Comparison of Optimization Algorithms Using IPOPT, 100 Runs

A comparison of different optimization algorithms using the IPOPT solver on the same model. The dataset contains results from 100 runs using a lockdown case scenario with a time step of 0.5. It was authored by Sandra Montes-Olivas and last updated on May 6, 2026.

Use Cases

• Benchmarking algorithm performance based on the reported 100 runs.
• Analyzing the relationship between Hessian non-zero elements and solver efficiency.
• Comparing computational cost based on identical objective and Hessian evaluation counts.

Strengths

• Provides a controlled comparison with 100 runs for statistical reliability.
• Objective function evaluations (183) and Lagrangian Hessian evaluations (128) were identical across all platforms, enabling a fair comparison.
• Released under a permissive CC-BY-4.0 license.

Limitations

• Row count and column-level documentation are absent; field semantics must be inferred after download.
• The dataset is very small (5.5 KB), indicating limited scope and likely a summary of results rather than raw run data.

Provenance

Source

figshare

Collection Method

Results from optimization runs performed on the same model.

Time Range

null

Freshness

Last updated 2026-05 06 17:40:51; freshness should be verified.

Geography

null