Hesitant back to the data type card30 methods
Hesitant
Methods that work with Hesitant 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.
41 academy cards · 0 only in the library · 30 methods in the catalogue
Methods with an academy card
41 cards- RankingHF-DFTHF-DFT does not compare alternatives at a single instant; it simulates how preference accumulates over time and, at the end of a deliberation period, recommends the alternative that has accumulated the most preference.Open the card →
- RankingPHFS-EHVaRPHFS-EHVaR resolves the cases PHFS-HVaR cannot distinguish by computing, instead of just an alternative's worst-case boundary, the probability-weighted average of every scenario below that boundary.Open the card →
- RankingPHFS-HVaRPHFS-HVaR is a risk measure that, when an alternative's future is expressed through several possible values and their probability of occurring, finds the worst boundary that stays below a chosen confidence level.Open the card →
- Subjective weightingAHSPRAHSPR derives a priority ranking from pairwise comparisons, but it does so not on one shared scale, but on a scale that bends to fit each decision-maker's own attitude to risk.Open the card →
- Subjective weightingHFLPR-PRIORITYHFLPR-PRIORITY derives a priority order directly from pairwise comparisons decision-makers give in words ("somewhat good," "very good," and the like), without first trying to make those words consistent.Open the card →
- PortfolioHF-MaxScore-PortfolioHF-MaxScore-Portfolio does not pick a single winner; it splits a limited budget across several alternatives in whatever way maximises the total evaluation score.Open the card →
- PortfolioHF-TRADEOFF-PORTHF-TRADEOFF-PORT finds a resource allocation across investment options whose returns are expressed as several possible values rather than one (hesitant), balancing return against risk according to the investor's risk type.Open the card →
- EfficiencyHFEAHFEA is a method that, when expert opinions are given as more than one possible score (hesitant), evaluates every option under the weighting most favourable to itself and produces an efficiency score showing whether it is efficient.Open the card →
- EfficiencyHFPEHFPE takes the several options HFEA leaves on the efficient frontier and distinguishes them into a single ranking by evaluating each one not only through its own eyes but through the eyes of every other option as well.Open the card →
- EfficiencyHFPEAHFPEA bounds the free-weighting latitude that HFEA gives each option in its own favour, computing efficiency under weights that also honour a priority order the decision-maker has stated among the criteria.Open the card →
- TOPSIS extensionsHesitant fuzzy TOPSISThis is the form of TOPSIS for situations where more than one plausible membership degree is held together for a single criterion. It carries these sets through the calculation and ranks the result, once again, with a single closeness score.Open the card →
- TOPSIS extensionsDual hesitant fuzzy TOPSISThis is the form of TOPSIS for situations where a cell holds more than one possible degree of support and more than one possible degree of rejection, recorded separately and independently. It measures the distance to the ideal and anti-ideal point through these two sets, and ranks the result with a closeness coefficient.Open the card →
- TOPSIS extensionsm-polar hesitant fuzzy TOPSISThis is the form of TOPSIS for situations where a criterion is assessed from more than one independent viewpoint (pole), and each viewpoint itself is hesitant, that is, carries more than one plausible value.Open the card →
- TOPSIS extensionsProbabilistic hesitant TOPSISThis is the form of TOPSIS for situations where more than one plausible value for a criterion is given together with its own probability of occurrence. Every cell is first reduced to its expected value, after which the remaining steps of classical TOPSIS are applied.Open the card →
- TOPSIS extensionsSimplified Neutrosophic Hesitant Fuzzy TOPSISThis is the form of TOPSIS for situations where a criterion's truth, indeterminacy and falsity degrees are each hesitant in their own right, that is, each carries more than one plausible value. Weights are not taken from outside; the method itself derives them from the disagreement in the data.Open the card →
- VIKOR extensionsHesitant fuzzy VIKORThis is the form of VIKOR for situations where more than one plausible membership degree is held together for a single criterion. It computes group utility and individual regret using distances between sets, and ranks the result, once again, with a compromise index.Open the card →
- VIKOR extensionsDual hesitant fuzzy VIKORThis is the form of VIKOR for situations where several decision-makers each give both a support and a rejection value for every criterion, and the weight of some criteria is not fully fixed in advance. It combines the decision-makers' votes, completes the missing weights with an optimisation, and ranks the result by a rule that is the exact opposite of classical VIKOR's: the HIGHEST Q counts as best.Open the card →
- VIKOR extensionsProbabilistic hesitant VIKORThis is the form of VIKOR for situations where a cell carries more than one possible degree, and it is also known how often, or with what probability, each of these degrees is observed. It reduces every cell to a probability-weighted expected value and builds the compromise index over these values.Open the card →
- SAW extensionsHesitant SAWThis is the form of SAW for situations where several plausible values on a criterion are held together. It carries these sets through the calculation and reduces the result to a single weighted score only at the last step.Open the card →
- AHP extensionsHesitant Fuzzy AHPHesitant Fuzzy AHP is the form of AHP for situations where a pairwise comparison rests not on a single ratio but on several defensible ratios at once. It converts these ratios directly into a weight vector through linear programming rather than an eigenvector.Open the card →
- AHP extensionsHesitant fuzzy linguistic AHPHesitant fuzzy linguistic AHP is the form of AHP for situations where criteria are compared pairwise and alternatives are scored on a seven-term verbal scale. Unlike crisp AHP, it does not generate weights alone; within the same exercise it also ranks the alternatives.Open the card →
- EDAS extensionsHesitant Fuzzy EDASThe form of EDAS in which every cell is given as a triangular fuzzy number and DecisionMind reduces this number to a single value at the very start of the calculation, comparing it against the set's average.Open the card →
