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main.py

-print('欢迎来到 InsCode')
+import random
\ No newline at end of file
+
+# 求y =-(400-x)*(400-x)+160000的最大值
+# 种群初始化
+def origin(number, size):
+    population = []
+    for i in range(number):
+        temp = []
+        for j in range(size):
+            temp.append(random.randint(0, 1))
+        population.append(temp)
+    return population
+
+# 评估适应度
+def fitness(body, size):
+    ten_number = 0
+    count = size-1
+    for i in body[0:size]:
+        ten_number = ten_number + i*pow(2, count)
+        count = count-1
+    fit =-(400-ten_number)*(400-ten_number)+160000
+    return fit
+
+# 轮盘选择
+def Select(population, size):
+    total = 0
+    temp = 0
+    select = []
+    for n in range(len(population)): select.append([])
+    # select数组为二维数组，每一个数组中存放挑选的概率和选中的次数
+    for i in range(len(population)):
+        total = total+population[i][size]
+    for j in range(len(population)):
+        temp = temp + population[j][size] / total
+        select[j].append(temp)
+    for n in range(len(population)): select[n].append(0) #修改为A[ ,0]的形式
+    for i in range(len(population)): #重复n次
+        x = random.random()
+        for z in range(len(select)): #修改选择的次数
+            if x <= select[z][0]:
+                select[z][1] = select[z][1]+1
+                break
+    min = max = select[0][1]
+    min_num =  max_num = 0
+    for i in range(len(select)):# 寻找最优个体位置
+        if select[i][1] < min:
+            min = select[i][1]
+            min_num = i
+        if select[i][1] > max:
+            max = select[i][1]
+            max_num = i
+    return (max_num,min_num)
+
+# 交配运算
+def crossover(population, size, max_mum):
+    temp_list0 = population[max_mum]
+    for i in range(len(population)):
+        if i == max_mum:
+            population[i].pop(size)# 防止自己和自己交配
+            continue
+        seed = random.randint(0, size-1)
+        tem_list = population[i]
+        population[i] = temp_list0[0:seed] + tem_list[seed:size] # 都和最优个体交配
+    return population
+
+# 变异
+def change(population, size, seed):
+    for i in range(len(population)):
+        if random.random() > seed:
+            x = random.randint(0, size-1)
+            if population[i][x] == 1:
+                population[i][x] = 0
+            else:
+                population[i][x] = 1
+    return population
+
+number = 30
+size = 10
+GA_number = 100
+seed = 0.01
+best = 0
+population = origin(number, size)
+print(population)
+for i in range(GA_number):
+    for j in range(len(population)):
+        population[j].append(fitness(population[j], size))
+    (max_num, min_num) = Select(population, size)
+    population[min_num] = population[max_num] #将最小选择的数组替换为最大的数组
+    population = crossover(population, size, max_num)
+    population = change(population, size, seed)
+print(population)
+for j in range(len(population)):
+    population[j].append(fitness(population[j], size))
+print(population)
+(max_num, min_num) = Select(population, size)
+best_body = population[max_num]
+count = size-1
+for i in best_body[0:size]:
+    best = best + i * pow(2, count)
+    count = count - 1
+print(best)
+
+