Update multistartoptimization.md

Author: Vaibhavdixit02

docs/src/optimization_packages/multistartoptimization.md

@@ -5,12 +5,6 @@
 
 Currently, only one global method (`TikTak`) is implemented and called by `MultiStartOptimization.TikTak(n)` where `n` is the number of initial Sobol points. 
 
-
-!!! note
-
-    If you checkout the master branch of `MultiStartOptimization` or have version `>=0.1.3` you can use all optimizers found in the `GalacticOptim` which work with an initial parameter set. See an example of this below.
-
-
 ## Installation: GalacticMultiStartOptimization.jl
 
 To use this package, install the GalacticMultiStartOptimization package:
@@ -38,10 +32,10 @@ x0 = zeros(2)
 p  = [1.0, 100.0]
 f = OptimizationFunction(rosenbrock)
 prob = GalacticOptim.OptimizationProblem(f, x0, p, lb = [-1.0,-1.0], ub = [1.0,1.0])
-sol = solve(prob, MultistartOptimization.TikTak(100), local_method = NLopt.LD_LBFGS())
+sol = solve(prob, MultistartOptimization.TikTak(100), NLopt.LD_LBFGS())
 ```
 
-If you have checked out the master branch `MultiStartOptimization` version `0.1.2` or have version `>=0.1.3` you can use any `GalactimOptim` optimizers you like. The global method of the `MultiStartOptimization` is a positional argument and if the given method has a local method it can be easily defined via the `local_method` keyword argument as you would without `MultiStartOptimization`. This for example means we can perform a multistartoptimization with LBFGS as the optimizer using either the `NLopt.jl` or `Optim.jl` implementation as follows. Moreover, this interface allows you access and adjust all the optimizer settings as you normally would:
+You can use any `GalacticOptim` optimizers you like. The global method of the `MultiStartOptimization` is a positional argument and followed by the local method. This for example means we can perform a multistartoptimization with LBFGS as the optimizer using either the `NLopt.jl` or `Optim.jl` implementation as follows. Moreover, this interface allows you access and adjust all the optimizer settings as you normally would:
 
 ```julia
 rosenbrock(x, p) =  (p[1] - x[1])^2 + p[2] * (x[2] - x[1]^2)^2