Classical back to the data type card113 methods
Classical
Methods that work with Classical 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 are listed below by name.
114 academy cards · 1 without a card yet · 113 methods in the catalogue
Methods with an academy card
114 cards- RankingTOPSISTOPSIS ranks alternatives by how far they sit from two hypothetical points built out of the best and worst value on every criterion: the alternative closest to the ideal and furthest from the worst comes out on top.Open the card →
- RankingVIKORVIKOR ranks alternatives by weighing their total distance from the ideal together with their distance on the single worst criterion; it looks for a compromise solution that "everyone can accept."Open the card →
- RankingSAWSAW equalises the scale of every criterion, multiplies it by its weight, and sums directly; it is the oldest and plainest member of the multiple-criteria decision methods. The alternative with the highest weighted sum comes out first.Open the card →
- OutrankingPROMETHEE IIPROMETHEE II does not compare alternatives one by one against an ideal. Instead it compares them pairwise against each other, grading "how much better" on every criterion with a preference function. Summing these grades into a net flow yields a complete ranking.Open the card →
- OutrankingELECTRE IIt does not rank alternatives; for every pair, it asks together "am I superior on enough criteria" (concordance) and "am I not very poor on any criterion" (discordance), and extracts a "kernel" of alternatives that no other alternative outranks.Open the card →
- Subjective weightingAHPA subjective weighting method that sets criteria against one another through pairwise comparison, and from those comparisons derives both a weight vector and a consistency measure showing how far the underlying judgements conflict with one another.Open the card →
- Subjective weightingBWMA subjective weighting method that weights criteria through a non-linear model built from the comparisons an expert makes against only the most important and the least important criterion, and that asks for comparatively few judgements.Open the card →
- Subjective weightingSWARASWARA first orders the criteria by importance, then compares each criterion only with the one immediately above it; it is a subjective weighting method that produces a weight vector from the smallest possible number of judgements.Open the card →
- Objective weightingEntropy WeightingA method that derives criterion weights not from expert opinion but from the data itself: the more a criterion separates alternatives from one another, the more weight it receives.Open the card →
- Objective weightingCRITICA method that derives criterion weights from the data itself: a criterion earns more weight the more it separates the alternatives and the less it repeats what other criteria already say.Open the card →
- RankingEDASA method that ranks alternatives not by their position relative to the ideal, but by their position relative to the set's own average: an alternative that sits markedly above the average and falls only slightly below it comes out ahead.Open the card →
- RankingCOPRASA method that ranks alternatives by combining the ratio of the weighted sum of benefit criteria to the weighted sum of cost criteria, and gives a benefit degree expressed as a percentage of the best alternative.Open the card →
- RankingMARCOSA method that ranks alternatives by comparing each one to both an ideal (best possible) and an anti-ideal (worst possible) reference point, then combines these two ratios into a single utility function.Open the card →
- RankingCODASCODAS ranks alternatives by comparing them against a single worst reference point using two different distance measures. It looks first at straight-line, Euclidean, distance; if alternatives come out very close to one another, it also brings in horizontal-and-vertical, that is city-block, distance.Open the card →
- OutrankingPROMETHEEPROMETHEE is a family of outranking methods that compare alternatives not against a hypothetical ideal but against each other. It grades "how much better" on every criterion with a preference function, comparing alternatives pairwise, and combines these comparisons into positive and negative flows to yield a partial or a full ranking.Open the card →
- RankingTODIMTODIM carries into multi-criteria ranking a behavioural decision theory in which the decision-maker is assumed to be cautious about gains and disproportionately sensitive to losses. It weighs alternatives pairwise, treating "winning" and "losing" separately.Open the card →
- RankingWASPASWASPAS combines two different aggregation logics, the weighted sum and the weighted product, into a single result; it is a ranking method that offsets the weakness of one with the strength of the other.Open the card →
- RankingARASARAS measures each alternative by the ratio of benefit it delivers relative to a hypothetical "best" alternative derived from the same table, converting that ratio into a directly interpretable percentage degree of utility.Open the card →
- OutrankingELECTRENot a single method but a family of outranking methods. The family establishes the relation "which alternative clearly beats which" through concordance and discordance criteria. Members built on the same core logic produce a choice, a ranking or a sorting, depending on the purpose.Open the card →
- RankingMABACMABAC ranks alternatives not against an ideal or an average, but against their distance from a hypothetical "border area" built for every criterion. Sitting above the border strengthens an alternative; sitting below it weakens one.Open the card →
- RankingMOORAOne of the lightest ranking methods to compute, MOORA ranks alternatives by scaling each criterion value against that criterion's total magnitude, then subtracting the sum of the harmful ratios from the sum of the beneficial ratios.Open the card →
- RankingGRAGRA ranks alternatives by a "grey relational grade": how closely each one tracks a hypothetical "reference" alternative that holds the best performance on every criterion.Open the card →
