Name
Abstract | ||
|---|---|---|
Vehicle routing problems (VRPs) are classical NP-hard problems. Those large scale and complex VRPs are even challenging. In this paper, we provide a general description of VRPs with heterogeneous constraints. For solving such type of VRPs in considerable solution quality and reasonable time, neighborhood search is a preferred choice. However, during the neighborhood search process, we may encounter a problem that the size of the neighboring solutions is still quite large, which consumes a great deal of computational resources. To tackle this problem, we propose a restricted neighborhood search method, which can ignore those non-promising neighboring solutions in a heuristic manner. Experiments on a real-world dataset show that our method can significantly accelerate the neighborhood search process, while the quality of the resultant solution is not impaired. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/ICNSC.2019.8743332 | 2019 IEEE 16th International Conference on Networking, Sensing and Control (ICNSC) |
Keywords | Field | DocType |
vehicle routing,large scale optimization,restricted neighborhood search,logistics | Vehicle routing problem,Heuristic,Mathematical optimization,Computer science,Control engineering,Neighborhood search | Conference |
ISSN | ISBN | Citations |
1810-7869 | 978-1-7281-0085-2 | 0 |
PageRank | References | Authors |
0.34 | 6 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hong Liu | 1 | 0 | 0.34 |
| Zizhen Zhang | 2 | 100 | 17.27 |
| Xiwang Guo | 3 | 34 | 2.67 |