Error : no method matching getindex

Specific Domains Optimization (Mathematical)
1

I have my code displaying the objective function with the constraints but the final answer is not reflecting. I always get the error " No method matching getindex".
I look through the work severally but am not able to rectify the error. Any help will be greatly appreciated please. Attached is the code please.

using JuMP
import Juniper
import Ipopt

m=15 # num customers
NumVar=5 # num hospitals
a=[0 2.5 -2.5 2 -2.5] # x cordinates of the circle
 b=[0 0.3 0.25 -2.5 -2.25]  # y cordinates of the circle
xs=[0 2.5 -2.5 2 -2.5] # x cordinates of the circle
 ys=[0 0.3 0.25 -2.5 -2.25]  # y cordinates of the circle


r= [2, 2 , 2 , 2 ,2] # Radiuus of circle
 R = 0.0

coverage=[1 0 0 0 1;0 0 0 1 1;1 0 0 0 1;0 0 1 1 1;0 0 0 1 1; 0 1 0 0 1;0 0 1 1 0;0 0 0 1 0;1 0 0 0 0;1 1 0 0 0;0 1 0 0 0;0 0 1 0 0;0 0 1 0 0;1 0 0 0 0;0 0 0 1 0 ] # here is the coverage matrix for five hospitals and two customers



   
function inner_loop(x, y,R,coverage)
   

    for i in 1:length(a)
        R = max(R, sqrt((a[i] - x)^2 + (b[i] - y)^2) + r[i])
    end
    
    model = Model(
    optimizer_with_attributes(
        Juniper.Optimizer,
        "nl_solver" => optimizer_with_attributes(Ipopt.Optimizer, MOI.Silent() => true),
    ),
)
    
    ###Declare the variables###
@variable(model, x[i=1:NumVar], Bin)
@variable(model, R>=0)
@variable(model, X>=0)
@variable(model, y>=0)
@variable(model, z >= 0)
    

##Define the objective function###

@objective(model, Min, R)

###Define your constraints###
@constraint(model, constr[i=1:m],   sum(coverage[i,j]*x[j] for j=1:NumVar)  >= 1)
for i in 1:NumVar
    
    
   @NLconstraint(model,  (sqrt((xs[i] -X)^2 + (ys[i] -y)^2 ) + r[i])*x[i] <= R  )
    
end
    
    
    @show model
print(model)
    optimize!(model)
    for i in 1:NumVar
   println("X[$i] = ", value(X[i]))
   
    #println("r[$i] = ", value(r[i]))
end
    return value(x), value(y), value(z), value(R)
end

function main()
    x, y, z, R = 0.0, 0.0, Inf, 0.0
    while abs(x^2 + y^2 - z) >= 0.01
        x, y, z, R = inner_loop(x, y,R,coverage)
    end
    
    print("The abs value is: abs(x^2+y^2-z) = " , abs(x^2+y^2-z))
    
    return x, y, z, R
end
main()
2

Your problem is println("X[$i] = ", value(X[i])). The capital X is a single variable, not a vector.

I’d refactored your code a little, but you still have a problem: it doesn’t converge because z isn’t part of the optimization model (and so it can pick any value).

using JuMP
import Juniper
import Ipopt

function inner_loop(old_x, old_y, R)
    m = 15 # num customers
    NumVar = 5 # num hospitals
    a = [0, 2.5, -2.5, 2, -2.5] # x cordinates of the circle
    b = [0, 0.3, 0.25, -2.5, -2.25]  # y cordinates of the circle
    xs = [0, 2.5, -2.5, 2, -2.5] # x cordinates of the circle
    ys = [0, 0.3, 0.25, -2.5, -2.25]  # y cordinates of the circle
    r = [2, 2, 2, 2, 2] # Radiuus of circle
    R = 0.0
    coverage = [
        1 0 0 0 1;
        0 0 0 1 1;
        1 0 0 0 1;
        0 0 1 1 1;
        0 0 0 1 1;
        0 1 0 0 1;
        0 0 1 1 0;
        0 0 0 1 0;
        1 0 0 0 0;
        1 1 0 0 0;
        0 1 0 0 0;
        0 0 1 0 0;
        0 0 1 0 0;
        1 0 0 0 0;
        0 0 0 1 0
    ]
    for i in 1:length(a)
        R = max(R, sqrt((a[i] - old_x)^2 + (b[i] - old_y)^2) + r[i])
    end    
    model = Model(
        optimizer_with_attributes(
            Juniper.Optimizer,
            "nl_solver" => optimizer_with_attributes(
                Ipopt.Optimizer, 
                MOI.Silent() => true,
            ),
        ),
    )
    @variable(model, x[1:NumVar], Bin)
    @variable(model, R >= 0)
    @variable(model, X >= 0)
    @variable(model, Y >= 0)
    @variable(model, z >= 0)
    @objective(model, Min, R)
    @constraint(model, [i=1:m], coverage[i, :]' * x >= 1)
    @NLconstraint(
        model, 
        [i=1:NumVar],
        (sqrt((xs[i] - X)^2 + (ys[i] - Y)^2) + r[i]) * x[i] <= R
    )
    optimize!(model)
    for i in 1:NumVar
        println("x[$i] = ", value(x[i]))
    end
    return value(X), value(Y), value(z), value(R)
end

function main()
    x, y, z, R = 0.0, 0.0, Inf, 0.0
    while abs(x^2 + y^2 - z) >= 0.01
        x, y, z, R = inner_loop(x, y, R)
    end
    print("The abs value is: abs(x^2+y^2-z) = " , abs(x^2 + y^2 - z))
    return x, y, z, R
end

main()
3

Thank you sir. I will fix the issue with z. It seems the code keeps running without stopping. How do I get that fixed please?

4

It seems the code keeps running without stopping

z can take any value. There’s nothing constraining it to be close to x^2 + y^2.

5

Corrected. Everything looks perfect now. Thank you for the explanation and help

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