Question

这是与软计算和优化相关的概念疑问。我正在实施离散入侵杂草优化（DIWO）来解决旅行商问题。我们从这篇研究论文中学习：

https://www.researchgate.net/publication/280261944_A_discrete_invasive_weed_optimization_algorithm_for_solving_traveling_salesman_problem

代码的DIWO部分片段：

# for every iteration i till iter_max
sd_iter = ( ( float(pow(iter_max-i,mod_index)) / float(pow(iter_max,mod_index)) ) * (sd_i-sd_f)) + sd_f
fmax = max(population)[0]           # weed with maximum fitness
fmin = min(population)[0]
print("Generation ",i, "Max Fitness =",fmax,"  Tour length = ",int(1/fmax))
for j in range(len(population)):
  #Calculate number of seeds for a given fitness
  s = no_seed(population[j][0],fmax,fmin)

  for k in range(s):
    cities = []                       #cities stores each seed's tour
    for z in range(max_city):
      # getting seeds using normal distribution function
      param = np.random.normal(population[j][1][z],sd_iter,None)
      param = int(param)
      val = param % max_city
      val += 1
      cities.append(val)

    count = [0] * max_city            #count[i] stores the number of times (i+1)'th city is repeated in 'cities'
    zero_count = []                   #zero_count contains cities which have not been included in 'cities' i.e. count[i+1] = 0
    for v in cities:
      count[v-1] += 1  
    for q in range(max_city):
      if count[q] == 0:
        zero_count.append(q+1)

    #Every city is to be visited and repetitions eliminated
    px = 0
    for q in range(len(cities)):
      if count[cities[q]-1] > 1:
        count[cities[q]-1] -= 1
        cities[q] = zero_count[px]
        px += 1

    first_city = cities[0]
    cities.append(first_city)
    cost = path_length(tsp,cities)
    fit = fitness(cost)
    seed = (fit,cities)

    population.append(seed)

    population.sort(reverse=True)

    #competitive exclusion
    population=population[0:gen_n_max]
final = population[0]

怀疑是在正常分配的步骤中，＆＃34; random.normal（...）＆＃34;它产生相对于相应杂草（亲本）的种子。当我们打印种子时，它们的结果远远超过最佳值。比如我在＆＃39; Berlin52.tsp＆＃39;来自TSPLIB95的在线数据集，其最佳旅行成本为7542.但是当打印种子时，即使一粒种子的健康状况也不会接近最佳成本。

我的种子成本高于25000-30000。我知道种子基本上是杂草的排列，但不应该只有一个种子有点接近7542像9000s？ 10,000s？至少。

也许错误在于探索和利用？任何帮助或推动这个方向将非常感谢！

离散入侵杂草优化正态分布以生成种子

0 个答案: