### Author:  [@varun7rs](https://discourse.julialang.org/u/varun7rs)
#### Post date: [June 28, 2018, 11:37pm UTC](https://discourse.julialang.org/t/boundserror-when-re-solving-a-model/12050/1 "2018-06-28T23:37:12Z")
I’ve implemented a neighbourhood search technique wherein I deepcopy the original model, hot-start it and then solve it repeatedly. While the first iteration went smooth, during the second iteration however, I get this error while solving the modified MIP
```julia
ERROR: LoadError: BoundsError: attempt to access 15469-element Array{Float64,1} at index [15470]
Stacktrace:
[1] set_constrLB!(::CPLEX.Model, ::Array{Float64,1}) at /home/user/.julia/v0.6/CPLEX/src/cpx_constrs.jl:243
[2] setconstrLB!(::CPLEX.CplexMathProgModel, ::Array{Float64,1}) at /home/user/.julia/v0.6/CPLEX/src/CplexSolverInterface.jl:123
[3] #build#119(::Bool, ::Bool, ::JuMP.ProblemTraits, ::Function, ::JuMP.Model) at /home/user/.julia/v0.6/JuMP/src/solvers.jl:337
[4] (::JuMP.#kw##build)(::Array{Any,1}, ::JuMP.#build, ::JuMP.Model) at ./:0
[5] #solve#116(::Bool, ::Bool, ::Bool, ::Array{Any,1}, ::Function, ::JuMP.Model) at /home/user/.julia/v0.6/JuMP/src/solvers.jl:168
```
I’m not sure where the error is. Besides, the error is thrown after the MIP is passed to the solver.
---
### Author:  [@odow](https://discourse.julialang.org/u/odow)
#### Post date: [June 29, 2018, 1:02pm UTC](https://discourse.julialang.org/t/boundserror-when-re-solving-a-model/12050/2 "2018-06-29T13:02:37Z")
Hi @varun7rs, can you provide a [minimum working example](https://stackoverflow.com/help/mcve) that triggers this bug? It’s a little hard to find out what is going wrong otherwise.
---
### Author:  [@varun7rs](https://discourse.julialang.org/u/varun7rs)
#### Post date: [June 29, 2018, 5:04pm UTC](https://discourse.julialang.org/t/boundserror-when-re-solving-a-model/12050/3 "2018-06-29T17:04:58Z")
Hi @odow, thanks for your reply. The original problem was too complicated to post. This is a condensed version of the problem I’m solving but I encounter a different error now. The stacktrace seems a little too similar to the previous error however.
Just to briefly explain what the heuristic does, we solve a relaxation of a MIP and then employ a rounding technique (the one in the MWE is a simplified version. In my problem I use the ACO heuristic for rounding). To improve the rounded solutions, we use a neighbourhood search technique.
```julia
using JuMP
using CPLEX
profit = [5, 3, 2, 7, 4]
weight = [2, 8, 4, 2, 5]
capacity = 10
const ϵ = 0.1
K = length(profit)
type MyProblem
model
x
z
end
function createproblem(profit, weight, capacity)
K = length(profit)
m = Model(solver=CplexSolver())
@variable(m, x[1:K], Bin)
@variable(m, z ≥ 0.0)
@objective(m, Max, dot(profit, x))
@constraint(m, dot(weight, x) <= capacity)
return MyProblem(m, x, z)
end
# A simple rounding heuristic
p = createproblem(profit, weight, capacity)
status = solve(p.model, relaxation = true)
xR, zR = getvalue(p.x), getvalue(p.z)
obj = getobjectivevalue(p.model)
x = zeros(Float64,K) # Fixed variables
for k = 1:K
if xR[k] ≥ 1-ϵ
x[k] = 1.0
end
end
# A Neighbourhood search heuristic
start = time(); TILIM = 300.0;
θ = 0.005 * obj; M = 1e+15;
i = 0
while (time()-start) < TILIM
i += 1
temp = deepcopy(p)
# Hot-start
for k = 1:K
setvalue(temp.x[k], x[k])
end
# Cut-off
@constraint(temp.model, dot(profit, temp.x) ≥ obj + θ - temp.z)
@objective(temp.model, Min, sum((x[k] == 0.0) ? temp.x[k] : 0.0 for k = 1:K)
+ sum((x[k] == 1.0) ? (1-temp.x[k]) : 0.0 for k = 1:K)
+ M * temp.z)
println("Iteration $i")
solve(temp.model)
if getvalue(temp.z) == 0.0
x = getvalue(temp.x); z = getvalue(temp.z)
obj = dot(profit, x)
else
θ = θ / 2.0
end
end
```
---
### Author:  [@odow](https://discourse.julialang.org/u/odow)
#### Post date: [June 29, 2018, 5:14pm UTC](https://discourse.julialang.org/t/boundserror-when-re-solving-a-model/12050/4 "2018-06-29T17:14:26Z")
`deepcopy` is not intended to be used on JuMP models. It can lead to unexpected behaviour as you observe.
Why do you need the copy instead of just using the model `p` everywhere?
---
### Author:  [@varun7rs](https://discourse.julialang.org/u/varun7rs)
#### Post date: [June 29, 2018, 5:55pm UTC](https://discourse.julialang.org/t/boundserror-when-re-solving-a-model/12050/5 "2018-06-29T17:55:06Z")
Since I modify model `p` at every iteration(I add a cut-off constraint which is modified over the course of the heuristic), I wanted to have a different copy of the model. And since I had trouble doing [this](https://discourse.julialang.org/t/solving-a-model-and-its-modified-copy/9778), I used `deepcopy`. Is there another way around this problem?
For now, I’ve settled with re-building the problem at each iteration by calling `createproblem` but I’m worried if model building would consume a lot of time for larger problem instances
---
### Author:  [@odow](https://discourse.julialang.org/u/odow)
#### Post date: [June 30, 2018, 4:55am UTC](https://discourse.julialang.org/t/boundserror-when-re-solving-a-model/12050/6 "2018-06-30T04:55:44Z")
Instead of the deepcopy, you should just rebuild the model using `createproblem`.
The upcoming release of JuMP will support constraint deletion which should help this situation a lot. Then you can just delete the cut and add a new one in each iteration to the same model.
Some solvers will also support constraint coefficient modification, so you don’t even have to delete and then re-add, you can just modify the coefficients of the constraint in-place.
---
### Author:  [@varun7rs](https://discourse.julialang.org/u/varun7rs)
#### Post date: [June 30, 2018, 5:51pm UTC](https://discourse.julialang.org/t/boundserror-when-re-solving-a-model/12050/7 "2018-06-30T17:51:12Z")
Thanks a lot for the help.