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ijoc-theory-development

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Use when the algorithm or model formulation, its correctness, and its theoretical guarantees are the bottleneck for an INFORMS Journal on Computing (IJOC) manuscript. Pins down formulation, complexity, and what the method provably does before experiments are finalized; it does not run the experiments.

INFORMS-Journal-on-Computing-Skills/skills/ijoc-theory-development/SKILL.md

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# Algorithm & Model Formulation (ijoc-theory-development)

## When to trigger

- An algorithm "works" empirically but its **statement, invariants, and termination** are not written down rigorously
- A formulation is proposed but its **validity** (the model exactly captures the problem; the cuts are valid; the relaxation is correct) is asserted, not argued
- A referee asks for **complexity, convergence, approximation ratio, or correctness** and the paper has none
- A heuristic or ML method needs the **theoretical scaffolding** (what it guarantees, when it can fail) that distinguishes IJOC from a pure benchmark paper

## What "theory" means at IJOC

IJOC is not a pure-theory journal, but it expects the **method to be defined and defended**, not just demonstrated. The advance is computational, yet referees want to know *why the method is correct* and *what it provably achieves* before they trust the experiments. Match the rigor to the archetype — an exact method needs validity and finiteness; a heuristic needs a clear procedure and, where possible, bounds; an ML-for-OR method needs a stated learning task and a guarantee or a falsifiable claim. The theory and the experiments must agree: a proven worst case should be visible in the runtime-vs-size plot.

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