The noising methods: A generalization of some metaheuristics

In this paper, an exhaustive review of the principles and of the applications of the noising methods, recent combinatorial optimization metaheuristics, is attempted. The features and the variants of the noising methods are detailed and the tunings of their parameters when applied to different combinatorial optimization problems are summarized. The links between the noising methods and two other metaheuristics (namely, the simulated annealing method and the threshold accepting algorithm) are also studied and that the noising methods can be considered as generalizations of these metaheuristics when their components are properly chosen is shown.