如何使用Pulp解决以下LP / QP问题？

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)

[] 在运行#### Define约束部分后得到以下错误：'TypeError：非常数表达式不能相乘。这可能是因为我的约束条件包括非线性变量。

我的Objective函数是线性的：公式：Maximize [Variable * constant]

我的约束是二次方的：公式：[变量*变量*常数==常数值]

我是PULP的新手，并且遇到此错误遇到的困难。有什么方法可以使用CVXPy或其他方法解决？

Answer 1

纸浆无法制定或解决QP问题。我建议您使用CVXpy，Gurobi或Cplex。或重新设计问题以使用线性约束