Warehouse & Logistics
Logistics & International Trade
Belt and Road Logistics Network Optimization
Asia-Europe Corridor
Data-Driven Infrastructure Planning for Global Trade
Novel two-stage method combining Machine Learning and Complex Network analysis to optimize dry port locations and service areas across the Belt and Road corridor for maximum logistics efficiency.
14 developers & analysts
10 months
Key Results:
- 30% improvement in logistics efficiency
- 25% reduction in transportation costs
- Optimized network for 50+ dry port locations
Technologies Used:
PythonNetworkXApache SparkGIS
Applied advanced complex network theory to real-world infrastructure planning
Challenge
Optimizing dry port locations and service areas across the Belt and Road corridor for maximum efficiency. Complex international trading patterns required sophisticated network analysis and location optimization algorithms.
Solution
Innovative approach using Machine Learning and Complex Network analysis with Eigenvector Centrality ranking from association rule networks. Gravity-based community detection validated on Belt and Road data for Mainland China.
Key Features
- Machine Learning for location optimization
- Complex Network analysis with Eigenvector Centrality
- Association rule mining for trade pattern analysis
- Gravity-based community detection algorithms
Results Achieved
30%
improvement in logistics efficiency
25%
reduction in transportation costs
50+
dry port locations optimized
Real-time
analysis of international trading data
Strategic
alignment with Belt and Road development plans