AttributeError: Unable to retrieve attribute 'ObjVal'

The modeling is feasible but AttributeError: Unable to retrieve attribute 'ObjVal'.

The optimization problem are shown as follows.

The code is shown as follows.

# _*_coding:utf-8 _*_
from __future__ import print_function

from typing import List, Any

from gurobipy import *
import re
import math
import matplotlib.pyplot as plt
import numpy
import pandas as pd

class Data:
    vehicleNum = 3  # 卡车数量
    droneNum = 2  # 无人车数量
    capacity = 200  # 卡车容量
    capacity_1 = 50  # 无人车容量
    W = 30  # 无人车释放所需时间
    w = 40  # 无人车回收所需时间
    cor_X = []
    cor_Y = []
    demand = []
    serviceTime = []
    readyTime = [0, 448, 652, 30, 567, 384, 475, 99, 179, 278, 912]
    dueTime = [1236, 505, 721, 92, 620, 429, 528, 148, 254, 345, 967]
    disMatrix = [[]]

# function to read data from .txt files
def readData(data, path, customerNum):
    data.customerNum = customerNum
    data.nodeNum = customerNum + 2
    f = open(path, 'r')
    lines = f.readlines()
    count = 0
    # read the info
    for line in lines:
        count = count + 1
        if (count == 5):
            line = line[:-1].strip()
            str = re.split(r" +", line)
            data.vehicleNum = 3
            data.capacity = float(str[1])
        elif (count >= 9 and count <= 9 + customerNum):
            line = line[:-1]
            str = re.split(r" +", line)
            data.cor_X.append(float(str[2]))
            data.cor_Y.append(float(str[3]))
            data.demand.append(float(str[4]))
            data.readyTime.append(float(str[5]))
            data.dueTime.append(float(str[6]))
            data.serviceTime.append(float(str[7]))

    data.cor_X.append(data.cor_X[0])
    data.cor_Y.append(data.cor_Y[0])
    data.demand.append(data.demand[0])
    data.readyTime.append(data.readyTime[0])
    data.dueTime.append(data.dueTime[0])
    data.serviceTime.append(data.serviceTime[0])

    # compute the distance matrix
    data.disMatrix = [([0] * data.nodeNum) for p in range(data.nodeNum)]  # 初始化距离矩阵的维度,防止浅拷贝
    # data.disMatrix = [[0] * nodeNum] * nodeNum]; 这个是浅拷贝，容易重复
    for i in range(data.nodeNum):
        for j in range(data.nodeNum):
            temp = (data.cor_X[i] - data.cor_X[j]) ** 2 + (data.cor_Y[i] - data.cor_Y[j]) ** 2
            data.disMatrix[i][j] = math.sqrt(temp)
            temp = 0

    return data


def printData(data, customerNum):
    print("下面打印数据")
    for i in range(len(data.demand)):
        print('{0}\t{1}\t{2}\t{3}'.format(data.demand[i], data.readyTime[i], data.dueTime[i], data.serviceTime[i]))

    print("-------距离矩阵-------\n")
    for i in range(data.nodeNum):
        for j in range(data.nodeNum):
            # print("%d   %d" % (i, j))
            print("%6.2f" % (data.disMatrix[i][j]), end=" ")
        print()


class Solution:
    ObjVal = 0
    X = [[[]]]
    Y = [[[[]]]]
    C = [[]]
    Ct = [[[]]]
    Vl = [[[]]]
    Vr = [[[]]]
    route_Truck = []
    route_UAV = []

    def getSolution(self, data, model):
        solution = Solution()
        solution.ObjVal = model.ObjVal

