```markdown
## Quasiconvex Optimization

### Problem Statement
- **Objective:** Minimize \( f_0(x) \)
- **Subject to:** 
  - \( f_i(x) \leq 0, \quad i = 1, \ldots, m \)
  - \( Ax = b \)

### Conditions
- \( f_0: \mathbb{R}^n \to \mathbb{R} \) is quasiconvex.
- \( f_1, \ldots, f_m \) are convex.

### Illustration
- The image includes a graph depicting a curve with a labeled point \((x, f_0(x))\).
- It demonstrates that quasiconvex optimization can have locally optimal points that are not globally optimal.

### Source
- A. d’Aspremont. Convex Optimization M2.
```
