Affiliation:
1. College of Electronic Information and Automation, Civil Aviation University of China, Tianjin 300300, China
Abstract
With the increased demands of airlines, it is important to study the location selection strategy for spare parts central warehouse in order to improve the allocation capacity of spare parts maintenance resources and reduce the operating costs of airlines. Based on the M/M/s/∞/∞ multiservice desk model and Multi-Echelon Technique for Recoverable Item Control (METRIC) theory, this paper proposes a spare parts supply strategy based on the spare parts pool network and establishes a location selection model for spare parts central warehouse. The particle swarm optimization (PSO) algorithm is used to iteratively optimize the location for spare parts central warehouse and adjust the location area of the central warehouse combining transportation facilities and geographical environment factors. Finally, the paper compares the operating results for multiple airlines in pooling and off-pooling states and verifies the effectiveness of the spare parts supply model and the advantages of cost control for airlines.
Subject
General Mathematics,General Medicine,General Neuroscience,General Computer Science
Reference40 articles.
1. Method of Spare Parts Prediction Models Evaluation Based on Grey Comprehensive Correlation Degree and Association Rules Mining: A Case Study in Aviation
2. Review on the civil aircraft spare parts prediction and configuration management technology;Y. Feng;Advances in Aeronautical Science and Engineering,2020
3. A two-echelon two-indenture inventory model for repairable spare parts based on VMI;J. Xu;Aircraft Design,2015
4. Forecasting spare part demand with installed base information: A review;S. Van der Auweraer;International Journal of Forecasting,2018
5. Optimal inventory modeling of spare parts under the criticality;Z. Cai;Systems Engineering and Electronics,2017
Cited by
4 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献