        # X_ijk
        solution.X = [[([0] * data.vehicleNum) for j in range(data.nodeNum)] for i in range(data.nodeNum)]
        # Y_ijkd
        solution.Y = [[[[[] for d in range(data.droneNum)] for k in range(data.vehicleNum)]
                       for j in range(data.nodeNum)] for i in range(data.nodeNum)]
        # C_ik, C_ikd
        solution.C = [([0] * data.vehicleNum) for i in range(data.nodeNum)]
        solution.Ct = [[([0] * data.droneNum) for k in range(data.vehicleNum)] for i in range(data.nodeNum)]
        # Vl, Vr
        solution.Vl = [[([0] * data.droneNum) for k in range(data.vehicleNum)] for i in range(data.nodeNum)]
        solution.Vr = [[([0] * data.droneNum) for k in range(data.vehicleNum)] for i in range(data.nodeNum)]


        for m in model.getVars():
            str = re.split(r"_", m.VarName)
            if (str[0] == "X" and m.x == 1):
                solution.X[int(str[1])][int(str[2])][int(str[3])] = m.x
                print(str, end="")
                print(" = %d" % m.x)
            elif (str[0] == "Y" and m.x == 1):
                solution.Y[int(str[1])][int(str[2])][int(str[3])][int(str[4])] = m.x
                print(str, end="")
                print(" = %d" % m.x)
            elif (str[0] == "C" and m.x == 1):
                solution.C[int(str[1])][int(str[2])] = m.x
                print(str, end="")
                print(" = %d" % m.x)
            elif (str[0] == "Ct" and m.x == 1):
                solution.Ct[int(str[1])][int(str[2])][int(str[3])] = m.x
                print(str, end="")
                print(" = %d" % m.x)
            elif (str[0] == "Vl" and m.x == 1):
                solution.Vl[int(str[1])][int(str[2])][int(str[3])] = m.x
                print(str, end="")
                print(" = %d" % m.x)
            elif (str[0] == "Vr" and m.x == 1):
                solution.Vr[int(str[1])][int(str[2])][int(str[3])] = m.x
                print(str, end="")
                print(" = %d" % m.x)
            elif (str[0] == "z" and m.x > 0):
                solution.z = m.x
                print(str, end="")
                print(" = %d" % m.x)

        return solution


data = Data()
path = 'c101_1.txt'
customerNum = 9
readData(data, path, customerNum)
printData(data, customerNum)
# =========build the model===========
big_M = 10000
# construct the model object
model = Model("FSTSP")

# Initialize variables
# create variables: Muiti-dimension vector: from inner to outer
# X_ijk
X = [[[[] for k in range(data.vehicleNum)] for j in range(data.nodeNum)] for i in range(data.nodeNum)]

# Y_ijkd
Y = [[[[[]for d in range(data.droneNum)] for k in range(data.vehicleNum)] for j in range(data.nodeNum)] for i in range(data.nodeNum)]

# C_i(k), C_i'(d)
C = [[[] for k in range(data.vehicleNum)] for i in range(data.nodeNum)]
Ct = [[[[] for d in range(data.droneNum)] for k in range(data.vehicleNum)] for i in range(data.nodeNum)]

# vL(释放节点), vR(回收节点)
Vl = [[[[] for d in range(data.droneNum)] for k in range(data.vehicleNum)] for i in range(data.nodeNum)]
Vr = [[[[] for d in range(data.droneNum)] for k in range(data.vehicleNum)] for i in range(data.nodeNum)]

# Pkd
P = [[[] for d in range(data.droneNum)] for k in range(data.vehicleNum)]

# A_ik, a_ikd (卡车无人车到达i的时间)
A = [[[] for k in range(data.vehicleNum)] for i in range(data.nodeNum)]
a = [[[[] for d in range(data.droneNum)] for k in range(data.vehicleNum)] for i in range(data.nodeNum)]

# R_ik, r_ikd (卡车无人车到达i的时间)
R = [[[] for k in range(data.vehicleNum)] for i in range(data.nodeNum)]
r = [[[[] for d in range(data.droneNum)] for k in range(data.vehicleNum)] for i in range(data.nodeNum)]

