Simulated annealing based on local genetic search

The flexible architecture of evolutionary algorithms allows specialised models to be obtained with the aim of resembling other algorithms, but performing more satisfactorily. In fact, several evolutionary proposals playing the role of local search methods have been proposed in the literature. In this paper, we make a step forward extending an innovative model recently proposed, which performs local search on external solutions, to match search process carried out by simulated annealing. We introduce acceptance criterion and cooling scheme concepts from simulated annealing, and modify some original components to better suit the new search process performed. An empirical study comparing the new model with classical simulated annealing algorithms shows that 1) the proposal is often able to reach good fitness values before than its competitors and 2) it suffers weaker convergence speed reductions that allow it to fruitfully continue the search process.