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ijoc-methods
Use when the method choice, baselines, and computational-experiment design need alignment for an INFORMS Journal on Computing (IJOC) manuscript — before the experiments are run at scale. Designs a fair, reproducible experimental protocol; it does not write the algorithm proofs (see ijoc-theory-development).
INFORMS-Journal-on-Computing-Skills/skills/ijoc-methods/SKILL.md
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# Method & Experimental Design (ijoc-methods)
## When to trigger
- The algorithm is settled but the **experimental protocol** (instances, baselines, tuning, hardware, metrics) is not designed
- You are about to run experiments and want to avoid a protocol a referee will reject after the fact
- A referee challenges the **fairness** of a comparison (asymmetric tuning, mismatched time limits, weak baseline)
- You must choose **what to measure** so the computational claim is actually supported
## Designing an IJOC-grade computational experiment
At IJOC the experiment *is* the evidence, so it is held to a high methodological standard. Design it before running it, around five pillars. Getting these right up front is cheaper than re-running after an R&R.
1. **Instances.** Use **public, standard benchmark sets** wherever they exist (e.g., MIPLIB-class libraries, TSPLIB-style, established generators) so results are comparable and not cherry-picked. If you must generate instances, document the generator, the parameter ranges, and the seeds, and deposit them. Report the size distribution; do not test only on the sizes where you win.