# Getindex in Model Constraints assign
**URL:** https://discourse.julialang.org/t/getindex-in-model-constraints-assign/54678
**Category:** Optimization (Mathematical)
**Tags:** jump
**Created:** [February 5, 2021, 10:41am UTC](https://discourse.julialang.org/t/getindex-in-model-constraints-assign/54678 "2021-02-05T10:41:38Z")
**Posts on this page:** 4
**Page:** 1
### Author:  [@user1200](https://discourse.julialang.org/u/user1200)
#### Post date: [February 5, 2021, 10:41am UTC](https://discourse.julialang.org/t/getindex-in-model-constraints-assign/54678/1 "2021-02-05T10:41:38Z")
Hello
Is there a way to use getIndex or findfirst function in Constraints in Model?
Usage: Get maximum value from “1 vector(column)”-but remember just its index, for example 8th.
Then get value from “another vector(column)” at specific index (8th)?
pseudocode
`vector2[getindex(max(vector1), vector1)]`
in model:
```julia
data = rand(14,10)
model = Model() #model = Model(Ipopt.Optimizer)
@variable(model, x1)
@variable(model, maxi)
@variable(model, inde) #@variable(model, inde,Int)
@constraints(model, begin
[i=1:14], data[i,1] * x1 <=maxi
end)
@constraints(model, begin
# inde==findfirst(maxi, data[1:14,1])
inde==getindex(maxi, data[1:14,1])
end)
@objective(model, Max, data[inde,2] ) #goal
```
_or custom function for model is needed to create?_
---
### Author:  [@Wikunia](https://discourse.julialang.org/u/Wikunia)
#### Post date: [February 5, 2021, 11:00am UTC](https://discourse.julialang.org/t/getindex-in-model-constraints-assign/54678/2 "2021-02-05T11:00:42Z")
In general you can’t index with a variable as the variable is continuous.
---
### Author:  [@user1200](https://discourse.julialang.org/u/user1200)
#### Post date: [February 5, 2021, 1:06pm UTC](https://discourse.julialang.org/t/getindex-in-model-constraints-assign/54678/3 "2021-02-05T13:06:16Z")
i tried
(code is working without errors, but optimum wasnt found 😁)
```julia
using Random
using JuMP
import Ipopt
Random.seed!(1200)
data = rand(6)
data2 = rand(6)
data[2]=40.1
data2[2]=123.12
model = Model(Ipopt.Optimizer)
@variable(model, x1)
f(x...) = data2[findfirst(x .== max(x...) ) ]
register(model, :f, 6, f; autodiff = true)
@NLexpression(model, y[i = 1:6],data[i]*x1 )
@NLobjective(model, Max, f(y...) )
optimize!(model)
value(x1)
data2
data
```
solution is optimal…x1=0
but, for x=1, objective value is 123.12 (higher)
(2nd element in data is max…also 2nd element in data2 (objective) is max
6-element Array{Float64,1}:
0.6090858757801794
**40.1**
0.7418153587583025
0.1461819584127848
0.22809478234081726
0.7570257298492764
julia\> data2
6-element Array{Float64,1}:
0.8393052531712282
**123.12**
0.05918180470419587
0.05660165930690897
0.3355748112808865
0.8392086371374328
---
### Author:  [@odow](https://discourse.julialang.org/u/odow)
#### Post date: [February 5, 2021, 9:20pm UTC](https://discourse.julialang.org/t/getindex-in-model-constraints-assign/54678/4 "2021-02-05T21:20:16Z")
You need to use a mixed-integer linear program:
```nohighlight
using JuMP, Cbc
data = rand(14, 2)
model = Model(Cbc.Optimizer)
@variables(model, begin
maxi
z[1:14], Bin
end)
@constraints(model, begin
[i=1:14], data[i, 1] <= maxi
maxi == sum(data[i, 1] * z[i] for i = 1:14)
sum(z) == 1
end)
@objective(model, Max, sum(data[i, 2] * z[i] for i = 1:14)
```
Here are some tricks: [9 Mixed integer optimization — MOSEK Modeling Cookbook 3.3.0](https://docs.mosek.com/modeling-cookbook/mio.html)