# z
z: float

# D'
Dk = [[[[] for d in range(data.droneNum)] for k in range(data.vehicleNum)] for i in range(data.nodeNum)]
temp = [[[[] for d in range(data.droneNum)] for k in range(data.vehicleNum)] for i in range(data.nodeNum)]
temp_1 = [[[[] for d in range(data.droneNum)] for k in range(data.vehicleNum)] for i in range(data.nodeNum)]
temp_2 = [[[[] for d in range(data.droneNum)] for k in range(data.vehicleNum)] for i in range(data.nodeNum)]

for k in range(data.vehicleNum):
    for d in range(data.droneNum):
        name1 = 'P_' + str(k) + '_' + str(d)
        P[k][d] = model.addVar(0, 1, vtype=GRB.BINARY, name=name1)
        for i in range(data.nodeNum):
            name2 = 'C_' + str(i) + '_' + str(k)
            name3 = 'Ct_' + str(i) + '_' + str(k) + '_' + str(d)
            name4 = 'Vl_' + str(i) + '_' + str(k) + '_' + str(d)
            name5 = 'Vr_' + str(i) + '_' + str(k) + '_' + str(d)
            name10 = 'A_' + str(i) + '_' + str(k)
            name11 = 'a_' + str(i) + '_' + str(k) + '_' + str(d)
            name12 = 'R_' + str(i) + '_' + str(k)
            name13 = 'r_' + str(i) + '_' + str(k) + '_' + str(d)
            name16 = 'Dk_' + str(i) + '_' + str(k) + '_' + str(d)
            name17 = 'temp_' + str(i) + '_' + str(k) + '_' + str(d)
            name18 = 'temp_1_' + str(i) + '_' + str(k) + '_' + str(d)
            name19 = 'temp_2_' + str(i) + '_' + str(k) + '_' + str(d)
            C[i][k] = model.addVar(0, 1, vtype=GRB.BINARY, name=name2)
            Ct[i][k][d] = model.addVar(0, 1, vtype=GRB.BINARY, name=name3)
            Vl[i][k][d] = model.addVar(0, 1, vtype=GRB.BINARY, name=name4)
            Vr[i][k][d] = model.addVar(0, 1, vtype=GRB.BINARY, name=name5)
            A[i][k] = model.addVar(0, big_M, vtype=GRB.CONTINUOUS, name=name10)
            a[i][k][d] = model.addVar(0, big_M, vtype=GRB.CONTINUOUS, name=name11)
            R[i][k] = model.addVar(0, big_M, vtype=GRB.CONTINUOUS, name=name12)
            r[i][k][d] = model.addVar(0, big_M, vtype=GRB.CONTINUOUS, name=name13)
            Dk[i][k][d] = model.addVar(0, big_M, vtype=GRB.CONTINUOUS, name=name16)
            temp[i][k][d] = model.addVar(0, big_M, vtype=GRB.CONTINUOUS, name=name17)
            temp_1[i][k][d] = model.addVar(0, big_M, vtype=GRB.CONTINUOUS, name=name18)
            temp_2[i][k][d] = model.addVar(0, big_M, vtype=GRB.CONTINUOUS, name=name19)
            for j in range(data.nodeNum):
                name6 = 'X_' + str(i) + '_' + str(j) + '_' + str(k)
                name7 = 'Y_' + str(i) + '_' + str(j) + '_' + str(k) + '_' + str(d)
                X[i][j][k] = model.addVar(0, 1, vtype=GRB.BINARY, name=name6)
                Y[i][j][k][d] = model.addVar(0, 1, vtype=GRB.BINARY, name=name7)

model.update()
z = model.addVar(0, big_M, vtype=GRB.CONTINUOUS, name='z')
b = model.addVar(0, 1, vtype=GRB.BINARY, name="b")
eps = 0.0001
M = 10 + eps

