Extension card · Plithogenic
Plithogenic MULTIMOORA
This is the form of MULTIMOORA for situations where criterion scores are given as a truth-indeterminacy-falsity triple and criteria carry a degree of contradiction relative to one another. The ratio system, the reference point and the full multiplicative form are each computed separately on these triples, and the result is merged into a single rank by the average-rank rule.
Base method
MULTIMOORA →
Philosophy, mechanics, strengths and weaknesses are on the base method card; this card describes only the difference.
Data type (family)
Plithogenic →
What this data type is, when to use it, how to write it in a cell: the family's full account is here.
What Changes from the Base Method?
Four things change; the dominance logic is preserved.
Cells. In crisp MULTIMOORA every cell is a single number. Here every cell is three numbers: truth (T), indeterminacy (I), falsity (F). The sub-option idea from the plithogenic data-type card is carried, as in P-TOPSIS, onto the criterion itself: DecisionMind treats the criteria themselves as sub-options of a whole. One criterion is taken as dominant, with a contradiction degree of zero; how strongly the other criteria oppose this dominant criterion is given by a fixed, per-criterion contradiction degree between 0 and 1. Criterion weights are an input separate from this degree.
Scale equalisation. Crisp MULTIMOORA divides the column by the square root of the sum of squares. Here the cost criterion's triple is first complemented (T and F swap places), then every cell is adjusted by its own criterion's contradiction degree: truth is pulled upward towards the dominant criterion, while indeterminacy and falsity are shrunk by the same proportion. This adjusted triple is reduced to a single number by a score function ((1+T−2I−F)/2), 1 is added, and only THEN is it equalised by dividing by the square root of the column's sum of squares. The plithogenic structure therefore collapses to a single number before scale equalisation; this is the same order as in the fuzzy and spherical fuzzy MULTIMOORA extensions.
Distance / score / merging. The ratio system and the reference point both operate on this equalised single number: the ratio system is a weighted sum, and the reference point is each alternative's weighted maximum deviation from the largest value in its column. The full multiplicative form is DIFFERENT. This component does not use the equalised single number but the contradiction-adjusted T-I-F triple: it raises truth, (1 − indeterminacy) and (1 − falsity) each to the power of the criterion's weight and multiplies them together (a weighted geometric aggregation), forming a new triple. This triple is converted to a single number with the same score function. This is the same design followed in Neutrosophic MULTIMOORA's (N-MULTIMOORA) full multiplicative form: only the full multiplicative form carries the T-I-F structure further, into its own aggregation step, than the ratio system and the reference point do.
Result and defuzzification. The output is a single number. When merging the three sub-rankings, this extension uses an average-rank calculation equivalent to crisp MULTIMOORA's Borda rule: each alternative's positions across the three sub-rankings are averaged, and the smallest average takes first place in the final ranking. N-MULTIMOORA's rule of "dominance in at least two sub-methods" does not apply here.
DecisionMind fixes, in this extension, the cost complement, the contradiction adjustment, the score-then-normalise order for the ratio system and reference point, the weighted geometric aggregation for the full multiplicative form alone, and the average-rank merging.
How to Read the Output
The final rank is a combined summary of three perspectives, as in crisp MULTIMOORA, and is read essentially the same way. The difference is here: beneath the score lie both T-I-F indeterminacy and an assumption about the contradiction degree between criteria, and this assumption affects the full multiplicative form directly, while it affects the ratio system and the reference point only after passing through the score-and-normalise step.
Thus instead of writing:
"Plithogenic MULTIMOORA gives a more reliable result because it also accounts for contradiction"
the report should read:
"The contradiction degree between criteria has been given under the following assumption; the three sub-methods use this assumption at different points, and the final rank is sensitive to it"
In the illustrative example below, the ranking of A1 and A3 reverses once C2's contradiction degree is raised from 0.33 to 0.90; A2's first place is unaffected by this change, because all three sub-methods already agree on it.
When to Prefer This over the Base Method
Use this extension when your criterion scores are given as a truth-indeterminacy-falsity triple, and some criteria carry information that is more "independent", or more "in conflict", than others. If the T-I-F triple alone is sufficient and no such dominance-contradiction relationship exists among the criteria, neutrosophic MULTIMOORA (N-MULTIMOORA) is already sufficient; the plithogenic form adds one further assumption, and if that assumption is given without justification it creates a spurious distinction.