- EDAS extensionsDual hesitant fuzzy EDASThis is the form of EDAS for situations where criterion evaluation carries more than one plausible value on both the supporting and the rejecting side, each value given with its own probability of occurrence. It merges several experts' matrices, builds weights from three sources, and still ranks the result with a single appraisal score.Open the card →
- EDAS extensionsProbabilistic hesitant EDASThis is the form of EDAS in which more than one plausible value for a criterion is carried in a single cell together with its probability of occurrence. Every cell is reduced to a probability-weighted expected value in the method's first step, and the rest of the calculation runs on that value.Open the card →
- COPRAS extensionsHesitant Fuzzy COPRASThe form of COPRAS for situations where more than one plausible degree of membership on a criterion must be held together. It builds the benefit and cost totals through set aggregation, then ranks the result, once again, with a relative-significance value.Open the card →
- COPRAS extensionsDual Hesitant Fuzzy COPRASThis is the form of COPRAS for situations where a cell records several possible degrees of both support and rejection separately. It builds the benefit and cost sums over these dual sets, and ranks the result by a relative-importance value.Open the card →
- COPRAS extensionsProbabilistic hesitant fuzzy COPRASThis is the form of COPRAS for situations where a cell carries more than one possible degree, and it is also known how often, or with what probability, each of these degrees is observed. It builds the benefit and cost sums over expected values weighted by these probabilities.Open the card →
- MARCOS extensionsHesitant MARCOSThis is the form of MARCOS for situations where several plausible membership degrees on a criterion are held together. It reduces the sets to a score first, then ranks them by comparing them against the ideal and anti-ideal references.Open the card →
- CODAS extensionsHesitant Fuzzy CODASHesitant Fuzzy CODAS is the form of CODAS used when more than one plausible value on a criterion must be held together. It carries these sets through most of the calculation and still ranks the result with a single assessment score.Open the card →
- CODAS extensionsHesitant fuzzy linguistic CODASHesitant fuzzy linguistic CODAS is the form of CODAS used when a criterion is scored not with a single verbal term but with a comparative verbal expression such as "at least good" or "between medium and good." It converts this expression into a fuzzy envelope and carries it as such through most of the calculation.Open the card →
- PROMETHEE extensionsHesitant fuzzy linguistic PROMETHEEHesitant fuzzy linguistic PROMETHEE is the form of PROMETHEE for situations where a judgement is given not as a single verbal term but as more than one possible term (such as "between good and very good"). It reduces every cell to a closeness degree relative to the best term, then ranks alternatives with crisp PROMETHEE's same pairwise comparison and flow logic.Open the card →
- TODIM extensionsDual hesitant fuzzy TODIMThis is the form of TODIM for situations where a cell holds more than one possible degree of both support and rejection, recorded separately. It runs the loss-aversion logic through a distance and a score comparison between these dual sets.Open the card →
- TODIM extensionsHesitant TODIMThis is the form of TODIM for situations where several plausible membership degrees on a criterion are held together. It runs the loss-aversion logic through a measurement function and a distance, without collapsing these sets early into a single number.Open the card →
- WASPAS extensionsHesitant fuzzy WASPASThis is the form of WASPAS for situations where more than one plausible membership degree is held together, in the criterion assessment, for the same criterion-alternative pair. The sum and product components are built on sets; the two are reduced to a single score with a coefficient.Open the card →
- ARAS extensionsHesitant Fuzzy ARASHesitant Fuzzy ARAS is the form of ARAS for situations where an assessment on a criterion holds more than one plausible value at once. It weights these sets, reduces them to a single number by averaging, and computes the ratio to the optimal alternative.Open the card →
- ELECTRE extensionsHesitant Fuzzy ELECTRE IThis is the form of ELECTRE I for situations where performance scores are given as hesitant fuzzy sets, holding several plausible values together rather than one. These values are compared without first collapsing them to an average; the output remains a core set together with outranking relations.Open the card →
- MABAC extensionsHesitant MABACThis is the form of MABAC for situations where several plausible membership degrees on a criterion are held together. It builds the border approximation area from the sets themselves, and ranks alternatives by their distance to this border.Open the card →
- MABAC extensionsHesitant fuzzy linguistic MABACHesitant fuzzy linguistic MABAC is the form of MABAC used when a criterion is scored not with a single verbal term but with a comparative verbal expression such as "at least high" or "between medium and high." It converts this expression into a linguistic term set and calculates its signed distance to the border area.Open the card →
- MOORA extensionsHesitant MOORAThis is the form of MOORA for situations where criterion scores are given as several plausible values (a hesitant set) rather than a single number. It reduces every cell to a score and runs the rest exactly as crisp MOORA's ratio system.Open the card →
- GRA extensionsHesitant GRAHesitant GRA is the form of GRA that works for situations where several plausible values for one criterion — expert opinions, scenarios, repeated measurements — are preserved together rather than collapsed into a single number. It builds its reference from both the best and the worst end, and ranks the result with a closeness ratio.Open the card →
- ELECTRE II extensionsHesitant Fuzzy ELECTRE IIThis is the form of ELECTRE II for situations where performance scores are given as hesitant fuzzy sets. The fuzziness is carried through to the very last step and is never collapsed early into a single average; the output remains a complete ranking.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.
No method without a card remains for this type.