"How to make the summation to a specific period in Julia?" - julia

Question

I am formulating mathematical programming and now I have an issue with the summation sign in a constraint. I want to sum over the specific period in a planning horizon, I have tried some but Julia report an error message.
the mathematical formula looks somewhat like this:
constraint1
and this:constraint2
here is some code I have tried:
Horizon = 12
Section = 5
TBetPM = [4 6 9 8 5]
LPM = [1 4 5 4 4]
MaxPM = [9 8 7 10 6]
PrevPM = [3 3 2 5 2]
tam=zeros(Float64,1,5)
for i=1:Section
tam[i] = TBetPM[i]-LPM[i]
end
tar = zeros(Float64,1,5)
for i=1:Section
tar[i] = Pi[i]*(MaxPM[i]-PrevPM[i])-LPM[i]
end
#constraint(mod, [i=1:Section],
sum(m[i,t] for t=1:Horizon if t<=tam[i]) >= 1
)
#constraint(mod, [i=1:Section],
sum(r[i,t] for t=1:Horizon if t<=tar[i]) >= 1
)
I also tried these but both does not work
#constraint(mod, [i=1:Section],
sum(m[i,t] for t=1:tam[i]) >= 1
)
#constraint(mod, [i=1:Section],
sum(r[i,t] for t=1:tar[i]) >= 1
)
Thank you in advance for all the answers :)

Answer 1

You used a model mod in your #constraint macro. It wasn't defined. You must create it if you use JuMP.
using JuMP
mod = Model()
You previsouly initialized tam and tar as two dimensionnal arrays of size 1x5 (matrices). I think you needed a one dimensional array as you accessed them as vectors :
tam = zeros(Float64,5)
tar = zeros(Float64,5)
You didn't defined the variables m and r in your model :
#variable(mod, m[i=1:Section, t=1:Horizon])
#variable(mod, r[i=1:Section, t=1:Horizon])
Finally, you might want JuMP to solve your model, this can be done with :
using GLPK # feel free here to use the solver you prefer
optimize!(mod, with_optimizer(GLPK.Optimizer))
And printing the solutions :
if termination_status(mod) == MOI.OPTIMAL
optimal_solution = value.(m), value.(r)
optimal_objective = objective_value(mod)
#show optimal_solution
#show optimal_objective
else
error("The model was not solved correctly.")
end
Whole working code (Julia v1.1.0, JuMP v0.19.0, GPLK v0.9.1):
Horizon = 12
Section = 5
TBetPM = [4 6 9 8 5]
LPM = [1 4 5 4 4]
MaxPM = [9 8 7 10 6]
PrevPM = [3 3 2 5 2]
using JuMP
using GLPK # feel free here to use the solver you prefer
mod = Model()
tam = zeros(Float64,5)
for i in 1:Section
tam[i] = TBetPM[i]-LPM[i]
end
tar = zeros(Float64,5)
for i=1:Section
tar[i] = pi*(MaxPM[i] - PrevPM[i]) - LPM[i]
end
#variable(mod, m[i=1:Section, t=1:Horizon])
#variable(mod, r[i=1:Section, t=1:Horizon])
#constraint(mod, [i=1:Section],
sum(m[i,t] for t in 1:Horizon if t <= tam[i]) >= 1)
#constraint(mod, [i=1:Section],
sum(r[i,t] for t in 1:Horizon if t <= tar[i]) >= 1)
# Solve model and printing solution
optimize!(mod, with_optimizer(GLPK.Optimizer))
if termination_status(mod) == MOI.OPTIMAL
optimal_solution = value.(m), value.(r)
optimal_objective = objective_value(mod)
#show optimal_solution
#show optimal_objective
else
error("The model was not solved correctly.")
end
I don't know if it's because of a copy/paste or something else, but you should indent your code even if it's not mandatory to compile it :p

Answer 2

Thank you for the reply, J.Khamphousone.
Here is the full code I have tried:
using JuMP, CPLEX, Gurobi, GLPKMathProgInterface
sex = Model(solver = GurobiSolver())
Horizon = 12
Section = 5
TBetPM = [4 6 9 8 5]
TlastPM = [0 0 0 0 0]
MaxPM = [9 8 7 10 6]
PrevPM = [3 3 2 5 2]
taf1=zeros(Float64,1,5)
for i=1:Section
taf1[i] = TBetPM[i]-TlastPM[i]
end
tafr1 = zeros(Float64,1,5)
for i=1:Section
tafr1[i] = TBetPM[i]*(MaxPM[i]-PrevPM[i])-TlastPM[i]
end
tafr = zeros(Float64,1,5)
for i=1:Section
tafr[i] = TBetPM[i]*MaxPM[i]
end
mdur = [9 6 8 10 3]
rdur = [18 16 23 16 12]
Maxdur = 24
mcost = [2 6 5.5 4 4]
rcost = [6 15 20 18 25]
scost = [0.6 1.17 0.81 0.66 1.4]
pcost = 2
ccost = 0.001
Ncus = 100
#variable(sex, m[1:Section,1:Horizon]>=0, Bin) # 1 if section s maintain in week h
#variable(sex, r[1:Section,1:Horizon]>=0, Bin) # 1 if section s renew in week h
#variable(sex, p[1:Horizon]>=0,Bin) #1 if possession in week h
#objective(sex, Min, sum(pcost*p[t] for t=1:Horizon)+
sum(mcost[i]*m[i,t] for t=1:Horizon, i=1:Section)+
sum(rcost[i]*r[i,t] for t=1:Horizon, i=1:Section)
)
#select first maintenance time (correct)
#constraint(sex, [i=1:Section],
sum(m[i,t] for t=1:Horizon if t==taf1[i]) >= 1
)
#select next maintenance time (correct)
#constraint(sex, [i=1:Section, k=1:(Horizon-TBetPM[i])],
sum(m[i,t] for t=1+k:TBetPM[i]+k) >= 1
)
#select first renewal time
#constraint(sex, [i=1:Section],
sum(r[i,t] for t in tafr1[i]) >= 1
)
#select next renewal time
#constraint(sex, [i=1:Section, k=1:(Horizon-tafr[i])],
sum(r[i,t] for t=1+k:tafr[i]+k) >= 1
)
# if there is maintenance, there is possession
#constraint(sex, [i=1:Section, h=1:Horizon],
m[i,h] <= p[h]
)
# if there is renewal, there is possession
#constraint(sex, [i=1:Section, h=1:Horizon],
r[i,h] <= p[h]
)
solve(sex)
#print(sex)
mVal = getvalue(m)
for i=1:Section, t=1:Horizon
if (mVal[i,t] ==1)
println("section[$i] repair in period [$t]", )
end
end
rVal = getvalue(r)
for i=1:Section, t=1:Horizon
if (rVal[i,t] ==1)
println("section[$i] renew in period [$t]", )
end
end