Research on Multi-Dimensional Optimal Location Selection of Maintenance Station Based on Big Data of Vehicle Trajectory
In order to rationally lay out the location of automobile maintenance service stations, a method of location selection of maintenance service stations based on vehicle trajectory big data is proposed. Taking the vehicle trajectory data as the demand points, the demand points are divided according to...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-04-01
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| Series: | Entropy |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1099-4300/23/5/495 |
| _version_ | 1797536931777609728 |
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| author | Shoujing Zhang Fujiao Tong Mengdan Li Shoufeng Jin Zhixiong Li |
| author_facet | Shoujing Zhang Fujiao Tong Mengdan Li Shoufeng Jin Zhixiong Li |
| author_sort | Shoujing Zhang |
| collection | DOAJ |
| description | In order to rationally lay out the location of automobile maintenance service stations, a method of location selection of maintenance service stations based on vehicle trajectory big data is proposed. Taking the vehicle trajectory data as the demand points, the demand points are divided according to the region by using the idea of zoning, and the location of the second-level maintenance station is selected for each region. The second-level maintenance stations selected in the whole country are set as the demand points of the first-level maintenance stations. Considering the objectives of the two dimensions of cost and service level, the location model of the first-level maintenance stations under two-dimensional programming is established, and the improved particle swarm optimization algorithm and immune algorithm, respectively, are used to solve the problem. In this way, the first-level maintenance stations in each region are obtained. The example verification shows that the location selection results for the maintenance stations using the vehicle trajectory big data are reasonable and closer to the actual needs. |
| first_indexed | 2024-03-10T12:07:52Z |
| format | Article |
| id | doaj.art-aa9a60ba376b4808ac9cd8c1bc5e33c7 |
| institution | Directory Open Access Journal |
| issn | 1099-4300 |
| language | English |
| last_indexed | 2024-03-10T12:07:52Z |
| publishDate | 2021-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Entropy |
| spelling | doaj.art-aa9a60ba376b4808ac9cd8c1bc5e33c72023-11-21T16:28:02ZengMDPI AGEntropy1099-43002021-04-0123549510.3390/e23050495Research on Multi-Dimensional Optimal Location Selection of Maintenance Station Based on Big Data of Vehicle TrajectoryShoujing Zhang0Fujiao Tong1Mengdan Li2Shoufeng Jin3Zhixiong Li4Xi’an Key Laboratory of Modern Intelligent Textile Equipment, College of Mechanical and Electrical Engineering, Xi’an Polytechnic University, Xi’an 710048, ChinaXi’an Key Laboratory of Modern Intelligent Textile Equipment, College of Mechanical and Electrical Engineering, Xi’an Polytechnic University, Xi’an 710048, ChinaXi’an Key Laboratory of Modern Intelligent Textile Equipment, College of Mechanical and Electrical Engineering, Xi’an Polytechnic University, Xi’an 710048, ChinaXi’an Key Laboratory of Modern Intelligent Textile Equipment, College of Mechanical and Electrical Engineering, Xi’an Polytechnic University, Xi’an 710048, ChinaYonsei Frontier Lab, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul 03722, KoreaIn order to rationally lay out the location of automobile maintenance service stations, a method of location selection of maintenance service stations based on vehicle trajectory big data is proposed. Taking the vehicle trajectory data as the demand points, the demand points are divided according to the region by using the idea of zoning, and the location of the second-level maintenance station is selected for each region. The second-level maintenance stations selected in the whole country are set as the demand points of the first-level maintenance stations. Considering the objectives of the two dimensions of cost and service level, the location model of the first-level maintenance stations under two-dimensional programming is established, and the improved particle swarm optimization algorithm and immune algorithm, respectively, are used to solve the problem. In this way, the first-level maintenance stations in each region are obtained. The example verification shows that the location selection results for the maintenance stations using the vehicle trajectory big data are reasonable and closer to the actual needs.https://www.mdpi.com/1099-4300/23/5/495internet of vehicles big datamaintenance station locationk-means algorithmimproved particle swarm algorithmimmune algorithm |
| spellingShingle | Shoujing Zhang Fujiao Tong Mengdan Li Shoufeng Jin Zhixiong Li Research on Multi-Dimensional Optimal Location Selection of Maintenance Station Based on Big Data of Vehicle Trajectory Entropy internet of vehicles big data maintenance station location k-means algorithm improved particle swarm algorithm immune algorithm |
| title | Research on Multi-Dimensional Optimal Location Selection of Maintenance Station Based on Big Data of Vehicle Trajectory |
| title_full | Research on Multi-Dimensional Optimal Location Selection of Maintenance Station Based on Big Data of Vehicle Trajectory |
| title_fullStr | Research on Multi-Dimensional Optimal Location Selection of Maintenance Station Based on Big Data of Vehicle Trajectory |
| title_full_unstemmed | Research on Multi-Dimensional Optimal Location Selection of Maintenance Station Based on Big Data of Vehicle Trajectory |
| title_short | Research on Multi-Dimensional Optimal Location Selection of Maintenance Station Based on Big Data of Vehicle Trajectory |
| title_sort | research on multi dimensional optimal location selection of maintenance station based on big data of vehicle trajectory |
| topic | internet of vehicles big data maintenance station location k-means algorithm improved particle swarm algorithm immune algorithm |
| url | https://www.mdpi.com/1099-4300/23/5/495 |
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