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今天看了一篇介绍屏障法的文章,图文并茂,还有真代码一行一行解有约束的含有不等式的最优化问题。虽然标题有内点法,但是没有提内点法中的原始对偶方法。其实这两个方法都是在面对 KKT 条件的时候的思考,不过对对偶变量的处理看待角度不同,朴素的求解都是用牛顿法。如果你对普通的等式约束,KKT 条件,拉格朗日方法有了解的,这篇文章读起来就更容易了。https://towardsdatascience.com/how-to-solve-constrained-optimization-problem-the-interior-point-methods-1733095f9eb5



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今天看了一篇介绍屏障法的文章,图文并茂,还有真代码一行一行解有约束的含有不等式的最优化问题。虽然标题有内点法,但是没有提内点法中的原始对偶方法。其实这两个方法都是在面对 KKT 条件的时候的思考,不过对对偶变量的处理看待角度不同,朴素的求解都是用牛顿法。如果你对普通的等式约束,KKT 条件,拉格朗日方法有了解的,这篇文章读起来就更容易了。https://towardsdatascience.com/how-to-solve-constrained-optimization-problem-the-interior-point-methods-1733095f9eb5

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