I get this warning message on some optimization problems.

```
┌ Warning: The addition operator has been used on JuMP expressions a large number of times. This warning is safe to ignore but may indicate that model generation is slower than necessary. For performance reasons, you should not add expressions in a loop. Instead of x += y, use add_to_expression!(x,y) to modify x in place. If y is a single variable, you may also use add_to_expression!(x, coef, y) for x += coef*y.
└ @ JuMP C:\Users\a\.julia\packages\JuMP\MsUSY\src\JuMP.jl:747
```

I only get this when I am reading large amounts of data from a spreadsheet for the optimisation problem, and not on simple problems. I suspect the source is the constraint calculation. I have given a MWE below, which does not yield the same warning but it should give an idea about how the constraint is determined. How can add_to_expression!(x,y) be used here to make the code more efficient?

```
using JuMP
using Clp
myModel = Model(with_optimizer(Clp.Optimizer))
prices = [99.74, 91.22, 98.71, 103.75, 97.15]
cashFlows = [4 5 2.5 5 4; 4 5 2.5 5 4; 4 5 2.5 5 4; 4 5 2.5 5 4; 4 5 102.5 5 4;4 5 0 105 104;4 105 0 0 0; 104 0 0 0 0]
Liab_CFs = [5, 7, 7, 6, 8, 7, 20, 0]*1000
Rates = [0.01, 0.015, 0.017, 0.019, 0.02, 0.025, 0.027, 0.029]
Disc= [0.99009901, 0.970661749, 0.950686094, 0.927477246, 0.90573081, 0.862296866, 0.829863942, 0.795567442]'
nBonds = [10, 100, 20, 30, 5]*1000
@variable(myModel, 0<= x[b = 1:length(nBonds)] <= nBonds[b])
@objective(myModel,Min,prices' *x)
A=Liab_CFs-cashFlows*x
M=[AffExpr(0.0) for k = 1:8]
M[1] = A[1]
M2[1] = M[1]
for k = 2:length(A)
M[k] = (A[k]*Disc[k]+M[k-1])
M2[k] = M[k]/Disc[k]
end
@constraint(myModel, constraint1,M2 .<=0.05*53.844)
optimize!(myModel)
```