Bus-Assisted Drone Delivery Optimization Results

Results from numerical experiments on a bus-assisted heterogeneous-drone logistics model for rural e-commerce. The 9.5 KB Excel file contains algorithm performance data comparing an Improved Black-Kite Algorithm against Gurobi and other metaheuristics. Author Song Jin published the dataset on Figshare in April 2026.

Use Cases

• Compare algorithm performance metrics like total cost, stability, and convergence speed between IBKA, GA, EGO, and BKA.
• Analyze sensitivity of delivery cost to specific model parameters such as drone payload capacity and bus headway.
• Validate optimization results from adapted Solomon instances used for the vehicle routing problem with time windows.
• Benchmark the proposed two-stage framework's cost savings against truck-only and homogeneous-drone delivery modes.

Strengths

• Dataset provides quantified performance improvements: IBKA reduces total cost by 5% vs GA, 9% vs EGO, and 13% vs BKA.
• Includes stability metrics, with IBKA improving stability by 23%, 55%, and 23% compared to the same algorithms.

Limitations

• Dataset is very small at 9.5 KB, indicating limited scope and likely a summary of results rather than raw experimental data.
• No column names or sample data are provided, making the internal structure and specific metrics unclear.

Provenance

Source

Song Jin, published on Figshare.

Collection Method

Generated from numerical experiments on adapted Solomon instances and a real-world case study.

Time Range

null

Freshness

Last updated in April 2026.

Geography

Includes a real-world study on the Xunyang–Tongqianguan line in Shaanxi Province, China.