Random Sampling
Description
Random Sampling is an algorithm which, simply, randomly creates a new candidate solution, usually by uniformly sampling the search space. (uniform sampling means that each possible genotype has the same probability of being chosen)
Definitions
$$f \gets \text{the objective/fitness function}$$ $$terminationCriteria \gets \text{the termination criterion}$$ $$x \gets \text{the new solution}$$ $$\textit{Best} \gets \text{the best individual ever discovered}$$
References
Thomas Weise - Metaheuristic Optimization
Pseudo Code
\begin{algorithm} \caption{RS Algorithm} \begin{algorithmic} \STATE $\textit{Best} \gets Null$ \WHILE{$terminationCriteria$} \STATE $x \gets random()$ \IF{$f(\textit{Best}) \geq f(x)$ or $\textit{Best} == Null$} \STATE $\textit{Best} \gets x$ \ENDIF \ENDWHILE \RETURN $\textit{Best}$ \end{algorithmic} \end{algorithm}