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

Chen Bing, Sun Shouqun and Liu Gang

Modern Applied Science, 2012, vol. 6, issue 6, 12

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.

Date: 2012
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://ccsenet.org/journal/index.php/mas/article/download/17079/11379 (application/pdf)
https://ccsenet.org/journal/index.php/mas/article/view/17079 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ibn:masjnl:v:6:y:2012:i:6:p:12

Access Statistics for this article

More articles in Modern Applied Science from Canadian Center of Science and Education Contact information at EDIRC.
Bibliographic data for series maintained by Canadian Center of Science and Education ().