version finale - #4
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dawutesse1 wants to merge 3 commits into
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dawutesse1 wants to merge 3 commits into
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dpo
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Aug 17, 2025
| Pkg.activate("labo3_env") | ||
| Pkg.add("LDLFactorizations") | ||
| Pkg.add("Metis") | ||
| Pkg.add("AMD") |
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Tu n'utilises pas Metis, ni AMD...
| using LinearAlgebra | ||
| using Printf | ||
| using NLPModels | ||
| using ADNLPModels |
| g = grad(model, x) | ||
| gnorm = norm(g, Inf) | ||
| println(@sprintf("%4d | %12.4e | %12.4e | - ", k, fval, gnorm)) | ||
| if gnorm < max(eps_a, eps_r*norm(x,Inf)) |
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pourquoi utiliser
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| # 3) direction inexacte via CG de Krylov.jl | ||
| Hop = hess_op(model, x) | ||
| tol_cg = min(0.5, sqrt(gnorm)) * gnorm |
| tol_cg = min(0.5, sqrt(gnorm)) * gnorm | ||
| # cg de Krylov : tol, maxiter, linesearch | ||
| p, history = Krylov.cg(Hop, -g; | ||
| atol = tol_cg, |
| end | ||
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| x .+= α*p | ||
| println(@sprintf("%4d | %12.4e | %12.4e | %8.4e", k, fval, gnorm, α)) |
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Tu affiches deux lignes par itération.
| itmax = n, | ||
| linesearch = true) | ||
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| # 4) recherche linéaire Armijo |
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Mettre Armijo dans une fonction.
| model = ADNLPModel(pb) # wrapping ADNLPModels | ||
| println("\n=== Problème : ", nom, " ===") | ||
| x_star = newton_modifiee(model) | ||
| println("Solution trouvée : ", x_star) |
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fval et ||g|| ne changent jamais... que se passe-t-il ?
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| # 4) recherche linéaire Armijo | ||
| α = 1.0; ρ = 0.5; c = 1e-4 | ||
| while obj(model, x + α*p) > fval + c * α * dot(g, p) |
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Tu recalcules dot(g, p) à chaque passage ...
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| À nouveau, chaque pas de Newton complet (α=1) suffit. | ||
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| Newton inexacte converge en 6 itérations également : |
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??? Elle prend 100 itérations et ne semble pas changer x une seule fois.
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