Data types
Plithogenic
This is the data structure that, where a criterion splits into several sub-options (attribute values), keeps both the degrees given to each sub-option and how contradictory the sub-options are to one another.
Example cell: 0.7, 0.2, 0.1
What Is It?
A plithogenic data structure treats a criterion not as a single question but as a question with several sub-options: the values of a "colour" criterion might be red, green and blue; a "supply region" criterion, domestic, neighbouring country and distant country; a "treatment route" criterion, medication, surgery and observation. An alternative is rated separately on each of these sub-options, and in DM3 those ratings are written as a triple of truth, indeterminacy and falsity (T, I, F).
The distinctive part of the structure is the degree of contradiction between the sub-options. For each criterion, a dominant sub-option is fixed, and how contradictory each other sub-option is to that dominant one is given as a number between 0 and 1. If "domestic" is dominant, "neighbouring country" is only mildly contradictory to it, while "distant country" is highly contradictory. This contradiction enters the calculation when the degrees are aggregated: the degrees of sub-options that contradict one another combine with a different weighting than those of sub-options that are close to one another.
In short, an ordinary triple says "how far does this alternative meet the criterion"; the plithogenic structure says "which sub-option of the criterion does this alternative meet, by how much, and how far apart are those sub-options from one another."
When to Use It
Use it where a criterion naturally splits into sub-options and those sub-options are not equally distant from one another. Where the contradiction between a criterion's sub-options matters to the decision itself — for instance, where "two suppliers from the same region can stand in for each other, but one from a distant region cannot" is genuine information — the plithogenic structure carries it.
By contrast, where the criterion is a single question ("is the price acceptable?"), or the sub-options are equally distant from one another, the contradiction degree adds nothing; a neutrosophic structure, or something simpler, then suffices. There is no need to pick the plithogenic structure merely as "the most general one."
Can Classical Data Be Converted into Plithogenic Data?
Yes, but three separate pieces of information are needed, and all three must be justified. The steps are as follows.
First, split the criterion into sub-options and write a judgement for each one: "the alternative meets this criterion via this sub-option." A measurement on its own does not become plithogenic; what is needed is a judgement about which sub-option the measurement falls under, and how far that sub-option is met.
Second, derive the three degrees for each sub-option from their own sources: truth from evidence in favour, falsity from evidence against, indeterminacy from information that is missing or conflicting. This step is the same as for the neutrosophic card.
Third, fix each sub-option's degree of contradiction relative to the dominant one. These degrees must not be a personal preference; they must come from the nature of the sub-options themselves, resting on a measurable basis such as distance, cost difference, or incompatibility.
What must not be done is dividing a single figure across the sub-options "by feel," and assigning contradiction degrees without justification; if the contradiction degree is invented, the aggregated result is invented too.
Contradiction Degree Is Not the Same as Importance Weight
The contradiction degree measures how far a sub-option is opposed to the dominant sub-option, not how important it is. A high contradiction degree for the "distant country" sub-option does not mean that sourcing from a distant country is bad; it means only that it cannot be put in the same basket as domestic sourcing, that one cannot substitute for the other.
For that reason:
"This sub-option matters less, so let us set its contradiction degree high"
is better replaced by:
"This sub-option is contradictory to the dominant one to such an extent; importance weight is given separately, at the criterion level"
If the two are conflated, the same piece of information enters the calculation twice.
Strengths
The chief advantage of the plithogenic structure is that it does not erase a criterion's internal structure. Structures that reduce sub-options to a single degree lose the information of "which sub-option" and the distance between sub-options; the plithogenic structure carries both through to the aggregation step.
Furthermore, in group decisions where several experts assess the same criterion through different sub-options, how far apart the experts' chosen sub-options are remains visible, so how hard consensus will be to reach can be measured.
Limitations
The structure's weakest point is the contradiction degrees themselves. In the literature these are mostly assigned by the analyst, and the justification is often not shown; different contradiction degrees give different results. A contradiction degree with no measurable basis leaves the result dependent on the analyst's preference.
The data-collection burden is heavy: for every alternative, every sub-option of every criterion needs three degrees, plus one contradiction degree per sub-option. Even in a small problem, the cell count grows quickly. The literature is relatively young; there is no single settled practice for aggregation rules and score functions. Also, for criteria without sub-options, this structure collapses into the neutrosophic structure and adds nothing extra.
Common Mistakes
The most frequent mistake is forcing a criterion with no sub-options into the plithogenic structure; if "price" has no sub-options, its contradiction degree is meaningless, and the structure is no different from neutrosophic.
The second mistake is using the contradiction degree as if it were an importance weight, or giving every sub-option the same contradiction degree, which reduces the structure's contribution to zero. A third is generating the sub-options' triples by splitting a single figure; each sub-option's degrees must rest on its own evidence.
The governing principle is this:
The plithogenic structure is used only where the criterion has genuine sub-options; each sub-option's degrees must come from its own evidence, and the contradiction degrees from the sub-options' own nature.
