Abstract
The big data revolution is here and now. We are currently observing the explosion of data generated in virtually all fields of science, business, and engineering, including-among others-medical image analysis, satellite imaging, banking, and agriculture. Transportation systems are not an exception here-collecting and analyzing data can help build better (meta)heuristics for solving rich vehicle routing problems (VRPs) using data-driven algorithms. In this chapter, we review the current advances in machine learning-powered approaches applied to solve different variants of VRPs and show how effective data mining can boost the capabilities of existent optimization techniques. Finally, we discuss how machine learning and deep learning in particular are exploited in smart delivery systems.
| Original language | English |
|---|---|
| Title of host publication | Smart Delivery Systems |
| Subtitle of host publication | Solving Complex Vehicle Routing Problems |
| Publisher | Elsevier |
| Pages | 203-226 |
| Number of pages | 24 |
| ISBN (Electronic) | 9780128157152 |
| DOIs | |
| Publication status | Published - 1 Jan 2019 |
Keywords
- Combinatorial optimization
- Deep learning
- Hybrid algorithms
- Machine learning
- Smart delivery systems
ASJC Scopus subject areas
- General Social Sciences
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