Vehicle Routing Optimization System with Smart Geopositioning Updates
Solving the vehicle routing problem (VRP) is one of the best-known optimization issues in the TLS (transport, logistic, spedition) branch market. Various variants of the VRP problem have been presented and discussed in the literature for many years. In most cases, batch versions of the problem are c...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-11-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/11/22/10933 |
| _version_ | 1827677421148569600 |
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| author | Radosław Belka Mateusz Godlewski |
| author_facet | Radosław Belka Mateusz Godlewski |
| author_sort | Radosław Belka |
| collection | DOAJ |
| description | Solving the vehicle routing problem (VRP) is one of the best-known optimization issues in the TLS (transport, logistic, spedition) branch market. Various variants of the VRP problem have been presented and discussed in the literature for many years. In most cases, batch versions of the problem are considered, wherein the complete data, including customers’ geographical distribution, is well known. In real-life situations, the data change dynamically, which influences the decisions made by optimization systems. The article focuses on the aspect of geopositioning updates and their impact on the effectiveness of optimization algorithms. Such updates affect the distance matrix, one of the critical datasets used to optimize the VRP problem. A demonstration version of the optimization system was developed, wherein updates are carried out in integration with both open source routing machine and GPS tracking services. In the case of a dynamically changing list of destinations, continuous and effective updates are required. Firstly, temporary values of the distance matrix based on the correction of the quasi-Euclidean distance were generated. Next, the impact of update progress on the proposed optimization algorithms was investigated. The simulation results were compared with the results obtained “manually” by experienced planners. It was found that the upload level of the distance matrix influences the optimization effectiveness in a non-deterministic way. It was concluded that updating data should start from the smallest values in the distance matrix. |
| first_indexed | 2024-03-10T05:43:47Z |
| format | Article |
| id | doaj.art-fe68314c13204799bb518f4008f83cc2 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-10T05:43:47Z |
| publishDate | 2021-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-fe68314c13204799bb518f4008f83cc22023-11-22T22:21:08ZengMDPI AGApplied Sciences2076-34172021-11-0111221093310.3390/app112210933Vehicle Routing Optimization System with Smart Geopositioning UpdatesRadosław Belka0Mateusz Godlewski1Faculty of Electrical Engineering, Automatics and Computer Science, Kielce University of Technology, Al. 1000-lecia P.P.7, 25-314 Kielce, PolandFaculty of Electrical Engineering, Automatics and Computer Science, Kielce University of Technology, Al. 1000-lecia P.P.7, 25-314 Kielce, PolandSolving the vehicle routing problem (VRP) is one of the best-known optimization issues in the TLS (transport, logistic, spedition) branch market. Various variants of the VRP problem have been presented and discussed in the literature for many years. In most cases, batch versions of the problem are considered, wherein the complete data, including customers’ geographical distribution, is well known. In real-life situations, the data change dynamically, which influences the decisions made by optimization systems. The article focuses on the aspect of geopositioning updates and their impact on the effectiveness of optimization algorithms. Such updates affect the distance matrix, one of the critical datasets used to optimize the VRP problem. A demonstration version of the optimization system was developed, wherein updates are carried out in integration with both open source routing machine and GPS tracking services. In the case of a dynamically changing list of destinations, continuous and effective updates are required. Firstly, temporary values of the distance matrix based on the correction of the quasi-Euclidean distance were generated. Next, the impact of update progress on the proposed optimization algorithms was investigated. The simulation results were compared with the results obtained “manually” by experienced planners. It was found that the upload level of the distance matrix influences the optimization effectiveness in a non-deterministic way. It was concluded that updating data should start from the smallest values in the distance matrix.https://www.mdpi.com/2076-3417/11/22/10933optimization systemvehicle routing problemdistance matrixgeopositioning |
| spellingShingle | Radosław Belka Mateusz Godlewski Vehicle Routing Optimization System with Smart Geopositioning Updates Applied Sciences optimization system vehicle routing problem distance matrix geopositioning |
| title | Vehicle Routing Optimization System with Smart Geopositioning Updates |
| title_full | Vehicle Routing Optimization System with Smart Geopositioning Updates |
| title_fullStr | Vehicle Routing Optimization System with Smart Geopositioning Updates |
| title_full_unstemmed | Vehicle Routing Optimization System with Smart Geopositioning Updates |
| title_short | Vehicle Routing Optimization System with Smart Geopositioning Updates |
| title_sort | vehicle routing optimization system with smart geopositioning updates |
| topic | optimization system vehicle routing problem distance matrix geopositioning |
| url | https://www.mdpi.com/2076-3417/11/22/10933 |
| work_keys_str_mv | AT radosławbelka vehicleroutingoptimizationsystemwithsmartgeopositioningupdates AT mateuszgodlewski vehicleroutingoptimizationsystemwithsmartgeopositioningupdates |