lab6 - #5
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nicolaspoly wants to merge 5 commits into
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lab6#5nicolaspoly wants to merge 5 commits into
nicolaspoly wants to merge 5 commits into
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dpo
reviewed
Aug 18, 2025
dpo
reviewed
Aug 18, 2025
dpo
reviewed
Aug 18, 2025
dpo
reviewed
Aug 18, 2025
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dpo
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Aug 19, 2025
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| ## Analyse | ||
| La méthode de Ipopt mets globalement moins d'itération que le gradient projeté mais les deux méthodes trouvent les mêmes solutions pour ces trois problèmes. |
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Ce sont les x* qu'il faudrait comparer...
| elapsed = time() - start_time | ||
| println("Max it atteint ($maxit). Temps écoulé = $(round(elapsed,digits=3)) s") | ||
| return x, q(x), maxit, :maxit | ||
| end |
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??????? ton solveur précédent doit déjà gérer le cas de la boule. Il n'y a pas besoin d'écrire un autre solveur. C'est là tout le but de l'exercice ...
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| Dans notre cas, cela revient à résoudre le même type de problème, mais en considérant la boule centrée en $x_k$ plutôt qu’en l’origine. | ||
| Par ailleur, toute fonction deux fois dérivable peut être approximée par une fonction quadratique locale via le développement de Taylor. | ||
| Cette propriété nous permet d'utiliser cet algorithme pour résoudre des problème d'optimisation avec des fonction objectifs C2. |
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