我有一个这样的形式的清单：
["Name/num1/num2/num3/num4/num5", ...]
例如：
available = ["a/1/2/3/4/5", "b/5/4/3/2/4", "c/4/3/2/1/3"]
我正在尝试在available中创建所有可能的项目组合，其中组合中每个项目的num5之和（例如for a is 5，for b is 1，for c is 5 ）小于MAXNUM（例如3000）。
为了举例说明，该程序将为上方available和MAXNUM = 9创建一个生成器，可以将其生成以下列表：
[["a/1/2/3/4/5", "b/5/4/3/2/4"], ["a/1/2/3/4/5", c/4/3/2/1/3], [b/5/4/3/2/4, b/5/4/3/2/4], [b/5/4/3/2/4, "c/4/3/2/1/3"], ["c/4/3/2/1/3", "c/4/3/2/1/3", "c/4/3/2/1/3"]]
注意：此代码需要在合理的时间内（理想情况下，不超过10分钟）返回包含100个项目的available和MAXNUM = 3000的结果
编辑：这是我根据要求实际使用的代码：
import itertools
import sys
import time
sys.setrecursionlimit(10000000)
#["Name/Carbs/Protein/Fat/Vitamins/Calories"]
available = ['Fiddleheads/3/1/0/3/80', 'Fireweed Shoots/3/0/0/4/150', 'Prickly Pear Fruit/2/1/1/3/190', 'Huckleberries/2/0/0/6/80', 'Rice/7/1/0/0/90', 'Camas Bulb/1/2/5/0/120', 'Beans/1/4/3/0/120', 'Wheat/6/2/0/0/130', 'Crimini Mushrooms/3/3/1/1/200', 'Corn/5/2/0/1/230', 'Beet/3/1/1/3/230', 'Tomato/4/1/0/3/240', 'Raw Fish/0/3/7/0/200', 'Raw Meat/0/7/3/0/250', 'Tallow/0/0/8/0/200', 'Scrap Meat/0/5/5/0/50', 'Prepared Meat/0/4/6/0/600', 'Raw Roast/0/6/5/0/800', 'Raw Sausage/0/4/8/0/500', 'Raw Bacon/0/3/9/0/600', 'Prime Cut/0/9/4/0/600', 'Cereal Germ/5/0/7/3/20', 'Bean Paste/3/5/7/0/40', 'Flour/15/0/0/0/50', 'Sugar/15/0/0/0/50', 'Camas Paste/3/2/10/0/60', 'Cornmeal/9/3/3/0/60', 'Huckleberry Extract/0/0/0/15/60', 'Yeast/0/8/0/7/60', 'Oil/0/0/15/0/120', 'Infused Oil/0/0/12/3/120', 'Simple Syrup/12/0/3/0/400', 'Rice Sludge/10/1/0/2/450', 'Charred Beet/3/0/3/7/470', 'Camas Mash/1/2/9/1/500', 'Campfire Beans/1/9/3/0/500', 'Wilted Fiddleheads/4/1/0/8/500', 'Boiled Shoots/3/0/1/9/510', 'Charred Camas Bulb/2/3/7/1/510', 'Charred Tomato/8/1/0/4/510', 'Charred Corn/8/1/0/4/530', 'Charred Fish/0/9/4/0/550', 'Charred Meat/0/10/10/0/550', 'Wheat Porridge/10/4/0/10/510', 'Charred Sausage/0/11/15/0/500', 'Fried Tomatoes/12/3/9/2/560', 'Bannock/15/3/8/0/600', 'Fiddlehead Salad/6/6/0/14/970', 'Campfire Roast/0/16/12/0/1000', 'Campfire Stew/5/12/9/4/1200', 'Wild Stew/8/5/5/12/1200', 'Fruit Salad/8/2/2/10/900', 'Meat Stock/5/8/9/3/700', 'Vegetable Stock/11/1/2/11/700', 'Camas Bulb Bake/12/7/5/4/400', 'Flatbread/17/8/3/0/500', 'Huckleberry Muffin/10/5/4/11/450', 'Baked Meat/0/13/17/0/600', 'Baked Roast/4/13/8/7/900', 'Huckleberry Pie/9/5/4/16/1300', 'Meat Pie/7/11/11/5/1300', 'Basic Salad/13/6/6/13/800', 'Simmered Meat/6/18/13/5/900', 'Vegetable Medley/9/5/8/20/900', 'Vegetable Soup/12/4/7/19/1200', 'Crispy Bacon/0/18/26/0/600', 'Stuffed Turkey/9/16/12/7/1500']
global AllSP, AllNames
AllSP = []
AllNames = []
def findcombs(totalNames, totalCarbs, totalProtein, totalFat, totalVitamins, totalNutrients, totalCalories, MAXCALORIES):
doneit = False
for each in available:
each = each.split("/")
name = each[0]
carbs = float(each[1])
protein = float(each[2])
fat = float(each[3])
vitamins = float(each[4])
nutrients = carbs+protein+fat+vitamins
calories = float(each[5])
# print(totalNames, totalCalories, calories, each)
if sum(totalCalories)+calories <= MAXCALORIES:
doneit = True
totalNames2 = totalNames[::]
totalCarbs2 = totalCarbs[::]
totalProtein2 = totalProtein[::]
totalFat2 = totalFat[::]
totalVitamins2 = totalVitamins[::]
totalCalories2 = totalCalories[::]
totalNutrients2 = totalNutrients[::]
totalNames2.append(name)
totalCarbs2.append(carbs)
totalProtein2.append(protein)
totalFat2.append(fat)
totalVitamins2.append(vitamins)
totalCalories2.append(calories)
totalNutrients2.append(nutrients)
# print(" ", totalNames2, totalCarbs2, totalProtein2, totalFat2, totalVitamins2, totalNutrients2, totalCalories2)
findcombs(totalNames2, totalCarbs2, totalProtein2, totalFat2, totalVitamins2, totalNutrients2, totalCalories2, MAXCALORIES)
