Worksheet 6-1: Convex Sets (with Solutions)

Worksheet 6-1: Convex Sets (with Solutions)#

Download: CMSE382-WS6_1.pdf · Solution PDF

Warning

This is an AI-generated transcript of the worksheet and may contain errors or inaccuracies. Please refer to the original course materials for authoritative content.


Worksheet 6-1: Q1#

Let \(\mathbf{x}_1 = (2,3)^\top\) and \(\mathbf{x}_2 = (1,4)^\top\).

  1. Write the equation of the line passing through \(\mathbf{x}_1\) and \(\mathbf{x}_2\) as a function of \(\lambda\):

    \[\mathbf{x}(\lambda) = (1-\lambda)\mathbf{x}_1 + \lambda \mathbf{x}_2\]
  2. For each value of \(\lambda\) below, compute the point \(\mathbf{x}(\lambda)\):

    \(\lambda\)

    \(\mathbf{x}(\lambda)\)

    On segment?

    \(\lambda = 0\)

    \(\lambda = 1/2\)

    \(\lambda = 1\)

    \(\lambda = 2\)

Solution
\[\begin{split}\mathbf{x}(\lambda) = (1-\lambda)\begin{bmatrix}2\\3\end{bmatrix} + \lambda\begin{bmatrix}1\\4\end{bmatrix} = \begin{bmatrix}2-\lambda \\ 3+\lambda\end{bmatrix}\end{split}\]

\(\lambda\)

\(\mathbf{x}(\lambda)\)

On segment?

\(0\)

\((2,3)\)

Yes (endpoint \(\mathbf{x}_1\))

\(1/2\)

\((1.5, 3.5)\)

Yes (midpoint)

\(1\)

\((1,4)\)

Yes (endpoint \(\mathbf{x}_2\))

\(2\)

\((0, 5)\)

No (outside, beyond \(\mathbf{x}_2\))

The segment corresponds to \(\lambda \in [0,1]\).


Worksheet 6-1: Q2#

For each of the following sets, determine whether it is convex or not convex.

(a) A finite set of points \(S = \{p_1, p_2, \ldots, p_k\} \subset \mathbb{R}^n\) (with \(k \ge 2\)).

Solution

Not convex. The midpoint of any two distinct points in \(S\) is generally not in \(S\).

(b) The nonnegative orthant \(\mathbb{R}^2_+ = \{(x,y) \mid x \ge 0, y \ge 0\}\).

../../../../_images/Rplus.png
Solution

Convex. For any \(\mathbf{x}, \mathbf{y} \in \mathbb{R}^2_+\) and \(\lambda \in [0,1]\): \((1-\lambda)\mathbf{x} + \lambda\mathbf{y}\) has nonnegative components, so it stays in \(\mathbb{R}^2_+\).

(c) The set \(\{(x,y) \mid xy = 0\}\) (the coordinate axes):

Solution

Not convex. Take \((1,0)\) and \((0,1)\); their midpoint \((1/2, 1/2)\) has \(xy = 1/4 \ne 0\), so it’s not in the set.

(d) The nonlinear region shown below:

../../../../_images/nonconvex.png
Solution

Not convex. The figure shows a non-convex region (a crescent or non-star-shaped region) — there exist two points in the set whose connecting segment exits the set.

(e) The \(\ell_1\), \(\ell_2\), and \(\ell_\infty\) unit balls in \(\mathbb{R}^2\):

../../../../_images/unit_ball_examples_R2.png
Solution

All three unit balls are convex:

  • \(\ell_1\) ball (diamond shape): convex polygon.

  • \(\ell_2\) ball (disk): convex (standard result for any norm ball).

  • \(\ell_\infty\) ball (square): convex polygon.

In general, \(\{\mathbf{x} \mid \|\mathbf{x}\| \le 1\}\) is convex for any norm, since norms satisfy the triangle inequality.


Worksheet 6-1: Q3#

(a) Draw an example of a union of two convex sets that is not convex.

Solution

Take \(A = \{(x,y) \mid x \le -1\}\) and \(B = \{(x,y) \mid x \ge 1\}\). Both are convex half-planes, but \(A \cup B\) is not convex (e.g., \((-1,0) \in A\) and \((1,0) \in B\) but the midpoint \((0,0) \notin A \cup B\)).

(b) Draw an example of a union of two convex sets that is convex.

Solution

Take \(A = \{(x,y) \mid x \le 0\}\) and \(B = \{(x,y) \mid x \ge 0\}\). Both are half-planes and \(A \cup B = \mathbb{R}^2\), which is convex. (Alternatively, any two sets where one contains the other.)


