A Heuristic Approach for a Real-World Electric Vehicle Routing Problem
To develop a non-polluting and sustainable city, urban administrators encourage logistics companies to use electric vehicles instead of conventional (i.e., fuel-based) vehicles for transportation services. However, electric energy-based limitations pose a new challenge in designing reasonable visiti...
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2019-02-01
|
| Series: | Algorithms |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1999-4893/12/2/45 |
| _version_ | 1828883861654732800 |
|---|---|
| author | Mengting Zhao Yuwei Lu |
| author_facet | Mengting Zhao Yuwei Lu |
| author_sort | Mengting Zhao |
| collection | DOAJ |
| description | To develop a non-polluting and sustainable city, urban administrators encourage logistics companies to use electric vehicles instead of conventional (i.e., fuel-based) vehicles for transportation services. However, electric energy-based limitations pose a new challenge in designing reasonable visiting routes that are essential for the daily operations of companies. Therefore, this paper investigates a real-world electric vehicle routing problem (VRP) raised by a logistics company. The problem combines the features of the capacitated VRP, the VRP with time windows, the heterogeneous fleet VRP, the multi-trip VRP, and the electric VRP with charging stations. To solve such a complicated problem, a heuristic approach based on the adaptive large neighborhood search (ALNS) and integer programming is proposed in this paper. Specifically, a charging station adjustment heuristic and a departure time adjustment heuristic are devised to decrease the total operational cost. Furthermore, the best solution obtained by the ALNS is improved by integer programming. Twenty instances generated from real-world data were used to validate the effectiveness of the proposed algorithm. The results demonstrate that using our algorithm can save 7.52% of operational cost. |
| first_indexed | 2024-12-13T10:56:31Z |
| format | Article |
| id | doaj.art-ee3a2e4c2726426199d95e20418f9f83 |
| institution | Directory Open Access Journal |
| issn | 1999-4893 |
| language | English |
| last_indexed | 2024-12-13T10:56:31Z |
| publishDate | 2019-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Algorithms |
| spelling | doaj.art-ee3a2e4c2726426199d95e20418f9f832022-12-21T23:49:30ZengMDPI AGAlgorithms1999-48932019-02-011224510.3390/a12020045a12020045A Heuristic Approach for a Real-World Electric Vehicle Routing ProblemMengting Zhao0Yuwei Lu1School of Automobile and Traffic Engineering, Wuhan University of Science and Technology, Wuhan 430065, ChinaSchool of Mechanical Engineering, Guangxi University of Science and Technology, Liuzhou 545006, ChinaTo develop a non-polluting and sustainable city, urban administrators encourage logistics companies to use electric vehicles instead of conventional (i.e., fuel-based) vehicles for transportation services. However, electric energy-based limitations pose a new challenge in designing reasonable visiting routes that are essential for the daily operations of companies. Therefore, this paper investigates a real-world electric vehicle routing problem (VRP) raised by a logistics company. The problem combines the features of the capacitated VRP, the VRP with time windows, the heterogeneous fleet VRP, the multi-trip VRP, and the electric VRP with charging stations. To solve such a complicated problem, a heuristic approach based on the adaptive large neighborhood search (ALNS) and integer programming is proposed in this paper. Specifically, a charging station adjustment heuristic and a departure time adjustment heuristic are devised to decrease the total operational cost. Furthermore, the best solution obtained by the ALNS is improved by integer programming. Twenty instances generated from real-world data were used to validate the effectiveness of the proposed algorithm. The results demonstrate that using our algorithm can save 7.52% of operational cost.https://www.mdpi.com/1999-4893/12/2/45transport optimizationmetaheuristicselectric vehiclesroutingadaptive large neighborhood search |
| spellingShingle | Mengting Zhao Yuwei Lu A Heuristic Approach for a Real-World Electric Vehicle Routing Problem Algorithms transport optimization metaheuristics electric vehicles routing adaptive large neighborhood search |
| title | A Heuristic Approach for a Real-World Electric Vehicle Routing Problem |
| title_full | A Heuristic Approach for a Real-World Electric Vehicle Routing Problem |
| title_fullStr | A Heuristic Approach for a Real-World Electric Vehicle Routing Problem |
| title_full_unstemmed | A Heuristic Approach for a Real-World Electric Vehicle Routing Problem |
| title_short | A Heuristic Approach for a Real-World Electric Vehicle Routing Problem |
| title_sort | heuristic approach for a real world electric vehicle routing problem |
| topic | transport optimization metaheuristics electric vehicles routing adaptive large neighborhood search |
| url | https://www.mdpi.com/1999-4893/12/2/45 |
| work_keys_str_mv | AT mengtingzhao aheuristicapproachforarealworldelectricvehicleroutingproblem AT yuweilu aheuristicapproachforarealworldelectricvehicleroutingproblem AT mengtingzhao heuristicapproachforarealworldelectricvehicleroutingproblem AT yuweilu heuristicapproachforarealworldelectricvehicleroutingproblem |