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Write_MST_Gurobi.py
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Write_MST_Gurobi.py
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# -*- coding: utf-8 -*-
"""
Created on Thu May 9 16:12:39 2019
@author: catar
"""
from __future__ import print_function
from scipy.io import loadmat
from connect_ifttt import email_alert
import numpy as np
import cplex
import socket
def Write_MST_Gurobi(casename):
global debug
debug = False
data = loadmat(casename)
S1 = data['Seq_Retirada']
C = data['C'][0][0]
R = data['R'][0][0]
Seq_Navio_Inv = data['Seq_Navio_Inv'].tolist()[0]
Seq_Navio_Id_Inv = data['Seq_Navio_Id_Inv'].tolist()[0]
Patios = data['patio'].tolist()
q_o = data['q_o'].tolist()
q_d = data['q_d'].tolist()
q_r = data['q_r'].tolist()
q_c = data['q_c'].tolist()
w_o = data['w_o'].tolist()
w_d = data['w_d'].tolist()
w_a = data['w_a'].tolist()
w_r = data['w_r'].tolist()
w_c = data['w_c'].tolist()
phi = data['phi'].tolist()
Npatios = len(Patios)
P=Npatios+1 # numero de portos
for o in range(Npatios):
for d in range(P):
if phi[o][d].shape[1] != 0 :
phi[o][d] = phi[o][d].tolist()[0]
else:
phi[o][d] = []
omega=[ [] for i in range(Npatios) ] # omega = conjunto dos indices dos conteineres em cada patio
S = []
for i in range(Npatios):
Patios[i]=Patios[i][0]
omega[i]=np.extract(Patios[i]!= 0 , Patios[i]).tolist()
S.append(S1[0][i].tolist()[0])
N=[ 0 for i in range(Npatios) ] # N = quantidade de conteineres em cada patio
for i in range(Npatios):
N[i]=np.count_nonzero(Patios[i])
T=N
H=[] # H = numero de linhas de cada patio
for i in range(Npatios):
H.append(Patios[i].shape[0])
W= [] # W = numero de colunas de cada patio
for i in range(Npatios):
W.append(Patios[i].shape[1])
print('parametros criados')
model = cplex.Cplex()
start_time = model.get_time()
model.objective.set_sense(model.objective.sense.minimize)
startVar=[]
startVal=[]
#------------------------------------------------------------#
#-------------------- Variaveis ---------------------------#
#------------------------------------------------------------#
nvar = 0
model,nvar,startVar,startVal = variavel_v(model,S,N,T,nvar,omega,startVar,startVal)
model,nvar,startVar,startVal = variavel_q(model,N,R,C,nvar,q_o,q_d,q_r,q_c,startVar,startVal)
model,nvar,startVar,startVal = variavel_u(model,N,R,C,nvar,Seq_Navio_Inv,startVar,startVal)
model,nvar,startVar,startVal = variavel_w(model,N,R,C,nvar,w_o,w_d,w_a,w_r,w_c,startVar,startVal)
model,nvar,startVar,startVal = variavel_z(model,omega,N,T,R,C,S,Seq_Navio_Id_Inv,nvar,startVar,startVal)
model,nvar,startVar,startVal = variavel_y(model,omega,Patios,S,N,H,W,T,nvar,startVar,startVal)
model,nvar,startVar,startVal = variavel_b(model,omega,Patios,S,N,H,W,T,nvar,startVar,startVal)
model,nvar,startVar,startVal = variavel_x(model,omega,N,H,W,T,nvar,startVar,startVal)
print('variaveis criadas')
solucao_inicial_gurobi_mst = casename + '.mst'
out_file = open(solucao_inicial_gurobi_mst,'w+')
out_file.write("# MIP start \n")
for Var,Val in zip(startVar,startVal):
out_file.write(str(Var)+" "+str(int(Val)) + "\n")
out_file.close()
#------------------------------------------------------------#
#-------------------- Variaveis ---------------------------#
#------------------------------------------------------------#
def variavel_v(model,S,N,T,nvar,omega,startVar,startVal):
global vind
vind = dict()
indx = nvar
vnames = []
val =[]
for o in range(len(N)):
for n in omega[o]:
flag = False
for t in range(1,T[o]+1):
# if debug:
vnames.append('v_'+str(n)+'_'+str(t))