Worksheet 6-1: Q4#

Let \(S = \{(1,1), (2,2), (3,1)\}\).

  1. Sketch the convex hull \(\text{conv}(S)\) — it is the triangle with vertices at these three points.

  2. Find coefficients for each point:

    Point \(\mathbf{x}\)

    \(\lambda_1\)

    \(\lambda_2\)

    \(\lambda_3\)

    \((2,2)\)

    \((2,1.5)\)

    \((1.5, 1.5)\)

    \((2, 1)\)

    Solution

    Note: \(\mathbf{x} = \lambda_1(1,1)+\lambda_2(2,2)+\lambda_3(3,1)\), i.e., \(x = \lambda_1+2\lambda_2+3\lambda_3\) and \(y = \lambda_1+2\lambda_2+\lambda_3\), with \(\lambda_1+\lambda_2+\lambda_3=1\).

    Point \(\mathbf{x}\)

    \(\lambda_1\)

    \(\lambda_2\)

    \(\lambda_3\)

    \((2,2)\)

    \(0\)

    \(1\)

    \(0\)

    \((2,1.5)\)

    \(0\)

    \(1/2\)

    \(1/2\)

    \((1.5, 1.5)\)

    \(1/2\)

    \(1/2\)

    \(0\)

    \((2, 1)\)

    \(1/3\)

    \(0\)

    \(2/3\)

  3. Identify the point for each set of coefficients:

    \(\lambda_1\)

    \(\lambda_2\)

    \(\lambda_3\)

    Point \(\mathbf{x}\)

    \(1/3\)

    \(1/3\)

    \(1/3\)

    \(1/2\)

    \(0\)

    \(1/2\)

    \(0\)

    \(1/4\)

    \(3/4\)

    Solution

    \(\lambda_1\)

    \(\lambda_2\)

    \(\lambda_3\)

    Point \(\mathbf{x}\)

    \(1/3\)

    \(1/3\)

    \(1/3\)

    \((2, 4/3)\) — centroid

    \(1/2\)

    \(0\)

    \(1/2\)

    \((2, 1)\) — midpoint of base

    \(0\)

    \(1/4\)

    \(3/4\)

    \((2.75, 1.25)\)


Worksheet 6-1: Q5#

Let \(S = \{(1,1), (1,2), (2,1), (2,2)\}\).

  1. Sketch \(S\) and its convex hull — it is the unit square \([1,2]\times[1,2]\).

  2. What is the maximum number of points from \(S\) needed to represent any point in \(\text{conv}(S)\) as a convex combination?

    Solution

    By Carathéodory’s theorem in \(\mathbb{R}^2\): any point in the convex hull can be written as a convex combination of at most \(2+1 = \mathbf{3}\) points.

  3. Write the point \(\mathbf{x} = (1.5, 1.4)\) as a convex combination of points in \(S\).

    Solution

    One valid decomposition uses 3 points: $\(\mathbf{x} = (1.5, 1.4) = 0.6(1,1) + 0(1,2) + 0(2,1) + 0.4(2,2)?\)\( Check: \)0.6(1,1)+0.4(2,2) = (0.6+0.8, 0.6+0.8) = (1.4, 1.4) \ne (1.5, 1.4)$.

    Try: \(\lambda_1(1,1) + \lambda_3(2,1) + \lambda_4(2,2)\) with \(\lambda_1+\lambda_3+\lambda_4=1\): $\(x: \lambda_1 + 2\lambda_3 + 2\lambda_4 = 1.5, \quad y: \lambda_1 + \lambda_3 + 2\lambda_4 = 1.4\)\( Subtracting: \)\lambda_3 = 0.1\(, then \)\lambda_1 + 2(0.1) + 2\lambda_4 = 1.5 \Rightarrow \lambda_1 + 2\lambda_4 = 1.3\(, and \)\lambda_1 + 0.1 + 2\lambda_4 = 1.4 \Rightarrow \lambda_1 + 2\lambda_4 = 1.3\( ✓. With \)\lambda_1+\lambda_3+\lambda_4=1\(: \)\lambda_1 + \lambda_4 = 0.9\(. From \)\lambda_1 + 2\lambda_4 = 1.3\(: \)\lambda_4 = 0.4\(, \)\lambda_1 = 0.5$.

    \[\mathbf{x} = 0.5(1,1) + 0.1(2,1) + 0.4(2,2) = (0.5+0.2+0.8,\, 0.5+0.1+0.8) = (1.5, 1.4) \checkmark\]