# Exponential Cone Example

In this example we show how to model optimization problems with exponential cone constraints. The exponential cone is defined as

\begin{aligned} \mathcal{K}_{exp} =& \{(x, y, z) \mid y \geq 0,~ ye^{x/y} \le z\} ~\cup~ \\ & \{ (x,y,z) \mid x \leq 0, y = 0, z \geq 0 \} \end{aligned}

We will solve the following optimization problem:

$$$\begin{array}{ll} \text{maximize} &x\\[2ex] \text{subject to} & \begin{array}{rl} y e^{x / y} &\!\le~z \\ y \!&=~1\\ z \!&=~e^5. \end{array} \end{array}$$$

### Objective function

The Clarabel solver's default configuration expects problems to be posed as minimization problems, so we define:

$$$P = 0 \textrm{~~~and~~~} q = - \begin{bmatrix} 1 & 0 & 0 \end{bmatrix}^T.$$$

### Constraints

The solver's default configuration expects constraints in the form $Ax + s = b$, where $s$ is in a cone or composition of cones. In this case we can write

$$$\begin{bmatrix} 0 \\ 0 \\ 0 \end{bmatrix} - I \begin{bmatrix} x \\ y \\ z \end{bmatrix} = s \in \mathcal{K}_{exp},$$$

and then append the two additional equality constraints.