Julia Discourse (53970)

using DataFrames
using OrderedCollections
using JuMP

H = 8;
d = 0;
N = 4;

#Sets
#  i 'tasks' /t1*t5/
#  j 'units' /j1*j5/
#  n 'events' /n0*n3/
#  s 'states' /s1*s4/

i = ["t1","t2","t3","t4","t5"];
j = ["j1","j2","j3","j4","j5"];
n = [1:N]
s = ["s1","s2","s3","s4"]

#SubSets

#Ij1(i) 'tasks which can be performed in unit 1' /task1/
#Ij2(i) 'tasks which can be performed in unit 2' /task2/
#Ij3(i) 'tasks which can be performed in unit 3' /task3/
#Ij4(i) 'tasks which can be performed in unit 4' /task4/
#Ij5(i) 'tasks which can be performed in unit 5' /task5/

Ij1 = i[1];
Ij2 = i[2];
Ij3 = i[3];
Ij4 = i[4];
Ij5 = i[5];

#Is1(i)'tasks which process state 1 and either produce or consume' /task1,task2/
#Is2(i)'tasks which process state 2 and either produce or consume' /task1,task2,task3/
#Is3(i)'tasks which process state 3 and either produce or consume' /task3,task4,task5/
#Is4(i)'tasks which process state 4 and either produce or consume' /task4,task5/

Is1 = i[1:2];
Is2 = i[1:3];
Is3 = i[3:5];
Is4 = i[4:5];

#Ips1(i) 'tasks which produce state 2' //
#Ips2(i) 'tasks which produce state 2' /task1,task2/
#Ips3(i) 'tasks which produce state 3' /task3/
#Ips4(i) 'tasks which produce state 4' /task4,task5/

Ips1 = [];
Ips2 = i[1:2];
Ips3 = i[3];
Ips4 = i[4:5];

#Ics1(i) 'tasks which consume state 1' /task1,task2/
#Ics2(i) 'tasks which consume state 2' /task3/
#Ics3(i) 'tasks which consume state 3' /task4,task5/
#Ics4(i) 'tasks which consume state 4' //

Ics1 = i[1:2];
Ics2 = i[3];
Ics3 = i[4:5];
Ics4 = [];

Sr =s[1]
Sfis = s[2:3]
Sp = s[4]

#alias(i,ip)
#alias(j,jp)
#alias(n,np,npp)

ip = i;
jp = j;
np = n;
npp = n;

#PARAMETERS
#bmin = [0,0,0,0,0]

bmin = OrderedDict(
   "t1" => 0,
   "t2" => 0,
   "t3" => 0,
   "t4" => 0,
   "t5" => 0
)

#bmax = [100,150,200,150,150]
bmax = OrderedDict(
   "t1" => 100,
   "t2" => 150,
   "t3" => 200,
   "t4" => 150,
   "t5" => 150
)

#STin = [10000, 0, 0, 0]
STin = OrderedDict(
     "s1" => 10000,
     "s2" => 0,
     "s3" => 0,
     "s4" => 0)

#STmax = [+inf, 200, 250, +inf ]
STmax = OrderedDict(
     "s1" => Inf,
     "s2" => 200,
     "s3" => 250,
     "s4" => 0
)

#alpha = [1.333, 1.333, 1.000, 0.667, 0.667]
alpha = OrderedDict(
"t1" => 1.333,
"t2" => 1.333,
"t3" => 1.000,
"t4" => 0.667,
"t5" => 0.667
)

#beta = [0.01333, 0.01333, 0.00500, 0.00445, 0.00445]
beta = OrderedDict(
"t1" => 0.01333,
"t2" => 0.01333,
"t3" => 0.00500,
"t4" => 0.00445,
"t5" => 0.00445
)

price = OrderedDict(
"s1" => 0,
"s2" => 0,
"s3" => 0,
"s4" => 5
)

demand = OrderedDict(
"s1" => 0,
"s2" => 0,
"s3" => 0,
"s4" => 0
)

#rho_table = wsv"""
#i        s1       s2     s3    s4
#t1       -1       +1      0     0
#t2       -1       +1      0     0
#t3        0       -1     +1     0
#t4        0        0     -1    +1
#t5        0        0     -1    +1
#"""

rho_table = DataFrame([(i = "t1", s1 = -1, s2 = +1, s3 = 0, s4 = 0 ),
                   (i = "t2", s1 = -1, s2 = +1, s3 = 0, s4 = 0 ),
                   (i = "t3", s1 = 0, s2 = -1, s3 = +1, s4 = 0 ),
                   (i = "t4", s1 = 0, s2 = 0, s3 = -1, s4 = +1 ),
                   (i = "t5", s1 = 0, s2 = 0, s3 = -1, s4 = +1 )]);

rho = OrderedDict( (r[:i],states) => r[Symbol(states)] for r in eachrow(rho_table), states in s);

example2_netprofit = Model()

@variables example2_netprofit begin
    w[i in i, n in n, np in np], Bin
    bs[i in i, n in n, np in np] >= 0
    ST0[s in s, n in n] >= 0
    ST[s in s, n in n] >= 0
    Ts[i in i, n in n] >= 0
    Tf[i in i,n in n] >= 0
    NetP
    MS
end

@constraints example2_netprofit begin
    tight1[j in j],
      sum(sum( (alpha[i]*w[i,n,np] + beta[i]*bs[i,n,np] ) for n in 1:length(n) if n <= np <= n+d) for i in Ij1) <= H

    tight2[j in j],
      sum(sum( (alpha[i]*w[i,n,np] + beta[i]*bs[i,n,np] ) for n in 1:length(n) if n <= np <= n+d) for i in Ij2) <= H

    tight3[j in j],
      sum(sum( (alpha[i]*w[i,n,np] + beta[i]*bs[i,n,np] ) for n in 1:length(n) if n <= np <= n+d) for i in Ij3) <= H

    tight4[j in j],
      sum(sum( (alpha[i]*w[i,n,np] + beta[i]*bs[i,n,np] ) for n in 1:length(n) if n <= np <= n+d) for i in Ij4) <= H

    tight5[j in j],
      sum(sum( (alpha[i]*w[i,n,np] + beta[i]*bs[i,n,np] ) for n in 1:length(n) if n <= np <= n+d) for i in Ij5) <= H

end