vind[(n, t)] = indx
indx += 1
val.append(0.0)
if S[o][t-1] == n or flag == True :
if flag == False:
flag = True
continue
else:
val[-1]= 1.0
flag = True
nv = len(vnames)
#nv= indx-nvar
nvar += nv
lb = [0.0]*nv
ub = [1.0]*nv
ctypes =[model.variables.type.binary]*nv
model.variables.add(obj=[], lb=lb, ub=ub, types=ctypes,names=vnames)
#startVar+=list(range(nvar-nv,nvar))
startVar+=vnames
startVal+=val
# model.MIP_starts.add(cplex.SparsePair(ind = vnames, val = val), model.MIP_starts.effort_level.repair, "first")
return model,nvar,startVar,startVal
#------------------------------------------------------------------------------------------------------------------#
#------------------------------------------------------------------------------------------------------------------#
def variavel_q(model,N,R,C,nvar,q_o,q_d,q_r,q_c,startVar,startVal):
qqnames = []
global qind
qind = dict()
indx = nvar
Y=np.size(q_o)
for o in range(Y):
qqnames.append('q_'+str(q_o[0][o])+'_'+str(q_d[0][o])+'_'+str(q_r[0][o])+'_'+str(q_c[0][o]))
qnames = []
val =[]
for o in range(1,len(N)+1):
for d in range(o+1,len(N)+2):
for r in range(1,R+1):
for c in range(1,C+1):
qind[(o,d, r, c)] = indx
indx += 1
if 'q_'+str(o)+'_'+str(d)+'_'+str(r)+'_'+str(c) in qqnames :
qnames.append('q_'+str(o)+'_'+str(d)+'_'+str(r)+'_'+str(c))
val.append(1.0)
else:
qnames.append('q_'+str(o)+'_'+str(d)+'_'+str(r)+'_'+str(c))
val.append(0.0)
nq = len(qnames)
nvar += nq
lb = [0.0]*nq
ub = [1.0]*nq
ctypes =[model.variables.type.binary]*nq
model.variables.add(obj=[], lb=lb, ub=ub, types=ctypes,names=qnames)
#startVar+=list(range(nvar-nq,nvar))
startVar+=qnames
startVal+=val
# model.MIP_starts.add(cplex.SparsePair(ind = qnames, val = val), model.MIP_starts.effort_level.repair, "first")
return model,nvar,startVar,startVal
#------------------------------------------------------------------------------------------------------------------#
#------------------------------------------------------------------------------------------------------------------#
def variavel_u(model,N,R,C,nvar,Seq_Navio_Inv,startVar,startVal):
unames = []
val =[]
global uind
uind = dict()
indx = nvar
for o in range(1,len(N)+1):
for r in range(1,R+1):
for c in range(1,C+1):
unames.append('u_'+str(o)+'_'+str(r)+'_'+str(c))
uind[(o, r, c)] = indx
indx += 1
if Seq_Navio_Inv[o-1][r-1,c-1] == 0:
val.append(0.0)
else:
val.append(1.0)
nu = len(unames)
nvar += nu
lb = [0.0]*nu
ub = [1.0]*nu
ctypes =[model.variables.type.binary]*nu
model.variables.add(obj=[], lb=lb, ub=ub, types=ctypes,names=unames)
#startVar+=list(range(nvar-nu,nvar))
startVar+=unames
startVal+=val
#model.MIP_starts.add(cplex.SparsePair(ind = unames, val = val), model.MIP_starts.effort_level.repair, "first")
return model,nvar,startVar,startVal
#------------------------------------------------------------------------------------------------------------------#
#------------------------------------------------------------------------------------------------------------------#
def variavel_w(model,N,R,C,nvar,w_o,w_d,w_a,w_r,w_c,startVar,startVal):
wnames = []
global wind
wind = dict()
indx = nvar
obj = []
val=[]
wwnames = []
Y=np.size(w_o)
for o in range(Y):
wwnames.append('w_'+str(w_o[0][o])+'_'+str(w_d[0][o])+'_'+str(w_a[0][o])+'_'+str(w_r[0][o])+'_'+str(w_c[0][o]))
for o in range(1,len(N)+1):
for d in range(o+1,len(N)+2):
for a in range(o+1,d+1):
for r in range(1,R+1):
for c in range(1,C+1):
wind[(o, d,a, r, c)] = indx
indx += 1
if 'w_'+str(o)+'_'+str(d)+'_'+str(a)+'_'+str(r)+'_'+str(c) in wwnames :
