gurobi之python调用实例_使用Python调用Gurobi求解PDPTW问题（Li & Lim's benchmark）

# -*- coding: utf-8 -*-

"""Created on Wed Jul 1 12:24:37 2020@author: AtticusYuan"""

from gurobipy import *

import numpy as np

import pandas as pd

import math

import random

import time

def read_txt_data(DataPath):

"""读取数据.读取Li & Lim's PDPTW benchmark 的txt文件格式的数据.参数----------arg1 : intarg1的具体描述arg2 : intarg2的具体描述返回值-------int返回值的具体描述参看--------otherfunc : 其它关联函数等...示例--------示例使用doctest格式, 在`>>>`后的代码可以被文档测试工具作为测试用例自动运行>>> a=[1,2,3]>>> print [x + 3 for x in a][4, 5, 6]"""

# 读取车辆信息

VehiclesInfo=pd.read_table(DataPath,nrows=1,names=['K','C','S'])

#print('VehiclesInfo:')

#print(VehiclesInfo)

Vehicles={}

for i in range(VehiclesInfo.iloc[0,0]):

Vehicles[i]=[VehiclesInfo.iloc[0,1],VehiclesInfo.iloc[0,2]] # 键i=车辆的序号，值为[车辆容量、速度]

#print(Vehicles)

# 读取Depot和任务信息

ColumnNames=['TaskNo','X','Y','Demand','ET','LT','ST','PI','DI']

TaskData=pd.read_table(DataPath,skiprows=[0],names=ColumnNames,index_col='TaskNo')

#print('TaskData:')

#print(TaskData)

# 提取Depot和取送货点(Customer)的位置坐标 Locations

nrows=TaskData.shape[0]

Locations={}

for i in range(nrows):

if i not in Locations.keys():

Locations[i]=[TaskData.iloc[i,0],TaskData.iloc[i,1]] # 键为depot或客户编号，值为相应的坐标(x，y)

#print('Locations:',Locations)

# 提取Depot和取送货点的Demand

Demand={}

for i in range(nrows):

if i not in Demand.keys():

Demand[i]=TaskData.iloc[i,2]

#print('Demand',Demand)

# 提取Depot和取送货点的最早和最晚取送货时间及时间窗

TimeWindow={}

EarliestTime=TaskData.sort_values(by='ET').iloc[0,3]

LatestTime=TaskData.sort_values(by='LT',ascending=False).iloc[0,4]

for i in range(nrows):

if i not in TimeWindow.keys():

TimeWindow[i]=[TaskData.iloc[i,3],TaskData.iloc[i,4]]

# print('TimeWindow',TimeWindow)

# print('EarliestTime:',EarliestTime)

# print('LatestTime:',LatestTime)

# 提取Depot和取送货点的服务时间ServiceTime

ServiceTime={}

for i in range(nrows):

if i not in ServiceTime.keys():

ServiceTime[i]=TaskData.iloc[i,5]

#print('ServiceTime',ServiceTime)

# 提取运输Request

# 对于取货任务，PICKUP索引为0，而同一行的DELIVERY索引给出相应送货任务的索引

Request={}

count = 0 # 记录运输需求的数量

for i in range(1,nrows-1):

if TaskData.iloc[i,6] == 0:

Request[count]=[i,TaskData.iloc[i,7]] # 将取送货点组合在一起，键为co