# GSoC 2017: Constrained Optimisation in Native Julia
**URL:** https://discourse.julialang.org/t/gsoc-2017-constrained-optimisation-in-native-julia/2497
**Category:** Community
**Created:** [March 6, 2017, 2:57pm UTC](https://discourse.julialang.org/t/gsoc-2017-constrained-optimisation-in-native-julia/2497 "2017-03-06T14:57:26Z")
**Posts on this page:** 2
**Page:** 1
### Author:  [@antonio-ribeiro](https://discourse.julialang.org/u/antonio-ribeiro)
#### Post date: [March 6, 2017, 2:57pm UTC](https://discourse.julialang.org/t/gsoc-2017-constrained-optimisation-in-native-julia/2497/1 "2017-03-06T14:57:26Z")
Hello, my name is Antonio and I am a Brazilian electrical engineer currently pursuing my master degree. I am interested in applying to Google Summer of Code 2017 with the proposal of implementing optimisation methods for problems with nonlinear constraints.
There is already a well developed ecosystem for optimisation in Julia: [JuliaOpt](http://www.juliaopt.org) provide wrappers for several solvers. And [JuliaNLSolvers](https://github.com/JuliaNLSolvers) provide implementation of solvers in native Julia.
There are many advantages of having a native Julia implementation, including the ability to use Julia-defined types and composability with other packages. However, while JuliaNLSolvers is in good shape for unconstrained optimisation, it still don’t have implemented methods that are able to deal with nonlinear constraints.
My proposal is to implement state-of-the-art solvers (interior point and SQP methods) for constrained optimisation problems in Julia. I have opened this topic to discuss possible mentors and get some feedback about the relevance of this project for Julia.
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### Author:  [@cortner](https://discourse.julialang.org/u/cortner)
#### Post date: [March 6, 2017, 3:42pm UTC](https://discourse.julialang.org/t/gsoc-2017-constrained-optimisation-in-native-julia/2497/2 "2017-03-06T15:42:11Z")
have a look at the `pkm/constrained` branch of `Optim.jl`