ors-tables-figures

Tables, Figures & Exhibits (ors-tables-figures)

When to trigger

• The model, proofs, and computational results exist and must be displayed clearly.
• You need a clean comparison table separating your method from prior work.
• Reviewers should be able to read a result table without hunting through the text.

Exhibits that carry an OR paper

Unlike empirical social-science papers built around correlation and regression tables,

Operations Research exhibits are about structure, guarantees, and computation:

• Formal-statement layout: number theorems, propositions, lemmas, and assumptions

consistently (Theorem 1, Assumption 1) and reference them by number everywhere.

Use the INFORMS LaTeX style files / amsthm so environments render uniformly.

• Comparison table (prior work × properties): rows = methods/papers, columns =

{assumptions, strongest result, approximation factor, complexity/rate}. This is the

single most persuasive OR exhibit for novelty.

• Computational-results table: instances/sizes × {optimality gap, time,

iterations, baseline comparison}. Report units, time limits, and which configuration

produced the row; bold or mark wins honestly.

• Plots: convergence curves, scaling (size vs. time, ideally log-log), performance

profiles across instance sets, and for stochastic output **error bars / confidence

intervals** — never bare means.

INFORMS house-style notes

• Format: prepare for 1.5-spaced, 11-point, 1-inch-margin manuscript layout;

submit as PDF (source LaTeX/Word on acceptance). Use the provided LaTeX style files.

• Self-contained exhibits: each table/figure has a complete caption (what, units,

instance set, what "best" means) so it stands alone.

• Notation consistency: symbols in exhibits match the text exactly; define them in

the caption or a notation table.

• E-companion: large result tables and ablations can go to the e-companion (which

must not be longer than the manuscript); keep the headline exhibits in the main text.

Vector tooling

Use TikZ/PGFPlots (or matplotlib exported to vector) for crisp figures; performance

profiles and log-log scaling plots reproduce well as vectors. Keep raw data/scripts in

the ORJournal repository so every exhibit regenerates.

Exhibit pushback patterns and the INFORMS-style fix

| Referee remark on an exhibit | What it flags | Venue-specific fix |

|------------------------------|---------------|--------------------|

| "Computational study lacks benchmarks" | no recognized baseline column | add a column for the closest prior method and a strong solver on standard instances |

| "Cannot tell what 'best' means" | undefined win marking | caption defines the metric and tie-breaking; bold/mark honestly |

| "Results not reproducible from the table" | missing units/time-limit/hardware | state units, time limit, termination, hardware, and the producing configuration |

| "Means hide variability" | bare means for stochastic output | error bars / confidence intervals on every random-output figure |

| "Theorem numbers don't match the text" | label drift | single numbering scheme via amsthm; reference by number everywhere |

| "Scaling claim unsupported" | linear-axis time plot | log-log size-vs-time plot or a performance profile across the instance set |

These are the exhibit-level versions of the two flags that sink OR computational

sections: no benchmarks and structure-not-connected-to-application. Because

Operations Research is the INFORMS flagship demanding both theorem-grade rigor and a

credible computational study, the comparison table and the performance profile carry as

much referee weight as the theorem environments.

Worked exhibit pair (illustrative numbers)

A paper proves a 1.5-approximation and validates it. Two exhibits do the persuading:

Comparison table — Method × {assumption, factor, complexity}:

| Method | Assumption | Factor | Complexity |

|--------|-----------|--------|------------|

| Prior (Author year) | bounded ratios | 2.0 | O(n²) |

| This paper | general weights | 1.5 | O(n² log n) |

Computational table — Instance set × {mean gap %, time (s), solver baseline}, e.g.

TSPLIB-derived instances showing 1.8% mean gap vs. 31% for the heuristic baseline at a

600 s limit on stated hardware, with the proved 50% bound never violated. The figure

pairs them: a log-log scaling plot with confidence-interval bands over 30 seeds. The

table corroborates the theorem's bound; the plot shows it holds as size grows.

Execution bridge (StatsPAI / Stata MCP)

Generate exhibits from the fitted result, not by retyping numbers (the usual source of

body-vs-appendix drift). Full map: [execution-with-mcp](../../../shared-resources/empirical-methods/execution-with-mcp.md). Operations Research is predominantly analytical / optimization / stochastic modeling; use the chain below only for its empirical/causal papers — modeling, optimization, and simulation are outside this causal-inference toolchain.

• Tables: etable (multi-model columns) or did_summary_to_latex straight from the

result_id.

• Figures: plot_from_result / enhanced_event_study_plot / event_study_table —

axis units and the SE/clustering note baked in.

• Every note names the estimator + clustering and states the effect size in

interpretable units.

See a full fitted-result → exhibit chain in the [JF execution walkthrough](../../../Journal-of-Finance-Skills/resources/worked-examples/02-execution-walkthrough.md).

Anti-patterns

• A results table with no time limits, units, or hardware — irreproducible.
• Bare means for stochastic output with no confidence intervals.
• A comparison table that omits the closest competitor.
• Theorem/assumption numbers that drift between text and exhibits.
• Raster screenshots of plots instead of vector figures.

Output format

【Formal statements】numbered consistently; INFORMS/amsthm style
【Comparison table】prior work × {assumptions, result, complexity}: drafted?
【Computational table】instances × {gap, time, baseline}; units/limits stated
【Plots】convergence / scaling / CIs present?
【House style】1.5-spaced, 11-pt; self-contained captions; e-companion split
【Next step】ors-writing-style