Abstract
Delivering goods in an efficient and cost-effective way is always a challenging problem in logistics. In this paper, the multi-depot vehicle routing is focused. To cope with the conflicting requirements, an advanced multi-objective evolutionary algorithm is proposed. Local-search empowered genetic operations and a fuzzy cluster-based initialization process are embedded in the design for performance enhancement. Its outperformance, as compared to existing alternatives, is confirmed by extensive simulations based on numerical datasets and real traffic conditions with various customers’ distributions.
| Original language | English |
|---|---|
| Pages (from-to) | 1337-1344 |
| Journal | International Journal of Computational Intelligence Systems |
| Volume | 10 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - 2017 |
Research Keywords
- Evolutionary algorithm
- Local search
- Multi-depot vehicle routing
- Multi-objective optimization
Publisher's Copyright Statement
- This full text is made available under CC-BY-NC 4.0. https://creativecommons.org/licenses/by-nc/4.0/
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