Abstract

With respect to the problem of complexity and uncertainty in the MRO (Maintenance, Repair and Overhaul) spare parts inventory, an optimized grey forecasting model is employed to forecast the demand of spare parts. The parameter g is optimized based on genetic algorithm (GA) method in the unbiased GM (1, 1) power model to minimize the ARPE (Average Relative Proportional Error) of accuracy. And the optimal model is used to forecast the prediction demand in a practical example. The experiment results indicate the forecasting accuracy can be accepted by using the optimized unbiased GM (1, 1) power model.

This work is licensed under a Creative Commons Attribution 4.0 License.