Converting a measured criterion into a T-I-F triple is manufacturing indeterminacy, not modelling it; this principle applies here too. The exit condition for crisp MULTIMOORA applies equally: all values must stay within their valid range or the full multiplicative form becomes undefined, and this method should not be used where no compromise is acceptable on a criterion.
Mistakes Specific to This Extension
Violating the value space. Every cell must be a valid T, I, F triple, and a contradiction degree must be declared for every criterion; running the method with a missing or invented contradiction degree invalidates it.
Assigning the contradiction degree without justification. In the illustrative example, raising C2's contradiction degree from 0.33 to 0.90 reverses the ranking of A1 and A3. If this degree is given "by feel", the ranking becomes a feeling too; the degree must rest on a measurable justification for how independent, or how overlapping, a criterion's information is relative to the dominant criterion.
Assuming the full multiplicative form also uses the normalised score. Only the ratio system and the reference point work on the score-and-normalised single number; the full multiplicative form uses the contradiction-adjusted T-I-F triple directly. Confusing the two produces a different calculation.
Choosing the dominant criterion arbitrarily. Which criterion is taken to have zero contradiction is a decision and must be justified in the report; if the dominant criterion changes, the contradiction degrees of the other criteria must be reconsidered too.
The governing principle is this:
In plithogenic MULTIMOORA the contradiction degree is a criterion's share of independence drawn from measurable ground; the ratio system and the reference point use it in its score-reduced form, while the full multiplicative form uses it directly on the T-I-F triple.
Cases
The first case is DecisionMind's validation example. Smarandache's founding 2018 source defines the plithogenic operations but includes no MULTIMOORA example decision table; DecisionMind has therefore built a small, hand-traceable table using the same formulas (the shared synthetic validation fixture of the P-* family). The second case is an illustrative fiction.
1. Illustrative example: Three alternatives, three criteria (DecisionMind validation example)
Three alternatives are assessed on three criteria. The first two criteria are more-is-better, the third is less-is-better. C1 is taken as the dominant criterion, with a contradiction degree of zero; the contradiction degrees of C2 and C3 relative to C1 are 0.33 and 0.67 respectively.
| Alternative | C1 (more is better) | C2 (more is better) | C3 (less is better) |
|---|---|---|---|
| A1 | (0.70; 0.20; 0.10) | (0.50; 0.30; 0.20) | (0.60; 0.30; 0.20) |
| A2 | (0.80; 0.10; 0.10) | (0.60; 0.20; 0.20) | (0.40; 0.20; 0.30) |
| A3 | (0.60; 0.20; 0.20) | (0.70; 0.20; 0.10) | (0.50; 0.30; 0.20) |
| Contradiction degree | 0.00 | 0.33 | 0.67 |
| Weight | 0.40 | 0.35 | 0.25 |
The method complements C3's triple, adjusts every cell by its own criterion's contradiction degree, then computes the ratio system and reference point from this adjusted triple's score, and the full multiplicative form from the adjusted triple itself. These three calculations have been independently reproduced in Python and matched exactly against DecisionMind's engine (method_runner.py P-MULTIMOORA).
| Alternative | Ratio system | Rank | Reference point (distance) | Rank | Full multiplicative | Rank |
|---|---|---|---|---|---|---|
| A1 | 0.5606 | 3 | 0.0214 | 2 | 0.6032 | 3 |
| A2 | 0.6013 | 1 | 0.0081 | 1 | 0.7201 | 1 |
| A3 | 0.5681 | 2 | 0.0356 | 3 | 0.6227 | 2 |
A2 is first in all three sub-methods; this is absolute dominance. Between A1 and A3 the sub-methods disagree: the ratio system and the full multiplicative form place A3 ahead of A1, while the reference point places A1 ahead of A3, because A3's position on C3 (the cost criterion) is slightly weaker than A1's and the reference point focuses on the worst criterion.
| Alternative | Average rank | Final rank |
|---|---|---|
| A2 | 1.00 | 1 |
| A3 | 2.33 | 2 |
| A1 | 2.67 | 3 |
The board's hesitation is this: if C2's contradiction degree is raised from 0.33 to 0.90, with everything else held constant, A1's average rank falls from 2.67 to 2.00, A3's rises from 2.33 to 3.00, and A1 and A3 swap places, A1 becoming second and A3 third. A2's first place is unaffected by this change, because it is already first in all three sub-methods.