wnames.append('w_'+str(o)+'_'+str(d)+'_'+str(a)+'_'+str(r)+'_'+str(c))
val.append(1.0)
else:
wnames.append('w_'+str(o)+'_'+str(d)+'_'+str(a)+'_'+str(r)+'_'+str(c))
val.append(0.0)
if a == d:
obj.append(0.0)
else:
obj.append(1.0)
nw = len(wnames)
nvar += nw
lb = [0.0]*nw
ub = [1.0]*nw
ctypes =[model.variables.type.binary]*nw
model.variables.add(obj=obj, lb=lb, ub=ub, types=ctypes,names=wnames)
#startVar+=list(range(nvar-nw,nvar))
startVar+=wnames
startVal+=val
# model.MIP_starts.add(cplex.SparsePair(ind = wnames, val = val), model.MIP_starts.effort_level.repair, "first")
return model,nvar,startVar,startVal
#------------------------------------------------------------------------------------------------------------------#
#------------------------------------------------------------------------------------------------------------------#
def variavel_z(model,omega,N,T,R,C,S,Seq_Navio_Id_Inv,nvar,startVar,startVal):
znames = []
val=[]
global zind
zind = dict()
indx = nvar
for o in range(len(N)):
for n in omega[o]:
flag = 0
for t in range(1,T[o]+1):
for r in range(1,R+1):
for c in range(1,C+1):
znames.append('z_'+str(n)+'_'+str(t)+'_'+str(r)+'_'+str(c))
zind[( n, t,r,c)] = indx
indx += 1
# if t==16 and r==1 and c==1:
# print('z_'+str(n)+'_'+str(t)+'_'+str(r)+'_'+str(c))
if Seq_Navio_Id_Inv[o][r-1,c-1] == n and S[o][t-1] == n:
val.append(1.0)
flag=1
row=r
col=c
continue
else:
val.append(0.0)
if flag == 1 and row == r and col == c:
val[-1]= 1.0
nz = len(znames)
nvar += nz
lb = [0.0]*nz
ub = [1.0]*nz
ctypes =[model.variables.type.binary]*nz
model.variables.add(obj=[], lb=lb, ub=ub, types=ctypes,names=znames)
#startVar+=list(range(nvar-nz,nvar))
startVar+=znames
startVal+=val
# model.MIP_starts.add(cplex.SparsePair(ind = znames, val = val), model.MIP_starts.effort_level.repair, "first")
return model,nvar,startVar,startVal
#------------------------------------------------------------------------------------------------------------------#
#------------------------------------------------------------------------------------------------------------------#
def variavel_y(model,omega,Patios,S,N,H,W,T,nvar,startVar,startVal):
yynames = []
val=[]
global yind
yind = dict()
indx = nvar
for o in range(len(N)): #para cada patio
for t in range(1,T[o]): #para cada tempo que sai um conteiner n
contador = H[o]+1
for j in range(1,H[o]+1): #percorrer as linhas do patio
contador = contador - 1
for i in range(1,W[o]+1): #percorrer as colunas do patio
if Patios[o][j-1,i-1]==S[o][t-1]:
n=S[o][t-1]
yynames.append('y_'+str(i)+'_'+str(contador)+'_'+str(n)+'_'+str(t))
continue
ynames = []
for o in range(len(N)):
for i in range(1,W[o]+1):
for j in range(1,H[o]+1):
for n in omega[o]:
for t in range(1,T[o]+1):
yind[(i,j,n, t)] = indx
indx += 1
if 'y_'+str(i)+'_'+str(j)+'_'+str(n)+'_'+str(t) in yynames:
ynames.append('y_'+str(i)+'_'+str(j)+'_'+str(n)+'_'+str(t))
val.append(1.0)
else:
ynames.append('y_'+str(i)+'_'+str(j)+'_'+str(n)+'_'+str(t))
val.append(0.0)
ny = len(ynames)
nvar += ny
lb = [0.0]*ny
ub = [1.0]*ny
ctypes =[model.variables.type.binary]*ny
model.variables.add(obj=[], lb=lb, ub=ub, types=ctypes,names=ynames)
#startVar+=list(range(nvar-ny,nvar))
startVar+=ynames
startVal+=val
# model.MIP_starts.add(cplex.SparsePair(ind = ynames, val = val), model.MIP_starts.effort_level.repair, "first")
return model,nvar,startVar,startVal
#------------------------------------------------------------------------------------------------------------------#
#------------------------------------------------------------------------------------------------------------------#
