Abstract
The optimization of urban emergency supplies transportation can effectively improve disaster relief efficiency and reduce disaster losses. In this study, a multi-objective location-routing problem (LRP) model is established aiming at minimizing the time, route length, and cost in urban emergency rescue. Moreover, an improved ant colony algorithm is designed to solve this model. In this algorithm, the pheromone updating strategy and heuristic factor are enhanced considering the disadvantages of ant colony algorithm. Finally, combining with the risk slope control works in Shenzhen, China, empirical studies are conducted in 30 dangerous slopes in Baoan District, Shenzhen to verify the feasibility and effectiveness of the improved ant colony algorithm.
| Original language | English |
|---|---|
| Pages | 472-478 |
| Number of pages | 7 |
| Volume | 160 |
| No | 12 |
| Specialist publication | Sensors and Transducers |
| State | Published - 2013 |
| Externally published | Yes |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 11 Sustainable Cities and Communities
Keywords
- Ant colony algorithm
- Emergency logistics
- Emergency management
- LRP
- Urban emergency
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