Question

我想以最少的糖摄入量制定一个最佳的饮食计划， 7天，但每日饮食计划应包括3种不同类别的食物。如何添加限制，使我可以从3种不同的食物中获取食物并制定7天的用餐计划？

我的数据框如下：

id      name               energy   sugar   Food_Groups
1       4-Grain Flakes      140     58.8    Breakfast
2       Beef Mince, Fried   1443    8.0     Meat
3       Pork                1000    3.0     Meat
4       cake                1200    150     Sweet
5       cheese              1100    140     Sweet
6       Juice               700     85      Drink
7       cabbage             60      13      vegetarian
8       cucumber            10      10      vegetarian
9       eggs                45      30      Breakfast

我创建了一个prob变量，制定了目标函数，创建了字典变量，添加了约束，并按以下方式解决了

# Create the 'prob' variable to contain the problem data
prob = LpProblem("Simple Diet Problem",LpMinimize)
#create data variables and dictionary
food_items = list(df['name'])
calories = dict(zip(food_items,df['energy']))
sugars = dict(zip(food_items,df['sugar']))

food_vars =LpVariable.dicts("Food",food_items,lowBound=0,cat='Integer')

#Building the LP problem by adding the main objective function.
prob += lpSum([sugars[i]*food_vars[i] for i in food_items])

#adding calorie constraint
prob += lpSum([calories[f] * food_vars[f] for f in food_items]) >= 
1800.0, "CalorieMinimum"
prob += lpSum([calories[f] * food_vars[f] for f in food_items]) <= 
2200.0, "CalorieMaximum"

prob.writeLP("SimpleDietProblem.lp")

prob.solve()

print("Status:", LpStatus[prob.status])

我想知道如何制作7天菜单？我尝试了以下代码，但是重复了相同的食物

    days = ['Monday', 'Tuesday', 'Wednesday', 'Thursday', 'Friday', 'Saturday', 'Sunday']
for i in days:
    print(days)
    prob.writeLP("SimpleDietProblem.lp")
    prob.solve(PULP_CBC_CMD())
    print("Status:", LpStatus[prob.status])
    print("Therefore, the optimal balanced diet consists of\n"+"-")
    for v in prob.variables():
        if v.varValue:
            print(v.name , "=", v.varValue)
            print("The total sugar of this balanced diet is: {}".format(round(value(prob.objective),2)))

在PuLP中的计划优化中添加7天约束

0 个答案: