Z-Number back to the data type card14 methods
Z-Number
Methods that work with Z-Number data
Every method that works with this data type has a page of its own. Those with an academy card are explained here through their philosophy, how to read their output and worked cases; the rest open on their formula page in the library.
17 academy cards · 1 only in the library · 14 methods in the catalogue
Methods with an academy card
17 cards- TOPSIS extensionsZ-number TOPSISThis is the form of TOPSIS for situations where every criterion value is given together with how far that value can be trusted. The output is again a closeness score, and a rank drawn from that score.Open the card →
- VIKOR extensionsZ-number VIKORThis is the form of VIKOR for situations where every criterion value is given together with how far that value can be trusted. The output is again group utility, individual regret, and a compromise index combining the two.Open the card →
- AHP extensionsZ-Number AHPThis is the form of AHP that adds to pairwise comparisons not only "how many times more important" but also how much this judgement is trusted. The output is again a weight vector; but the reliability of every comparison is embedded into the weight.Open the card →
- BWM extensionsZ-number BWMThis is the form of BWM in which the comparisons given against the best and the worst criterion also carry how far that judgement is trusted. The output is still a weight vector; a comparison with low reliability enters the weight calculation more weakly.Open the card →
- BWM extensionsZ-number Game-Theoretic BWMThis extension combines BWM's best/worst-criterion weighting with a zero-sum game played over a payoff table of alternatives expressed as Z-numbers. Unlike every other BWM family member, the output is not a weight vector but a ranking of alternatives derived from the game's Nash equilibrium.Open the card →
- CRITIC extensionsSpherical Fuzzy Z-Number CRITICThis is the form of CRITIC for situations where criterion values are given as spherical fuzzy triples (support, rejection, hesitancy), and each of these three degrees is further accompanied by its own reliability. The output is again a weight vector.Open the card →
- EDAS extensionsZ-number EDASThis is the form of EDAS for situations where every criterion value is given together with how far that value can be trusted. The output is again an assessment score, and a rank drawn from that score.Open the card →
- COPRAS extensionsZ-number COPRASThis is the form of COPRAS for situations where every criterion value is given together with how far that value can be trusted. The output is a relative-significance value that comes from combining the benefit and cost totals.Open the card →
- MARCOS extensionsZ-number MARCOSThis is the form of MARCOS for situations where the decision-matrix cells are not crisp numbers but Z-numbers, carrying a value together with how far that value is trusted. The logic of the utility ratio relative to the ideal and the anti-ideal stays exactly the same; only the cells change.Open the card →
- MARCOS extensionsComplex Fuzzy Z-Number MARCOSThe form of MARCOS for situations where criterion values are given both as an amplitude-phase pair and as a reliability degree attached to that pair. The output is still a final utility degree and a rank.Open the card →
- MARCOS extensionsSpherical Fuzzy Z-Number MARCOSThis is the form of MARCOS for situations where criterion values are given as spherical fuzzy triples (support, rejection, hesitancy), and each of these three degrees is further accompanied by its own reliability. The output is again a final utility degree and a rank.Open the card →
- PROMETHEE extensionsZ-number PROMETHEEThis is the form of PROMETHEE for situations where every criterion value is given together with how far that value can be trusted. The output is again a net flow and a rank; but a claim with low reliability does not enter the ranking with its full stated value.Open the card →
- WASPAS extensionsZ-number WASPASThis is the form of WASPAS for situations where the decision-matrix cells are not crisp numbers but Z-numbers, carrying a value together with how far that value is trusted. The logic of blending the sum with the product stays exactly the same; only the cells change.Open the card →
- WASPAS extensionsComplex fuzzy Z-number WASPASThis is the form of WASPAS for situations where criterion values are given both as an amplitude-phase pair and as a separate reliability degree attached to that pair. The output remains a combined score and a rank.Open the card →
- CRADIS extensionsSpherical fuzzy Z-number CRADISThis is the form of CRADIS for situations where criterion values are given as a spherical fuzzy triple (support, rejection, hesitancy) and each of these three degrees is additionally accompanied by a reliability. The output is again a compromise score.Open the card →
- CRADIS extensionsZ-fuzzy CRADISThis is the form of CRADIS for situations where a criterion value is carried as a triangular fuzzy number together with a separate Z-number component stating how far that value can be trusted, the two together reduced to a single fuzzy number. The output remains a compromise score.Open the card →
- LMAW extensionsZ-fuzzy LMAWZ-fuzzy LMAW is the form of LMAW that carries the priority experts give to criteria not only as a fuzzy term, but together with a separate component stating how much that term is trusted. Its output is not a ranking but a criterion weight vector.Open the card →
Other methods in the library
These methods do not yet have an academy card. Their formulae, steps and source citation live in the library; each link opens the method page directly.