如何使用Pulp解決以下LP / QP問題？

Question

from pulp import *
import pandas as pd
import numpy as np
pd.read_excel('Example.xlsx', encoding='latin-1')

prob = pulp.LpProblem('Performance', pulp.LpMaximize)

#### Create Decision Variables:
decision_variables = []
for rownum, row in data.iterrows():
    variable = str('x' + str(rownum))
    variable = pulp.LpVariable(str(variable), lowBound= row['D']*0.7, 
upBound= row['D']*1.3, cat='Continuous')
decision_variables.append(variable)

#### Define Objective Function
total_cost = ""   
for rownum, row in data.iterrows():
    for i, variable in enumerate(decision_variables):
        if rownum == i:
            formula = variable * row['C'] * row['F'] / row['D']
            total_cost += formula           
prob += total_cost
print("Optimization Function: " + str(total_cost))

#### Define Constraints
problem_spend = ""
for rownum, row in data.iterrows():
    for i, variable in enumerate(decision_variables):
        if rownum == i:
            formula = variable * variable * row['C'] * row['F'] * row['E'] / row['D']
            problem_spend += formula
prob += (total_spend == problem_spend)

[ ]在運行#### Define約束部分后得到以下錯誤：'TypeError：非常數表達式不能相乘。 這可能是因為我的約束條件包括非線性變量。

我的Objective函數是線性的：公式：Maximize [Variable * constant]

我的約束是二次方的：公式：[變量*變量*常數==常數值]

我是PULP的新手，並且遇到此錯誤遇到的困難。 有什么方法可以使用CVXPy或其他方法解決？

Answer 1

紙漿無法制定或解決QP問題。我建議您使用CVXpy，Gurobi或Cplex。 或重新制定問題以使用線性約束