testsolver.jl

using JuMP, AmplNLWriter

function SolverNL(C)

    num_stations  = length(ESTACIONES);
    num_candidatas  = 15#length(CANDIDATAS);

    Centros = [1,1,1,1,1,1,1,1,1,1,1,1,1,1,1]
    Pertenece = []
    CANDIDATOS = [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15]
    for j in CANDIDATAS
        if C[j] == 1
            push!(Pertenece,j);
        end
    end
    println("Centros: ", Centros);
    println("Pertenece: ", Pertenece)


    E = zeros(Int64,num_stations);
    m = Model(with_optimizer(AmplNLWriter.Optimizer, "knitro",  ["outlev=3"]))
    @variable(m,x[i=1:num_stations,j=1:num_candidatas],Bin)
    @variable(m,beta, start = 0.0);
    f1 = @NLexpression(m,(sum(dist[i, j] * x[i, j] for i in ESTACIONES, j in CANDIDATOS)))#-idealf1)/(anti_idealf1-idealf1));
    f2 = @NLexpression(m,(beta))#-idealf2)/(anti_idealf2-idealf2));
    @NLobjective(m,Min,a_ws*f1+(1-a_ws)*f2);

    for i in ESTACIONES
        @constraint(m,sum(x[i,j] for j in CANDIDATOS) == 1)
    end

    for i in ESTACIONES
        for j in CANDIDATOS
                @constraint(m,x[i,j] <= c[i,j]*Centros[j])
        end
    end

    for j in CANDIDATOS
        for l in PRIORIDADES
            if l == 1
                pxsum = @expression(m, sum(prior[i,l]*x[i,j] for i in ESTACIONES))
                psum = @expression(m, sum(prior[i,l] for i in ESTACIONES))
                @constraint(m,(pxsum  - floor(psum/cl)*Centros[j]) <= prioridad)
                @constraint(m,(floor(psum/cl)*Centros[j] - pxsum) <= prioridad)
            end
        end
    end

    f2Array = @NLexpression(m, [j = 1:num_candidatas], abs(sum(r_menos[i]*x[i,j] for i in ESTACIONES)-sum(r_mas[i]*x[i,j] for i in ESTACIONES)))
    @NLconstraint(m, [j = 1:num_candidatas], beta*(sum(r_menos[i]*x[i,j] for i in ESTACIONES)+sum(r_mas[i]*x[i,j] for i in ESTACIONES)) >= f2Array[j])

    optimize!(m)
    status = termination_status(m);
    Z_opt = objective_value(m);
    x_opt = value.(x);
    valuef2 = value(f2);

    x_normal = []
    for i in CANDIDATOS
        #x_normal[Pertenece[i]] = x_opt[i,:]
    end
    #println("x_OPT ", x_opt);
    #println("x_NORMAL ", x_normal);

    if valuef2 > 1
        valuef2 = 1;
    end
    println("FUNCION OBJETIVO POR RETORNAR: ", Z_opt);
    println("FUNCION 1 POR RETORNAR: ", value(f1));
    println("FUNCION 2 POR RETORNAR: ", valuef2);

    ##CALCULO DE DMAX
    dmax = fitness_all(x_normal, C)

    if (status != MOI.OPTIMAL && status != MOI.LOCALLY_SOLVED) || (length(x_normal) == 0)
        return Inf, Inf, Inf, E, dmax;
    else
        for i in ESTACIONES
            E[i] = findall(x->x==1,x_normal[i,:])[1];
        end
        return Z_opt, value(f1), valuef2, E, dmax
    end
end