# constraint (1.2)
# for i in range(1, 6):
#     for j in range(6, 10):
#         for k in range(data.vehicleNum):
#             for d in range(data.droneNum):
#                 if(i!=j):
#                     model.addConstr(a[i][k][d] == (A[i][k] + data.W + data.disMatrix[i][j]) * P[k][d], name='1.2')

# create the objective expression(1.3)
for k in range(data.vehicleNum):
    expr5 = LinExpr(0)
    expr6 = LinExpr(0)
    for i in range(data.nodeNum):
        for j in range(data.nodeNum):
            if (i != j):
                expr5.addTerms(1, X[i][j][k])

    expr1 = LinExpr(0)
    expr2 = LinExpr(0)
    for l in range(1, data.nodeNum):
        if (i != j):
            expr1.addTerms(1, C[l][k])

    expr3 = LinExpr(0)
    expr4 = LinExpr(0)
    for d in range(data.droneNum):
        for i in range(1, 6):
            expr2.addTerms(1, Vr[i][k][d])
        for j in range(0, 5):
            expr3.addTerms(1, Vl[j][k][d])

    for i in range(data.nodeNum):
        for n in range(data.droneNum):
            # 建模如果 A_ik > a_ikm, 则 b = 1，否则 b = 0
            model.addConstr(temp[i][k][n] == a[i][k][n] - (A[i][k] + data.serviceTime[i]), name='1.3_1')
            model.addConstr(temp_1[i][k][n] == max_(temp[i][k][n], constant=0), name='1.3_2')
            model.addConstr(A[i][k] >= a[i][k][n] + eps - M * (1 - b), name='1.3_3')
            model.addConstr(A[i][k] <= a[i][k][n] + M * b, name='1.3_4')
            model.addConstr((b == 1) >> (Dk[i][k][n] == data.W), name='1.3_5')
            model.addConstr((b == 0) >> (Dk[i][k][n] == temp_1[i][k][n] + data.W), name='1.3_6')

    model.addConstr(z >= expr5 * data.disMatrix[i][j] + expr1 * data.serviceTime[l] + expr2 * Dk[i][k][n] + expr3 * data.w, name='objective')
    expr1.clear()
    expr2.clear()
    expr3.clear()
    expr4.clear()
    expr5.clear()
    expr6.clear()

model.setObjective(z, GRB.MINIMIZE)

# constraint (1.4)
for k in range(data.vehicleNum):
    expr1 = LinExpr(0)
    expr2 = LinExpr(0)
    for j in range(1, data.nodeNum):
        expr1.addTerms(1, X[0][j][k])
    for i in range(0, data.nodeNum - 1):
        expr2.addTerms(1, X[i][0][k])
    model.addConstr(expr1 == expr2, "c1.4")
    expr1.clear()
    expr2.clear()

for k in range(data.vehicleNum):
    expr = LinExpr(0)
    for i in range(1, 6):
        expr.addTerms(1, X[i][0][k])
    model.addConstr(expr == 1, "c1.4_1")
    expr.clear()

# constraint (1.5)
for i in range(1, data.nodeNum - 1):
    expr1 = LinExpr(0)
    expr2 = LinExpr(0)
    for k in range(data.vehicleNum):
        expr1.addTerms(1, C[i][k])
        for d in range(data.droneNum):
            expr2.addTerms(1, Ct[i][k][d])

    model.addConstr(expr1 + expr2 == 1, "c1.5")
    expr1.clear()
    expr2.clear()

for i in range(1, 6):
    expr = LinExpr(0)
    for k in range(data.vehicleNum):
        expr.addTerms(1, C[i][k])

    model.addConstr(expr == 1, "c1.5_1")
    expr.clear()

for i in range(6, 10):
    expr = LinExpr(0)
    for k in range(data.vehicleNum):
        for d in range(data.droneNum):
            expr.addTerms(1, Ct[i][k][d])

    model.addConstr(expr == 1, "c1.5_2")
    expr.clear()

