@@ -69,7 +69,7 @@ For a more extensive documentation of all the algorithms and options please cons
69
69
* ` μ0::Union{Symbol,Number} = :auto `
70
70
* ` show_linesearch::Bool = false `
71
71
72
- The Rosenbrock function can optimized using the ` Optim.IPNewton() ` as follows:
72
+ The Rosenbrock function with constraints can optimized using the ` Optim.IPNewton() ` as follows:
73
73
74
74
``` @example Optim1
75
75
using Optimization, OptimizationOptimJL
@@ -350,10 +350,9 @@ The Rosenbrock function can optimized using the `Optim.KrylovTrustRegion()` as f
350
350
``` @example Optim5
351
351
using Optimization, OptimizationOptimJL
352
352
rosenbrock(x, p) = (1 - x[1])^2 + 100 * (x[2] - x[1]^2)^2
353
- cons= (res,x,p) -> res .= [x[1]^2 + x[2]^2]
354
353
x0 = zeros(2)
355
354
p = [1.0,100.0]
356
- optprob = OptimizationFunction(rosenbrock, Optimization.AutoForwardDiff();cons= cons )
355
+ optprob = OptimizationFunction(rosenbrock, Optimization.AutoForwardDiff())
357
356
prob = Optimization.OptimizationProblem(optprob, x0, p)
358
357
sol = solve(prob, Optim.KrylovTrustRegion())
359
358
```
@@ -362,8 +361,8 @@ sol = solve(prob, Optim.KrylovTrustRegion())
362
361
363
362
364
363
### Without Constraint Equations
365
- The following method in [ ` Optim ` ] ( https://github.com/JuliaNLSolvers/Optim.jl ) is performing global optimization on problems without
366
- constraint equations . It works both with and without lower and upper constraints set by ` lb ` and ` ub ` in the ` Optimization.OptimizationProblem ` .
364
+ The following method in [ ` Optim ` ] ( https://github.com/JuliaNLSolvers/Optim.jl ) performs global optimization on problems with or without
365
+ box constraints . It works both with and without lower and upper bounds set by ` lb ` and ` ub ` in the ` Optimization.OptimizationProblem ` .
367
366
368
367
- [ ` Optim.ParticleSwarm() ` ] ( https://julianlsolvers.github.io/Optim.jl/stable/#algo/particle_swarm/ ) : ** Particle Swarm Optimization**
369
368
@@ -386,8 +385,8 @@ sol = solve(prob, Optim.ParticleSwarm(lower=prob.lb, upper= prob.ub, n_particles
386
385
```
387
386
388
387
### With Constraint Equations
389
- The following method in [ ` Optim ` ] ( https://github.com/JuliaNLSolvers/Optim.jl ) is performing global optimization on problems with
390
- constraint equations .
388
+ The following method in [ ` Optim ` ] ( https://github.com/JuliaNLSolvers/Optim.jl ) performs global optimization on problems with
389
+ box constraints .
391
390
392
391
- [ ` Optim.SAMIN() ` ] ( https://julianlsolvers.github.io/Optim.jl/stable/#algo/samin/ ) : ** Simulated Annealing with bounds**
393
392
0 commit comments