Pareto trade-off comparison
Which complete alternatives are no worse on every declared dimension and strictly better on at least one?
Worked example
A policymaker can compare service options across cost, coverage and recovery time. Keep options with genuine trade-offs visible and disclose any preference weights.
Identifies alternatives dominated on every declared comparable dimension without adding unlike units or choosing a policy winner.
Try it yourself
The calculator opens with the fictional example already filled in. Change one input, choose Calculate locally, and compare the result to the original values below. Use Reset fictional fixture to start over.
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- Nondominated among complete feasible alternatives 2 alternatives
- Dominated complete alternatives 1 alternatives
- Incomplete and unresolved alternatives 0 alternatives
- Alternatives violating declared constraints 0 alternatives
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Compare the arrangements
Keep physical resources and evaluation conditions equal. With identical inputs, all three approaches produce identical arithmetic. The comparison refuses material differences in declared conditions; it does not verify those declarations.
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Executive brief and reproducible export
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Method, inputs and limits
Identifies alternatives dominated on every declared comparable dimension without adding unlike units or choosing a policy winner. Method version 0.2.0. Choose a government action, value unlike dimensions equally, infer causation or compare incomplete alternatives as if complete.
| Input | Unit / type | Required interpretation |
|---|---|---|
| constraints — Optional declared feasibility thresholds | separate declared dimensions / json | Rows: dimensionId, operator (<= or >=), threshold, unit. |
| preferences — Optional explicit preference assumptions | separate weights and normalizations / json | Object: enabled (false disables preference ordering), weights:{dimensionId:nonnegative weight}, normalization:{dimensionId:{min,max,unit}}. No preference order is produced without both. |
| dimensions — Metrics, units and preferred direction | separate declared dimensions / json | Rows: id, label, unit, kind (quantity or money), direction (minimize or maximize). Money also requires currency, priceBasis and baseYear; unit must state those semantics in minor units. |
| alternatives — Alternative metric values | separate declared dimensions / json | Rows: id, label, values:{dimensionId:{value:number,unit:matching unit}}. null or missing values remain unknown and are excluded from dominance claims. |
Visible mathematics / decision rules
A dominates B iff A is no worse than B on every declared dimension and strictly better on at least one
Nondominated alternatives have no dominator among complete, comparable alternatives
What this result cannot establish
- Bounded implementation from supplied acceptance checks and restored CORE definitions; scope choices are explicit below.
- Optional constraints screen feasibility before dominance. Optional visible weights require explicit per-dimension normalization and produce a conditional preference order, never an automatic policy action.
- Directions are explicit human choices. No preference score is created without explicitly supplied weights and normalization; no policy winner is selected.
- All alternatives must share definitions, period and scope externally; matching unit labels alone do not establish substantive comparability.
- Incomplete alternatives remain unresolved and may dominate an eligible complete alternative if unknown values are later supplied.
- Measurement uncertainty is not modeled; exact numeric comparisons may be sensitive to rounding. Preference values outside a declared normalization range are reported as extrapolations.
What would falsify the assumptions?
- The result fails if dimensions, directions, units, scope or values are incorrect.
- Independent comparable measurements can change dominance relationships.
- No resources are added or allocated; all dimensions retain their own units.
- Check each pair of alternatives manually using the same inequalities.
- This is a descriptive ordering of supplied values, not a forecast or causal estimate.
- MAR adds no benefit if manual comparison is equally clear; concealing missing metrics would add risk.
- Assumptions fail if the supplied definitions, units, period, scope or source records are wrong or incomplete.
- An independent source audit or replication may contradict an input or the recorded dependency.
- This method creates no resources. Physical conservation is checked in the inventory and transfer ledgers; descriptive graphs and checklists are not resource-flow models.
- The same equations and review checklist can be reproduced with a spreadsheet or structured human-only process.
- This is deterministic arithmetic, a descriptive comparison or a structured governance check, not a fitted causal effect or forecast. Fictional inputs remain an exercise.
- Equal or worse measured errors, net review effort, disclosure burden or fallback under MAR would show no added benefit or added risk; no improvement is assumed.
Reproducible fictional fixture and independently calculated expectations
This fixture is synthetic. It does not describe a country, government, company or event.
{
"observations": {
"unit": "separate declared dimensions",
"origin": "synthetic",
"sources": [
{
"id": "SYN-001",
"kind": "synthetic",
"label": "Fictional alternatives with separate dimensions",
"url": null
}
],
"dimensions": [
{
"id": "cost",
"label": "Declared cost",
"unit": "USD minor units; nominal 2026",
"kind": "money",
"currency": "USD",
"priceBasis": "nominal",
"baseYear": 2026,
"direction": "minimize"
},
{
"id": "served",
"label": "Requests served",
"unit": "requests",
"kind": "quantity",
"direction": "maximize"
}
],
"alternatives": [
{
"id": "A",
"label": "Option A",
"values": {
"cost": {
"value": 10000,
"unit": "USD minor units; nominal 2026"
},
"served": {
"value": 70,
"unit": "requests"
}
}
},
{
"id": "B",
"label": "Option B",
"values": {
"cost": {
"value": 12000,
"unit": "USD minor units; nominal 2026"
},
"served": {
"value": 90,
"unit": "requests"
}
}
},
{
"id": "C",
"label": "Option C",
"values": {
"cost": {
"value": 13000,
"unit": "USD minor units; nominal 2026"
},
"served": {
"value": 70,
"unit": "requests"
}
}
}
]
},
"parameters": {
"constraints": [],
"preferences": {
"enabled": false,
"weights": {
"cost": 0.5,
"served": 0.5
},
"normalization": {
"cost": {
"min": 0,
"max": 20000,
"unit": "USD minor units; nominal 2026"
},
"served": {
"min": 0,
"max": 100,
"unit": "requests"
}
}
}
}
}Expected checks
{
"nondominatedCount": 2,
"dominatedCount": 1,
"incompleteCount": 0
}Download input fixtureAuthoritative background references
- U.S. GAO: Cost Estimating and Assessment Guide — Published 12 March 2020. Estimation and sensitivity guidance; no endorsement of this implementation. Reviewed 2026-11-09. Reference, not endorsement or validation.
These sources inform definitions or review practices. They do not validate this implementation or endorse MAR.