An efficient maintenance optimisation method for series-parallel systems using stochastic ordering and revenue difference boundaries

Abstract

A critical problem during the maintenance optimisation of series-parallel systems is the large strategy space. To address this issue, existing research largely relies on heuristic algorithms, e.g. genetic algorithm (GA) and ant colony optimisation (ACO). These heuristic algorithms can have a low convergence speed, and the obtained strategy are often not global optimal. Instead of searching an optimal strategy in a large space, this paper focuses on the reduction of optimisation space. After investigating the performance dependence among subsystems, this research develops a new strategy space reduction criterion based on the average revenue difference boundaries. By combining the proposed criterion and an earlier method developed by the authors which is based on the stochastic ordering [1], this research develops an efficient maintenance optimisation algorithm. The simulation study shows that the developed maintenance optimisation algorithm can reduce the strategy space more considerably than that proposed in [1].