fix typo

Author: SebastianM-C

docs/src/getting_started.md

@@ -14,7 +14,7 @@ The simplest copy-pasteable code using a quasi-Newton method (LBFGS) to solve th
 
 ```@example intro
 # Import the package and define the problem to optimize
-using OptimizationLBFGS, Zygote
+using OptimizationLBFGSB, Zygote
 rosenbrock(u, p) = (p[1] - u[1])^2 + p[2] * (u[2] - u[1]^2)^2
 u0 = zeros(2)
 p = [1.0, 100.0]

docs/src/optimization_packages/optimization.md

@@ -5,7 +5,7 @@ There are some solvers that are available in the Optimization.jl package directl
 ## Methods
 
   - `LBFGS`: The popular quasi-Newton method that leverages limited memory BFGS approximation of the inverse of the Hessian. Through a wrapper over the [L-BFGS-B](https://users.iems.northwestern.edu/%7Enocedal/lbfgsb.html) fortran routine accessed from the [LBFGSB.jl](https://github.com/Gnimuc/LBFGSB.jl/) package. It directly supports box-constraints.
-    
+
     This can also handle arbitrary non-linear constraints through a Augmented Lagrangian method with bounds constraints described in 17.4 of Numerical Optimization by Nocedal and Wright. Thus serving as a general-purpose nonlinear optimization solver available directly in Optimization.jl.
 
 ```@docs
@@ -18,7 +18,7 @@ Optimization.Sophia
 
 ```@example L-BFGS
 
-using Optimization, OptimizationLBFGS, Zygote
+using Optimization, OptimizationLBFGSB, Zygote
 
 rosenbrock(x, p) = (p[1] - x[1])^2 + p[2] * (x[2] - x[1]^2)^2
 x0 = zeros(2)

docs/src/tutorials/certification.md

@@ -7,7 +7,7 @@ This works with the `structural_analysis` keyword argument to `OptimizationProbl
 We'll use a simple example to illustrate the convexity structure certification process.
 
 ```@example symanalysis
-using SymbolicAnalysis, Zygote, LinearAlgebra, Optimization, OptimizationLBFGS
+using SymbolicAnalysis, Zygote, LinearAlgebra, Optimization, OptimizationLBFGSB
 
 function f(x, p = nothing)
     return exp(x[1]) + x[1]^2

docs/src/tutorials/remakecomposition.md

@@ -11,7 +11,7 @@ The SciML interface provides a `remake` function which allows you to recreate th
 Let's look at a 10 dimensional schwefel function in the hypercube $x_i \in [-500, 500]$.
 
 ```@example polyalg
-using OptimizationLBFGS, Random
+using OptimizationLBFGSB, Random
 using OptimizationBBO, ReverseDiff
 
 Random.seed!(122333)