An Optimized Unbiased GM (1, 1) Power Model for Forecasting MRO Spare Parts Inventory

Chen Bing, Sun Shouqun, Liu Gang

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.


Full Text: PDF DOI: 10.5539/mas.v6n6p12

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Modern Applied Science   ISSN 1913-1844 (Print)   ISSN 1913-1852 (Online)

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