In order to determine or establish convexity of sets, it is useful to review some operators that preserve the convexity.

Intersection

Firstly, convexity is preserved under intersection. Namely, if $C_1$ and $C_2$ are convex then $C_1\cap C_2$ is convex.

A set $C$ is called a convex cone if $C$ is a cone and $C$ is convex, i.e. for any $x_1,x_2\in C$ and $\lambda_1, \lambda_2 \geqslant0$ we have

$$\lambda_1x_1 +\lambda_2x_2\in C.$$

Conic combination

A conic combination of the points $x_1,\ldots, x_n$ is a point of form $\lambda_1x_1+\ldots+\lambda_nx_n$ with $\lambda_i\geqslant0\ \ \forall i=1,\ldots,n$.

The following table shows the difference between affine combination, convex combination and conic combination

Affine combination	Convex combination	Conic combination
Form: $\ \lambda_1x_1 +\ldots+ \lambda_nx_n$	Form: $\ \lambda_1x_1 +\ldots+ \lambda_nx_n$	Form: $\ \lambda_1x_1 +\ldots+ \lambda_nx_n$
Where $\ \lambda_i\in\mathbb R$ and $\sum_{i=1}^n \lambda_i=1$	Where $\ \lambda_i\geqslant0 $ and $\sum_{i=1}^n \lambda_i=1$	Where $\ \lambda_i\geqslant0$

Conic hull

The set of all conic combination of points in $C$ is called the conic hull of $C$

$$\text{cone}(C) = \left\{ \sum_{i=1}^n \lambda_i x_i\ \Big|\ \ x_i\in C \text{ and } \lambda_i\geqslant 0 \ \ \forall i=1,\ldots,n\right\}.$$

Tip: In the definition of conic hull, we only need $\lambda_i\geqslant0$

convex