Research on Location Selection Strategy for Airlines Spare Parts Central Warehouse Based on METRIC
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 mod...
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| Veröffentlicht in: | Computational intelligence and neuroscience 2021, Vol.2021 (1), p.4737700-4737700 |
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| creator | Wang, Rui Qin, Yicong Sun, Hui |
| description | 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. |
| doi_str_mv | 10.1155/2021/4737700 |
| format | Article |
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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.</description><identifier>ISSN: 1687-5265</identifier><identifier>EISSN: 1687-5273</identifier><identifier>DOI: 10.1155/2021/4737700</identifier><identifier>PMID: 34456993</identifier><language>eng</language><publisher>New York: Hindawi</publisher><subject>Aging ; Airlines ; Algorithms ; Analysis ; Aviation ; Cost control ; Logistics ; Mathematical optimization ; Operating costs ; Optimization ; Particle swarm optimization ; Preventive maintenance ; Queuing theory ; Site selection ; Spare parts ; Turnover ; Warehouse stores ; Warehouses</subject><ispartof>Computational intelligence and neuroscience, 2021, Vol.2021 (1), p.4737700-4737700</ispartof><rights>Copyright © 2021 Rui Wang et al.</rights><rights>COPYRIGHT 2021 John Wiley & Sons, Inc.</rights><rights>Copyright © 2021 Rui Wang et al. This is an open access article distributed under the Creative Commons Attribution License (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 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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. 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| subjects | Aging Airlines Algorithms Analysis Aviation Cost control Logistics Mathematical optimization Operating costs Optimization Particle swarm optimization Preventive maintenance Queuing theory Site selection Spare parts Turnover Warehouse stores Warehouses |
| title | Research on Location Selection Strategy for Airlines Spare Parts Central Warehouse Based on METRIC |
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