# constraint (1.6)
for k in range(data.vehicleNum):
    for j in range(1, 6):  # j∈Ct, 非隔离区节点集合
        expr1 = LinExpr(0)
        expr2 = LinExpr(0)
        for i in range(0, data.nodeNum - 1):
            if(i!=j):
                expr1.addTerms(1, X[i][j][k])
        for l in range(1, data.nodeNum):
            if(l!=i):
                expr2.addTerms(1, X[j][l][k])

        model.addConstr(expr1 == expr2, "c1.6")
        expr1.clear()
        expr2.clear()

# constraint (1.7)
for k in range(data.vehicleNum):
    for d in range(data.droneNum):
        for j in range(6, 10):
            expr1 = LinExpr(0)
            expr2 = LinExpr(0)
            for i in range(6, 10):
                if(i!=j):
                    expr1.addTerms(1, Y[i][j][k][d])
                    expr2.addTerms(1, Y[j][i][k][d])

            model.addConstr(expr1 == expr2, "c1.7")
            expr1.clear()
            expr2.clear()

# constraint (1.8)
for k in range(data.vehicleNum):
    for d in range(data.droneNum):
        expr1 = LinExpr(0)
        expr2 = LinExpr(0)
        for i in range(0, 5):
            expr1.addTerms(1, Vl[i][k][d])
        for j in range(1, 6):
            expr2.addTerms(1, Vr[j][k][d])

        model.addConstr(expr1 == expr2, "c1.8")
        model.addConstr(expr1 <= 1, "c1.8_1")
        expr1.clear()
        expr2.clear()


# constraint (1.9)
for k in range(data.vehicleNum):
    for j in range(1, 6):
        expr = LinExpr(0)
        for i in range(data.nodeNum - 1):
            if(i!=j):
                expr.addTerms(1, X[i][j][k])

        model.addConstr(C[j][k] * (expr - 1) == 0, "c1.9")
        expr.clear()

# constraint (1.10)
for k in range(data.vehicleNum):
    for j in range(1, 6):
        expr = LinExpr(0)
        for i in range(data.nodeNum - 1):
            if (i != j):
                expr.addTerms(1, X[j][i][k])

        model.addConstr(C[j][k] * (expr - 1) == 0, "c1.10")
        expr.clear()

# constraint (1.11)
for d in range(data.droneNum):
    for j in range(6, 10):
        for k in range(data.vehicleNum):
            expr = LinExpr(0)
            for i in range(data.nodeNum - 1):
                if (i != j):
                    expr.addTerms(1, Y[i][j][k][d])

            model.addConstr(Ct[j][k][d] * (expr - 1) == 0, "c1.11")
            expr.clear()

# constraint (1.12)
for d in range(data.droneNum):
    for j in range(6, 10):
        for k in range(data.vehicleNum):
            expr = LinExpr(0)
            for i in range(data.nodeNum - 1):
                if (i != j):
                    expr.addTerms(1, Y[j][i][k][d])

            model.addConstr(Ct[j][k][d] * (expr - 1) == 0, "c1.12")
            expr.clear()

# constraint (1.13)
for d in range(data.droneNum):
    for k in range(data.vehicleNum):
        for i in range(1, 6):  # Vl
            expr = LinExpr(0)
            for j in range(6, 10):  # Cd
                if (i != j):
                    expr.addTerms(1, Y[i][j][k][d])

            model.addConstr(expr == Vl[i][k][d], "c1.13")
            expr.clear()

# constraint (1.14)
for d in range(data.droneNum):
    for k in range(data.vehicleNum):
        for i in range(1, 6):  # Vr
            expr = LinExpr(0)
            for j in range(6, 10):  # Cd
                if (i != j):
                    expr.addTerms(1, Y[j][i][k][d])

            model.addConstr(expr == Vr[i][k][d], "c1.14")
            expr.clear()