def variavel_b(model,omega,Patios,S,N,H,W,T,nvar,startVar,startVal):
bnames = []
val=[]
global bind
bind = dict()
indx = nvar
flag=0
for o in range(len(N)):
for i in range(1,W[o]+1):
contador = H[o]+1
for j in range(1,H[o]+1):
contador = contador - 1
for n in omega[o]:
flag = 1
for t in range(1,T[o]+1):
bnames.append('b_'+str(i)+'_'+str(contador)+'_'+str(n)+'_'+str(t))
bind[(i, contador, n, t)] = indx
indx += 1
val.append(0.0)
if Patios[o][j-1,i-1]==n and flag == 1: # se o conteiner n eh o que esta na posicao (i,j), entao b_ijnt=1
val[-1]= 1.0
if Patios[o][j-1,i-1]==S[o][t-1]: # se chegamos no tempo t em que o conteiner n sai, nos proximos tempos b_ijnt deve ser igual a 0
flag = 0
nb = len(bnames)
nvar += nb
lb = [0.0]*nb
ub = [1.0]*nb
ctypes =[model.variables.type.binary]*nb
model.variables.add(obj=[], lb=lb, ub=ub, types=ctypes,names=bnames)
# startVar+=list(range(nvar-nb,nvar))
startVar+=bnames
startVal+=val
# model.MIP_starts.add(cplex.SparsePair(ind = bnames, val = val), model.MIP_starts.effort_level.repair, "first")
return model,nvar,startVar,startVal
#------------------------------------------------------------------------------------------------------------------#
#------------------------------------------------------------------------------------------------------------------#
def variavel_x(model,omega,N,H,W,T,nvar,startVar,startVal):
xnames = []
val=[]
global xind
xind = dict()
indx = nvar
for o in range(len(N)):
for i in range(1,W[o]+1):
for j in range(1,H[o]+1):
for k in range(1,W[o]+1):
for l in range(1,H[o]+1):
for n in omega[o]:
for t in range(1,T[o]+1):
xnames.append('x_'+str(i)+'_'+str(j)+'_'+str(k)+'_'+str(l)+'_'+str(n)+'_'+str(t))
val.append(0.0)
xind[(i,j,k,l,n,t)] = indx
indx +=1
nx = len(xnames)
nvar += nx
lb = [0.0]*nx
ub = [1.0]*nx
ctypes =[model.variables.type.binary]*nx
obj = [1.0]*nx
model.variables.add(obj=obj, lb=lb, ub=ub, types=ctypes,names=xnames)
#startVar+=list(range(nvar-nx,nvar))
startVar+=xnames
startVal+=val
#model.MIP_starts.add(cplex.SparsePair(ind = xnames, val = val), model.MIP_starts.effort_level.repair, "first")
return model,nvar,startVar,startVal
#------------------------------------------------------------------------------------------------------------------#
# FIM
#------------------------------------------------------------------------------------------------------------------#
if __name__ == "__main__":
# i=1
# for n in range(2):
# if n==3 or n==4 or n==7 or n==8 or n==10 or n==11 or n==12:
# name_instance = 'SolucaoInicial_Aleatoria_Instancia_' + str(i)
# print(name_instance)
# _ = Write_MST_Gurobi(name_instance)
# i = i+1
# else:
# name_instance = 'SolucaoInicial_Instancia_' + str(i)
# print(name_instance)
# _ = Write_MST_Gurobi(name_instance)
# i = i+1
_ = Write_MST_Gurobi('SolucaoInicial_InstanciaIntegradaTeste3.mat')
# i=1
# for n in range(12):
# if n==3 or n==4 or n==7 or n==8 or n==10 or n==11 or n==12:
# name_instance = 'SolucaoInicial_Aleatoria_Instancia_' + str(i)
# print(name_instance)
# _ = Write_MST_Gurobi(name_instance)
# i = i+1
# else:
# name_instance = 'SolucaoInicial_Instancia_' + str(i)
# print(name_instance)
# _ = Write_MST_Gurobi(name_instance)
# i = i+1
#
# i=1
# for t in range(12):
# if t==7:
# name_instance = 'SolucaoInicial_Aleatoria_Instancia_' + str(i) + '_1'
# print(name_instance)
# _ = Write_MST_Gurobi(name_instance)
# i = i+1
# else:
# name_instance = 'SolucaoInicial_Instancia_' + str(i)
# print(name_instance)
# _ = Write_MST_Gurobi(name_instance)
# i = i+1