Joint scheduling of spare parts production and service engineers based on progressive Pareto algorithm

We analyse the joint scheduling of spare parts production and service engineers in a multi-site maintenance system. In the system, for each failure, a service engineer with the required spare part needs to be allocated for on-site maintenance. If one of the required resources is not readily available, the maintenance task can be satisfied via an external channel with quick responsiveness but high involved costs. Service providers need to make an efficient plan, including production scheduling of spare parts, allocation of service engineers and outsourcing strategy. First, a mathematical model with the objectives of minimum total outsourcing costs and minimum weighted tardiness is formulated. Then, a novel and knowledge-based heuristic algorithm is developed, namely progressive Pareto algorithm based on step-size (PPAS). To verify the performance of PPAS, it is compared against other well-known algorithms, including NSGA-II, MOEA/D, NNIA, RIPG, MMOIG and MNNIA. Finally, the effectiveness of the joint scheduling mode is demonstrated by comparing it with the separate optimisation mode of spare parts production and workforce allocation.

Automated summary

We study the joint scheduling of spare parts production and service engineers in a multi-site maintenance system. A mathematical model is formulated to minimize total outsourcing costs and weighted tardiness. We propose a novel heuristic algorithm, PPAS, and compare it with other well-known algorithms. The effectiveness of the joint scheduling mode is demonstrated by comparing it with the separate optimization mode.