Bus-Assisted Drone Delivery Optimization Model Results

Numerical experiment results from a study proposing a bus-assisted heterogeneous-drone scheme for rural logistics. The dataset contains performance metrics for an Improved Black-Kite Algorithm (IBKA) tested on adapted Solomon instances, showing cost reductions of 5-13% compared to benchmark algorithms. Song Jin published this data on figshare in April 2026.

Use Cases

• Compare algorithm performance metrics like total cost and stability between IBKA, Gurobi, GA, EGO, and BKA.
• Analyze sensitivity test results for parameters such as drone payload and bus headway.
• Validate the mixed-integer programming model's outputs from the real-world Xunyang–Tongqianguan line case study.

Strengths

• Algorithm performance is validated against four established benchmarks (Gurobi, GA, EGO, BKA).
• Includes a real-world case study from the Xunyang–Tongqianguan line in Shaanxi Province.

Limitations

• The dataset is very small at 9.5 KB, indicating limited scope and likely a summary of results rather than raw simulation data.
• Specific input data, column names, and row counts are not provided, limiting reproducibility.

Provenance

Source

Song Jin via 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 case study from the Xunyang–Tongqianguan line in Shaanxi Province, China.