hw4 is done
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@ -36,7 +36,7 @@ $$\nabla_X L(X,\lambda) = \begin{bmatrix}(-3-\lambda)x^* + 1\\(1-\lambda)y^* +
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\begin{bmatrix}x^*\\y^*\\z^*\end{bmatrix} =
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\begin{bmatrix}x^*\\y^*\\z^*\end{bmatrix} =
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\begin{bmatrix}\frac1{3+\lambda}\\-\frac1{1-\lambda}\\-\frac{1}{2-\lambda}\end{bmatrix}$$
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\begin{bmatrix}\frac1{3+\lambda}\\-\frac1{1-\lambda}\\-\frac{1}{2-\lambda}\end{bmatrix}$$
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Then we have the conditions on the equality constraint:
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Then we have the complementarity condition:
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$$c(X) = {x^*}^2 + {y^*}^2 + {z^*}^2 - 1 = 0 \Leftrightarrow \|X^*\| = 1$$
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$$c(X) = {x^*}^2 + {y^*}^2 + {z^*}^2 - 1 = 0 \Leftrightarrow \|X^*\| = 1$$
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@ -141,10 +141,76 @@ Then we have the conditions on the equality constraint:
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$$Ax - b = 0 \Leftrightarrow \begin{bmatrix}x_1 + x_3\\x_2 + x_3\end{bmatrix} =
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$$Ax - b = 0 \Leftrightarrow \begin{bmatrix}x_1 + x_3\\x_2 + x_3\end{bmatrix} =
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\begin{bmatrix}3\\0\end{bmatrix}$$
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\begin{bmatrix}3\\0\end{bmatrix}$$
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Then we have the conditions on the equality constraint:
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Then we have the complementarity condition:
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$$\lambda^T (Ax - b) = 0 \Leftarrow Ax - b = 0 \text{ which is true if the above
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$$\lambda^T (Ax - b) = 0 \Leftarrow Ax - b = 0 \text{ which is true if the above
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condition is true.}$$
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condition is true.}$$
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Since we have no inequality constraints, we don't need to apply the KKT
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Since we have no inequality constraints, we don't need to apply the KKT
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conditions realated to inequality constraints.
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conditions realated to inequality constraints.
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# Exercise 3
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## Exercise 3.1
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The lagrangian of this problem is the following:
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$$L(x, \lambda) = c^T x - \lambda^T (Ax - b) - s^T x$$
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The KKT conditions are the following:
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1. The partial derivative of the lagrangian w.r.t. $x$ is 0:
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$$\nabla_x L(x, \lambda) = c - A^T \lambda - s = 0 \Leftrightarrow A^T \lambda
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+ s = c$$
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2. Equality constraints hold:
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$$Ax - b = 0 \Leftrightarrow Ax = b$$
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3. Inequality constraints hold:
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$$x \geq 0$$
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4. The lagrangian multipliers for inequality constraints are non-negative:
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$$s \geq 0$$
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5. The complementarity condition holds (here considering only inequality constraints,
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since the condition trivially holds for equality ones):
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$$s^T x \geq 0$$
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## Exercise 3.2
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We define the dual problem is the following way:
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$$\max b^T \lambda \;\; \text{ s.t. } \;\; A^T \lambda + s = c \; \text{ and
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}\; s \geq 0$$
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To convert this maximization problem in a minimization one, we flip the sign of
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the objective and we find:
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$$\min - b^T \lambda \;\; \text{ s.t. } \;\; A^T \lambda + s = c \; \text{ and
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}\; s \geq 0$$
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We then compute the Lagrangian of the dual problem:
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$$L(\lambda, x) = -b^T \lambda + x^T (A^T \lambda + s - c) - x^T s = - b^T \lambda + x^T (A^T \lambda - c)$$
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The KKT conditions are the following:
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1. The partial derivative of the lagrangian w.r.t. $x$ is 0:
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$$\nabla_{\lambda} L(\lambda, x) = - b^T + x^T A^T = 0 \Leftrightarrow Ax = b$$
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2. Equality constraints hold:
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$$A^T \lambda + s = c$$
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3. Inequality constraints hold:
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$$c - A^T \lambda \geq 0 \Leftrightarrow s \geq 0 \;\;\; \text{ using 2.\ to find
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that } s = c - A^T \lambda$$
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4. The lagrangian multipliers for inequality constraints are non-negative:
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$$x \geq 0$$
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5. The complementarity condition holds (here considering only inequality constraints,
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since the condition trivially holds for equality ones):
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$$x^T s \geq 0 \Leftrightarrow s^T x \geq 0$$
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Then, if we compare the KKT conditions of the primal problem with the ones above
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we can match them to see that they are identical:
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- 1.\ from the dual is identical to 2.\ from the primal;
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- 2.\ from the dual is identical to 1.\ from the primal;
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- 3.\ from the dual is identical to 4.\ from the primal;
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- 4.\ from the dual is identical to 3.\ from the primal;
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- 5.\ from the dual is identical to 5.\ from the primal.
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Therefore, the primal and the dual problem are equivalent.
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