这是我正在处理“项目选择”问题的数据框:
Return Sector Investment Project_name
0.290 Solar 228376120 Solar1
0.07 Solar 70021891 Solar2
0.25 Wind 6467237 Eolico1
0.3 Wind 417713440 Eolico2
0.16 Wind 377494250 Eolico3
0.28 Wind 230345712 Eolico4
0.29 CGHPCHBIO 35476862 CGH1
0.26 CGHPCHBIO 60671402 CGH2
0.07 CGHPCHBIO 349544333 PCH1
0.12 CGHPCHBIO 425442985 PCH2
0.29 CGHPCHBIO 66292734 PCH3
0.15 CGHPCHBIO 300677487 PCH4
0.25 CGHPCHBIO 409144798 Biomassa1
0.19 CGHPCHBIO 184123496 Biomassa2
0.08 CGHPCHBIO 61835863 Biomassa3
我的目标是:
Maximize the "Return"
我的限制是:
from pulp import *
import pandas as pd
import xlrd
#First, we create a LP problem with the method LpProblem in PuLP
prob = LpProblem("Selecao de Projetos",LpMaximize)
#Read the first rows dataset in a Pandas DataFrame
df = pd.read_excel("df.xlsx", encoding = 'unicode_escape')
#Create a list of the projects names
projects = list(df['Project_name'])
#Create a dictionary of investments for all the projects
investments = dict(zip(projects,df['Investment']))
#Create a dictionay of sectors for all the projects
sectors = dict(zip(projects,df['Sector']))
#Create a dictionary of Returns for all the projects
returns = dict(zip(projects,df['Return']))
#Create a dictionary of projects with lower bound = 0 and category continuous
project_vars = LpVariable.dicts("Project",projects,lowBound =0,cat='Continuous')
#Built the LP problem by assing the main objective function
prob += lpSum([returns[i]*project_vars[i] for i in projects])
#Add the constraints
prob += lpSum([investments[f] * project_vars[f] for f in projects]) <= 916000000
prob += lpSum([investments[f] * project_vars[f] for f in sectors["Solar"]]) <= sum(df['Investment'])*0.6 #this last one isn't working.
我想知道如何正确估算
关于按部门划分的最大投资权重的限制。
这就是我正在处理“项目选择”问题的数据帧:返回行业投资项目名称0.290太阳能228376120太阳能1 0.07太阳能70021891太阳能2 0.25 ...