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	{\KwIn{Set $E$ of elements constituting a solution; incremental cost function $c(s, e)$; fitness function $f$ to minimize, parameters \textcolor{myevidence}{$I_{max}$ and $0 \leqslant \alpha \leqslant 1$}, improvement method \textcolor{myevidence}{$local\_ search$}}
		\KwResult{Complete solution $s^*$}
		$f^* \leftarrow \infty$\\
		\For{\textcolor{myevidence}{$I_{max}$ iterations}}
		{ Initialize $s$ to a trivial partial solution\\
			$R \leftarrow E$\tcp*[r]{Elements that can be added to $s$}
			\While{$R \neq \varnothing$ }
			{\textcolor{myevidence}{Find $c_{min} = \min_{e \in R}{c(s, e)}$ and $c_{max} = \max_{e \in R}{c(s, e)}$}\\
				\textcolor{myevidence}{Choose randomly, uniformly $e' \in R$ such that  $c_{min} \leqslant c(s, e') \leqslant c_{min} + \alpha (c_{max} - c_{min})$}\\
				$s \leftarrow s \cup e'$\tcp*[r]{Include $e'$ in the partial solution $s$}
				Remove from $R$ the elements that cannot be added any more to $s$\\
			}
			\textcolor{myevidence}{$s' \leftarrow local\_ search(s)$}\tcp*[r]{Find the local optimum associated with $s$}
			\If{$f^* > f(s')$}
			{$f^* \leftarrow f(s')$\\
				$s^* \leftarrow s'$
			}
		}
	}

