Summary of Mvmoe: Multi-task Vehicle Routing Solver with Mixture-of-experts, by Jianan Zhou et al.
MVMoE: Multi-Task Vehicle Routing Solver with Mixture-of-Experts
by Jianan Zhou, Zhiguang Cao, Yaoxin Wu, Wen Song, Yining Ma, Jie Zhang, Chi Xu
First submitted to arxiv on: 2 May 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: Machine Learning (cs.LG)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This paper focuses on developing a unified neural solver for vehicle routing problems (VRPs) that can handle various VRP variants simultaneously. The proposed multi-task vehicle routing solver with mixture-of-experts (MVMoE) is designed to enhance model capacity without increasing computational complexity. A hierarchical gating mechanism is introduced, which achieves a good balance between empirical performance and computation. Experimental results show significant zero-shot generalization performance on 10 unseen VRP variants, decent results on the few-shot setting, and real-world benchmark instances. The paper also investigates the effect of MoE configurations in solving VRPs and demonstrates the superiority of hierarchical gating when handling out-of-distribution data. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This research aims to create a smart way to solve different types of vehicle routing problems. Usually, these solutions are designed for specific problems only, making them less useful for other situations. The authors propose a new approach that can handle many different vehicle routing problems at once. They call this approach “multi-task vehicle routing solver with mixture-of-experts” and show it works well in various scenarios. The results suggest that their method is effective even when dealing with new or unexpected data. |
Keywords
» Artificial intelligence » Few shot » Generalization » Mixture of experts » Multi task » Zero shot