# constraint (1.15)
for k in range(data.vehicleNum):
    for d in range(data.droneNum):
        for i in range(1, 6):  # Vl
            expr = LinExpr(0)
            for j in range(data.nodeNum - 1):
                if (i != j):
                    expr.addTerms(1, X[j][i][k])

            model.addConstr(expr >= P[k][d] * Vl[i][k][d], "c1.15")
            expr.clear()

# constraint (1.16)
for k in range(data.vehicleNum):
    for d in range(data.droneNum):
        for i in range(1, 6):  # Vr
            expr = LinExpr(0)
            for j in range(data.nodeNum - 1):
                if (i != j):
                    expr.addTerms(1, X[j][i][k])

            model.addConstr(expr >= P[k][d] * Vr[i][k][d], "c1.16")
            expr.clear()

# constraint (1.17)
for k in range(data.vehicleNum):
    for d in range(data.droneNum):
        for i in range(1, 6):
            for j in range(1, 6):
                for p in range(data.nodeNum - 1):
                    if(i != j):
                        model.addConstr(temp_2[p][k][d] == Vl[i][k][d] * Vr[j][k][d], name="c1.17")
                        model.addConstr(temp_2[p][k][d] >= 0 + eps - M * (1 - b), name="c1.17_1")
                        model.addConstr((b == 1) >> (A[j][k] - A[i][k] >= 0), name='c1.17_2')

# constraint (1.18)
for i in range(1, 6):
    for k in range(data.vehicleNum):
        for d in range(data.droneNum):
            model.addConstr(temp[i][k][d] == a[i][k][d] - (A[i][k] + data.serviceTime[i]), name='1.18_1')
            model.addConstr(temp_1[i][k][d] == max_(temp[i][k][d], constant=0), name='1.18_2')
            model.addConstr(A[i][k] >= a[i][k][d] + eps - M * (1 - b), name="conStr1")
            model.addConstr(A[i][k] <= a[i][k][d] + M * b, name="conStr2")
            model.addConstr((b == 0) >> (r[i][k][d] == A[i][k] + temp_1[i][k][d] + data.W), name="conStr3")
            model.addConstr((b == 1) >> (r[i][k][d] == A[i][k] + data.W), name="conStr4")

# constraint (1.19)
for k in range(data.vehicleNum):
    for d in range(data.droneNum):
        for i in range(data.nodeNum - 1):
            for j in range(data.nodeNum - 1):
                if (i != j):
                    model.addConstr(a[j][k][d] - a[i][k][d] >= data.serviceTime[i] + data.disMatrix[i][j] - big_M + big_M * Y[i][j][k][d], "c1.19")


# constraint (1.20)
for k in range(data.vehicleNum):
    for i in range(data.nodeNum - 1):
        for j in range(data.nodeNum - 1):
            if(i != j):
                model.addConstr(A[j][k] - A[i][k] >= data.serviceTime[i] + data.disMatrix[i][j] - big_M + big_M * X[i][j][k], "c1.20")

# constraint (1.21)
for i in range(data.vehicleNum):
    expr = LinExpr(0)
    for j in range(data.droneNum):
        expr.addTerms(1, P[i][j])

    model.addConstr(expr <= data.capacity, "c1.21")
    expr.clear()

# constraint (1.22)
for k in range(data.vehicleNum):
    for d in range(data.droneNum):
        expr = LinExpr(0)
        for i in range(1, data.nodeNum - 1):
            expr.addTerms(1, Ct[i][k][d])

        model.addConstr(30 * expr <= data.capacity_1, "c1.22")
        expr.clear()

# =========solve the model===========
model.write('a.lp')
model.Params.timelimit = 3600

# get the solution info
solution = Solution()
solution = solution.getSolution(data, model)
print("\n-----optimal value-----")
print("Obj: %g" % solution.ObjVal)