A multi-stage approach for the thermal generator maintenance scheduling problem

The thermal generator maintenance scheduling problem has been tackled by a variety of traditional optimisation techniques over the years. While these methods can give an optimal solution to small scale problems, they are often inefficient and impractical when applied to larger problems. We employ a multi-stage approach where the problem is decomposed into smaller sub-problems, each of which can be solved much more efficiently by existing algorithms. After each part of the problem has been solved, the results are then recombined to form the solution to the whole problem. Both tabu search and a memetic algorithm have been observed to produce very good results but they take a significant amount of time to run. We utilise both techniques to form the basis of a multi-stage approach to solve the thermal generator maintenance scheduling problem. The results demonstrate that the multi-stage methodology is just as effective for this problem while achieving a significant reduction in run-time