Examples
Each example opens with a familiar, single exact figure and shows the conditions and steps under which that same figure moves into plithogenic form.
2. Engineering: A part costing 180 Turkish lira
An exact figure. A manufacturer is choosing among three designs for a part. The current design's unit cost is 180 Turkish lira; it is read from cost accounting, and it does not become plithogenic.
Step 1: Split the criterion into sub-options. Let the criterion be "fit with the production technology," with sub-options casting, machining and additive manufacturing. The judgement for each design: "This design can be produced with this technology."
Step 2: Three degrees for each sub-option. Prototype results, supplier capacity, and production steps not yet trialled are assessed separately:
- •casting: (0.80, 0.10, 0.15)
- •machining: (0.60, 0.20, 0.30)
- •additive: (0.35, 0.45, 0.30)
Step 3: Contradiction degrees. Let the dominant sub-option be "casting." "Machining" is moderately contradictory to it (0.4), "additive" strongly so (0.8); these degrees rest on the difference in production logic (moulding versus cutting versus layering).
In plithogenic form. The design is represented, on the "fit with the production technology" criterion, by three triples and their contradiction degrees; because additive manufacturing's high indeterminacy is paired with strong contradiction to casting, it affects casting's high degree only lightly in aggregation.
Same figure, different case. If the additive-manufacturing prototype is produced successfully, that sub-option's indeterminacy degree falls; the contradiction degrees stay the same, because the nature of the technologies is unchanged.
3. Medicine: A patient aged 64
An exact figure. An oncology board is choosing among three treatment plans. The patient's age is 64; it is read from the identity record, and it does not become plithogenic.
Step 1: Split the criterion into sub-options. Let the criterion be "fit with the treatment route," with sub-options medication, surgery and active monitoring. The judgement for each plan: "This route is suitable for this patient."
Step 2: Three degrees for each sub-option. Guideline recommendations, the patient's comorbidities, and incomplete tests are assessed separately:
- •medication: (0.65, 0.25, 0.25)
- •surgery: (0.45, 0.35, 0.40)
- •monitoring: (0.50, 0.30, 0.35)
Step 3: Contradiction degrees. Let the dominant sub-option be "medication." "Monitoring" is moderately contradictory to it (0.5), "surgery" more so (0.7); these degrees rest on the difference in intervention intensity.
In plithogenic form. The patient is represented, on the "fit with the treatment route" criterion, by three triples and their contradiction degrees; in aggregation, the contradiction between surgery and medication weighs more heavily than that between monitoring and medication.
Same figure, different case. If the missing tests are completed, each sub-option's indeterminacy degree falls; the contradiction degrees stay the same, because the nature of the treatment routes is unchanged. The age itself is never converted into a triple under any circumstances; it enters only as an input to the judgement.
4. Supply region: A natural example
An exact figure. A supplier's average delivery time is 14 days.
Step 1. The choice is among three suppliers, on the criterion "supply source," with sub-options domestic, neighbouring country and distant country. The supplier can source goods from all three regions.
Step 2. Three degrees for each region, from that region's own delivery records: domestic (0.85, 0.05, 0.10), neighbouring country (0.60, 0.20, 0.25), distant country (0.35, 0.30, 0.45).
Step 3. The dominant region is "domestic." The neighbouring country is mildly contradictory (0.3), the distant country strongly so (0.8); these degrees rest on distance and customs differences.
In plithogenic form. This is the plithogenic structure's natural example: the criterion's sub-options are real, each sub-option's degrees come from separate records, and the contradiction rests on a measurable basis (distance).
5. What Not to Do
Writing a plithogenic structure for a criterion with no sub-options: for "budget share," writing 12 per cent → (0.7, 0.2, 0.1) plus a contradiction degree of 0.5, or writing a patient's age as 64 → (0.6, 0.2, 0.2). Neither the budget share nor the age has sub-options; the contradiction degree becomes a number whose target of opposition is undefined. A measured value stays crisp; the plithogenic structure arises only from a criterion with genuine sub-options.
The numbers in the examples are fictional; they are not real data.
Short decision rule
A single, reliable value → Crisp
Criterion is a single question; true / uncertain / false, independent → Neutrosophic
Criterion splits into sub-options, equally distant from one another → Each sub-option treated as its own criterion, neutrosophic
Criterion splits into sub-options, contradictory to differing degrees → Plithogenic
The sub-options' contradiction has no measurable basis → Not plithogenic; a contradiction degree is not invented
Key sources
Smarandache, F. (2017). Plithogeny, Plithogenic Set, Logic, Probability, and Statistics. Pons Publishing House, Brussels. (no DOI)
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
Abdel-Basset, M., El-hoseny, M., Gamal, A., & Smarandache, F. (2019). A novel model for evaluation Hospital medical care systems based on plithogenic sets. Artificial Intelligence in Medicine, 100, 101710. DOI: 10.1016/j.artmed.2019.101710
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