

public Chromosome mutateChromosome(Chromosome x, Random rnd)
{
    Chromosome result = x;
    //SWAP mutation
    double value = rnd.NextDouble();
    if (value < MUTATION_RATE)
    {
        int index1 = (int)rnd.Next(0, x.customerSequence.Count() - 1);
        int index2 = (int)rnd.Next(0, x.customerSequence.Count() - 1);
        Console.WriteLine(  "Muation at chromosome: " + x.ToString() + ", mutation at indexes [" + index1 + "," + index2+ 
                            "], values ["+x.customerSequence[index1].index+","+x.customerSequence[index2].index+"]");
        Customer cust1 = x.customerSequence[index1];
        Customer cust2 = x.customerSequence[index2];
        result.customerSequence[index1] = cust2;
        result.customerSequence[index2] = cust1;
    }
    return result;
}

在某个时候,这个单一的随机实例将被创建并存储在一个字段中。如果不了解您创建的架构,我无法说出最佳位置在哪里,因此我将随机实例移动为要传递给需要随机性的方法的参数。

【讨论】:

  • 感谢您的快速回复!我不知道 Random 实例是这样工作的。这确实解决了我的问题:-)
  • @Marijn,如果这解决了您的问题,请考虑标记答案。
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