else:
#find SP
try:
carbs = sum([x * y for x, y in zip(totalCalories, totalCarbs)]) / sum(totalCalories)
protein = sum([x * y for x, y in zip(totalCalories, totalProtein)]) / sum(totalCalories)
fat = sum([x * y for x, y in zip(totalCalories, totalFat)]) / sum(totalCalories)
vitamins = sum([x * y for x, y in zip(totalCalories, totalVitamins)]) / sum(totalCalories)
balance = (carbs+protein+fat+vitamins)/(2*max([carbs,protein,fat,vitamins]))
thisSP = sum([x * y for x, y in zip(totalCalories, totalNutrients)]) / sum(totalCalories) * balance + 12
except:
thisSP = 0
#add SP and names to two lists
AllSP.append(thisSP)
AllNames.append(totalNames)
def main(MAXCALORIES):
findcombs([], [], [], [], [], [], [], MAXCALORIES)
index = AllSP.index(max(AllSP))
print()
print(AllSP[index], " ", AllNames[index])
for i in range(100, 3000, 10):
start = time.time()
main(i)
print("Calories:", i, ">>> Time:", time.time()-start)
答案 0 :(得分：1)
对，因此N食品的任务在时间和空间上的复杂度为O(exp(N))。您需要的是类似A* (link)的启发式搜索，该搜索遵循某种想法，即一个不完全组合的“好”是指导其进一步的搜索。结果，您将不会找到最佳的解决方案，而是在有限的时间内找到切实可行的解决方案。替代方法是遗传算法，模拟退火和其他优化算法。请注意，您必须定义每个组合的好坏的度量！
我在我的视频游戏AI中使用了astar（https://github.com/jrialland/python-astar）软件包，它超出了我的期望。
其他建议：使用namedtuple使代码更具可读性，否则您将不喜欢查找错误并对其进行扩展：
from collections import namedtuple
food = namedtuple('Food', 'name carbs protein fat vitamins calories')
bananas = food('bananas', 10, 15, 20, 10, 100)
oranges = food('oranges', carbs=10, protein=15, fat=20, vitamins=10, calories=100)
print(bananas.calories, oranges.fat)
答案 1 :(得分：1)
Given the high number of possibilities, perhaps you should approach the use of this information differently. For example, if the usage context is selection of foods given a prior selection, you could simply provide the information on how many of each food type can be had without going over the maximum
foofInfo = [ food.split("/") for food in available ]
foofInfo = { food[0]:tuple([int(v) for v in food[1:]]) for food in available } #name:(carbs,proteins,fat,vitamins,nutrients,calories)
calFood = {}
for name,(_,_,_,_,calories) in foofInfo.items():
if calories not in calFood: calFood[calories] = []
calFood[calories].append(name)
maxCalories = 3000
for calories,foods in calFood.items():
maxCount = maxCalories//calories
print("Up to ",maxCount," of ",", ".join(foods))
So you could propose a progressive refinement of the available options rather than a bazillion combinations:
Up to 37 of Fiddleheads, Huckleberries
Up to 20 of Fireweed Shoots
Up to 15 of Prickly Pear Fruit
Up to 33 of Rice
Up to 25 of Camas Bulb, Beans, Oil, Infused Oil
Up to 23 of Wheat
Up to 15 of Crimini Mushrooms, Raw Fish, Tallow
Up to 13 of Corn, Beet
Up to 12 of Tomato
Up to 12 of Raw Meat
Up to 60 of Scrap Meat, Flour, Sugar
Up to 5 of Prepared Meat, Raw Bacon, Prime Cut, Bannock, Baked Meat, Crispy Bacon
Up to 3 of Raw Roast, Basic Salad
Up to 6 of Raw Sausage, Camas Mash, Campfire Beans, Wilted Fiddleheads, Charred Sausage, Flatbread
Up to 150 of Cereal Germ
Up to 75 of Bean Paste
Up to 50 of Camas Paste, Cornmeal, Huckleberry Extract, Yeast
Up to 7 of Simple Syrup, Camas Bulb Bake
Up to 6 of Rice Sludge, Huckleberry Muffin
Up to 6 of Charred Beet
Up to 5 of Boiled Shoots, Charred Camas Bulb, Charred Tomato, Wheat Porridge
Up to 5 of Charred Corn
Up to 5 of Charred Fish, Charred Meat
Up to 5 of Fried Tomatoes
Up to 3 of Fiddlehead Salad
Up to 3 of Campfire Roast
Up to 2 of Campfire Stew, Wild Stew, Vegetable Soup
Up to 3 of Fruit Salad, Baked Roast, Simmered Meat, Vegetable Medley
Up to 4 of Meat Stock, Vegetable Stock
Up to 2 of Huckleberry Pie, Meat Pie
Up to 2 of Stuffed Turkey