ijoc-literature-positioning
GitHub用于在IJOC论文中精确定位计算与方法论贡献。通过对比OR/MS与CS前沿，明确需击败的具体基线方法，强调算法增量而非单纯应用，确保对近期竞品进行公平评估与诚实定位，避免被拒稿。
Trigger Scenarios
Install
npx skills add brycewang-stanford/Awesome-Journal-Skills --skill ijoc-literature-positioning -g -y
SKILL.md
Frontmatter
{
"name": "ijoc-literature-positioning",
"description": "Use when staking the computational\/methodological contribution of an INFORMS Journal on Computing (IJOC) manuscript against OR\/MS and CS prior art. Positions the advance relative to the right baselines and the right frontier; it does not invent citations."
}
Literature Positioning (ijoc-literature-positioning)
When to trigger
- Reviewers say "the contribution over existing methods is unclear" or "this is incremental"
- Your related-work section cites application papers but not the algorithmic/computational prior art you actually compete with
- You straddle OR and CS literatures and are unsure which frontier you are advancing
- A referee names a recent method you did not compare against, and you must decide whether it is the relevant baseline
Positioning IJOC papers — two frontiers, one claim
An IJOC paper usually advances against two literatures at once: the OR/MS literature that owns the problem and the computing literature that owns the method. Your positioning must make clear which frontier you push and by how much, in computational terms. The decisive move is to identify the state-of-the-art method you must beat or match, cite it precisely, and commit to it as an experimental baseline. Vague positioning ("little work exists") reads as not having read the field and is a fast path to desk rejection by an Area Editor who knows it well.
| Your claim type | The prior art you must engage | The baseline this implies |
|---|---|---|
| New exact method, larger instances | best published exact method for this problem | re-run or cite its reported results on shared instances |
| New formulation, tighter bounds | strongest existing formulation / relaxation | root-gap and node-count comparison |
| New heuristic, better quality/time | the leading heuristic and the best exact bound | gap-to-optimal and time-to-target |
| ML-for-OR, learns to solve faster | both the OR baseline and prior learning approaches | beat the OR method and prior learning |
| New simulation/estimation method | prior estimators for the same estimand | variance/cost at equal accuracy |
| Software/tooling | prior tools and the methods they implement | feature/performance comparison, not just existence |
Engaging recent work fairly
IJOC reviewers are active researchers in the chosen area; they will know the last two years of work. Cite the most recent competing methods, not only the classics, and state honestly where a competitor is still better (e.g., "Method X remains faster on dense instances; we win on sparse and large"). Honest scoping is more credible than a blanket "we outperform all." When a competitor's code is in the IJOC GitHub repository or a public repo, plan to actually run it rather than quoting stale numbers from different hardware.
Sibling-journal framing in the related work
Position so the reader sees why this is IJOC and not a sibling: emphasize the computational/methodological delta. If the related work reads like an Operations Research model survey, the computing contribution is buried; if it reads like a CS algorithms paper with no OR task, the OR relevance is missing. The synthesis — "here is the OR problem, here is the computing frontier, here is the gap we close" — is the IJOC signature.
Using the IJOC corpus and deposit as evidence
Two underused positioning moves are specific to IJOC. First, the IJOC Software and Data Repository means many recent competing methods ship with runnable code; cite those and, where feasible, re-run them on your instances rather than quoting heterogeneous published numbers — a re-run comparison is far more persuasive to a referee who knows the field. Second, IJOC's "Test of Time" award and its published archive signal which methods the area considers canonical; engaging those anchors your claim in the literature the Area Editor and reviewers actually hold as the bar. Position against the strongest reproducible competitor, not merely the most cited.
Checklist
- The single state-of-the-art method you compete with is named and cited precisely
- Both the problem (OR/MS) literature and the method (computing) literature are engaged
- Recent (last ~2 years) competing methods are cited, not only canonical ones
- Each claimed advantage is tied to a baseline you will actually run or fairly quote
- Where a competitor is still better, the paper says so and scopes the claim
- The positioning makes the IJOC (not OR/MS/MPC/IJOO/CS) fit obvious
- No invented or padded citations; every cited result is checkable
Anti-patterns
- "Little/no prior work exists" on a topic the Area Editor has published in
- Comparing only to old baselines while a current method dominates the field
- Citing application papers as if they were your methodological competitors
- Quoting a competitor's runtimes from a different machine as if comparable
- A related-work section that could belong to Operations Research or a CS venue with the journal name swapped
- Overclaiming "we outperform all existing methods" without per-regime honesty
Output format
【Journal】INFORMS Journal on Computing
【Skill】ijoc-literature-positioning
【SOTA to beat/match】named method + citation
【Frontier(s) advanced】OR/MS problem / computing method / both
【Claimed delta】the computational gap closed, in measurable terms
【Honest scoping】where a competitor still wins
【Sibling boundary】why IJOC and not OR / MS / MPC / IJOO / CS
【Next skill】ijoc-methods
Version History
- 1839142 Current 2026-07-05 13:21
