This chapter provides a review of the principles and of applications of the noising methods. We detail the features and the variants of the noising methods and we summarize the tunings of their parameters when these methods are applied to different combinatorial optimization problems. We also study the links between the noising methods and other metaheuristics (namely, the simulated annealing method, the threshold accepting algorithm or the descents with mutations).