This paper presents an effective iterated local search (ILS) for the single machine scheduling problem with periodic machine availability (PMASMSP) that seeks to find a schedule of jobs with the minimum makespan. The PMASMSP is \({\mathcal {N}}{\mathcal {P}}\) -hard and occurs in many production industries, where the efficiency, safety as well as productivity enhancement are directly influenced by maintenance activities in the scheduling of production processes. In our proposed ILS, the perturbation procedure is based on swapping of jobs in different periods, local search procedure follows a series of local search strategies, and acceptance criterion follows two step procedures in which the second step, particularly, is used to prevent ILS to be trapped into deep local optima. We evaluate our proposed ILS on available classes of benchmark instances. Computational results indicate that our proposed ILS dominates the best 3 out of 19 methods and the genetic algorithm designed for this problem. Our proposed ILS finds new best results in 6 out of the 14 categories of benchmark instances. In addition, the use of two step procedures in the acceptance criterion of ILS is also studied to understand the performance of ILS for this problem.
