Iterated Local Search for the Generator Maintenance Scheduling Problem

We consider the task of devising an effective metaheuristic for a variant of the preventive maintenance scheduling problem (PMSP) — the (power) generator maintenance scheduling problem (GMSP). Recent research on metaheuristics for this problem has made progress on it, but the potential economic benefits of effective methods is significant in this area, and warrants further focused work. We propose here a solution method based on Iterated Local Search (ILS) following an earlier study by us on neighbourhood search for the same task. Several extensions to a basic ILS design are developed and analysed, including specialised operators and delta-evaluation, as well as restart and portfolio strategies. With these methods, we obtain a significant improvement in performance (in terms of solution quality, runtime and function evaluations) over recent techniques for real-world derived instances of the GMSP. We also provide a benchmark (and results on additional benchmark instances) for future studies of this problem.