In the report: "Under the average-rank rule with the given contradiction degrees (C1=0, C2=0.33, C3=0.67), A2 is first, A3 second and A1 third. A2's first place is robust, since all three sub-methods agree on it; the ranking of A3 and A1 reverses once C2's contradiction degree is raised to 0.90."
Source: DecisionMind's P-MULTIMOORA manifest, validation example. The plithogenic operations (contradiction adjustment, weighted geometric aggregation) rest on the formulas defined by Smarandache (2018); since the founding source gives no MULTIMOORA example decision table, the table has been constructed by DecisionMind, as the P-* family's shared synthetic fixture, faithfully to the formulas. A DOI recorded elsewhere as this family's common "founding paper" (10.61356/j.plc.2024.1253) resolves to an unrelated article and has therefore not been included on this card; the detail is in the approval note.
2. Furniture manufacturing: A manufacturer's choice of timber supplier
A furniture manufacturer is to choose among three timber suppliers. Three criteria are used: suitability of the timber for machining, suitability for continuity of supply, and unit price (less is better). Machinability is taken as the dominant criterion, with a contradiction degree of zero. Supply continuity is judged to carry moderately independent information that partly conflicts with machinability. Price is judged to carry information more independent still of machinability and therefore receives a higher contradiction degree. Each supplier is scored on each criterion with a truth-indeterminacy-falsity triple; the indeterminacy comes from inconsistency across sample-batch tests.
The method adjusts the three suppliers by their own contradiction degrees and multiplies by the weights; it computes the ratio system and the reference point on the adjusted score, and the full multiplicative form on the adjusted triple itself. Suppose the supplier with the highest machinability suitability also has the highest unit price, and it still comes first, because the weight on machinability exceeds that on price.
The manufacturer's hesitation: if price's contradiction degree has been kept high, that is, treated as information independent of machinability, this supplier's real cost risk may not carry enough weight in the final rank. The manufacturer should not decide on the final rank alone without setting an upper bound against a rise in unit cost.
In the report: "With the high weight given to machinability suitability, the most suitable supplier ranks first in the final order; because price's contradiction degree has been kept high, a separate upper bound is recommended for cost risk."
3. What Not to Do
If C3's triple is run without being complemented in the illustrative example, that is, the cost criterion is treated as more-is-better, the most expensive alternative is drawn towards the ideal and the ranking becomes meaningless. The second error is computing the full multiplicative form on the same score-and-normalised number as the ratio system; this component uses the contradiction-adjusted T-I-F triple directly, not the normalised score. The third error is raising C2 and C3's contradiction degrees arbitrarily "to widen the gap"; in the illustrative example this can reverse the ranking of A1 and A3 without justification.
Sources
For the formulas behind each step, the intermediate tables and citation formats, see the DecisionMind method page: decisionmind.app/library/p-multimoora
Smarandache, F. (2018). Plithogenic set, an extension of crisp, fuzzy, intuitionistic fuzzy, and neutrosophic sets – revisited. Neutrosophic Sets and Systems, 21, 153–166. DOI: 10.5281/zenodo.1408740
Smarandache, F. (2017). Plithogeny, Plithogenic Set, Logic, Probability, and Statistics. Pons Publishing House, Brussels. (no DOI)
Brauers, W. K. M., & Zavadskas, E. K. (2010). Project management by MULTIMOORA as an instrument for transition economies. Technological and Economic Development of Economy, 16(1), 5–24. DOI: 10.3846/tede.2010.01
Abdel-Basset, M., & Mohamed, R. (2020). A novel plithogenic TOPSIS-CRITIC model for sustainable supply chain risk management. Journal of Cleaner Production, 247, 119586. DOI: 10.1016/j.jclepro.2019.119586