- EfficiencyDEADEA is a benchmarking method that compares multiple units of the same kind by how well they convert inputs into outputs. It gives every unit an efficiency score between 0 and 1; it is not a preference-ranking method.Open the card →
- RankingCoCoSoA method that evaluates alternatives with both an additive and a multiplicative measure of performance, then ranks them by combining these two measures through three different compromise strategies.Open the card →
- RankingMULTIMOORAA method that ranks alternatives separately from three distinct viewpoints, ratio, distance from the worst case, and full multiplication, then combines those three rankings into a single order through dominance theory.Open the card →
- RankingWPMWPM raises each alternative's ratio on every criterion to a power equal to that criterion's weight, multiplies these together into a single unit-free score, and ranks alternatives on that score.Open the card →
- RankingELECTRE IIELECTRE II does not settle for ELECTRE I's core-set output. It runs the same outranking logic in two directions at once, from the best alternative downward and from the worst upward, and places every alternative in a full order. Where the two directions disagree, it prefers to say "incomparable" rather than force a verdict.Open the card →
- RankingSPOTISSPOTIS ranks alternatives by their distance to a fixed ideal point. That point is not built from the other alternatives in a given analysis but from "best possible / worst possible" bounds fixed before the analysis begins. The method thereby aims to prevent the ranking from shifting as the alternative set changes, that is, to prevent rank reversal.Open the card →
- RankingAROMANAROMAN does not rely on a single form of normalisation. It blends two different normalisations with a mixing coefficient, then combines the benefit and cost totals with a balance parameter to rank the alternatives.Open the card →
- RankingMAUTMAUT first converts the value on each criterion into its own "utility" scale, then sums these utilities with weights. The result is a single figure for how much total utility an alternative delivers to the decision-maker.Open the card →
- RankingPSIPSI asks for no external criterion weights. It derives them itself from how much the alternatives differ on each criterion, then ranks the alternatives using those weights.Open the card →
- RankingRAFSIRAFSI maps alternatives onto a single scale interval against fixed ideal and anti-ideal points the decision-maker sets in advance, then ranks them. Because these points are fixed, the ranking does not break when an alternative is added or removed.Open the card →
- RankingRAWECRAWEC measures every alternative, on a weighted basis, both by "how close to the best" and "how far from the worst" it sits, then combines these two perspectives into a single comparison index.Open the card →
- RankingWISPWISP scores each alternative through four separate comparison logics, based on both summing and multiplying, and averages these four results into a single ranking.Open the card →
- RankingCRADISA method that assesses alternatives through two separate utility ratios, one for how close they sit to the ideal point and one for how far they sit from the worst point, and ranks them by the average of these two ratios.Open the card →
- RankingELECTRE IIICompares pairs of alternatives on a fuzzy scale of "how credibly does one outrank the other" and distils these credibility degrees in two directions to derive an order; some pairs may remain incomparable.Open the card →
- RankingLMAWLMAW first standardises every cell in a way sensitive to both direction and magnitude, then passes it through a logarithmic transformation. It then sums these values through a weighted, bounded aggregation function to rank the alternatives. Its purpose is to stop extreme values from dragging the ranking to excess.Open the card →
- Objective weightingMERECMEREC derives criterion weights by looking at how much the alternatives' overall performance assessment would change if that criterion were removed from the table. The criterion that changes things most when removed receives the most weight.Open the card →
- RankingOCRAA method that separately sums the alternatives' relative shortfall on input (cost) criteria and their relative superiority on output (benefit) criteria, then combines the two at a common reference point to produce a ranking.Open the card →
- RankingROVROV ranks alternatives by the average of their best-case performance on benefit criteria and their worst-case performance on cost criteria.Open the card →
- RankingSMARTSMART places each criterion's worst and best end directly onto a 0-to-1 scale, then sums these using importance weights supplied by the decision-maker; it is a simple multi-attribute rating method.Open the card →
- RankingAPLOCOAPLOCO compares alternatives two at a time: it sums how far each alternative leads its rival on each criterion, subtracts how far it trails, and ranks alternatives by the net score that remains.Open the card →
- RankingCOBRACOBRA ranks alternatives by combining their distance to four separate reference points (best, worst, above-average and below-average), rather than looking at a single ideal point from four different angles.Open the card →
- RankingCompromise ProgrammingCompromise Programming ranks alternatives by how far they fall short of the best achievable value on each criterion; the alternative that falls short the least stands out as the best compromise.Open the card →
- RankingERVDERVD judges every alternative not against an "ideal point" but against a reference (expectation) level the decision-maker has set in advance; it weighs losses below that reference more heavily than gains above it.Open the card →
- RankingEVAMIXWhen some criteria are measured numerically and others are expressed only as a ranking (first, second, third), EVAMIX combines the two types in a single analysis without converting one into the other.Open the card →
- RankingFUCAFUCA compares alternatives not by their raw figures but by their rank on every criterion; the alternative with the smallest weighted sum of criterion ranks comes out on top.Open the card →
- RankingGoal ProgrammingGoal Programming first sets an attainable target level for every criterion, then compares alternatives by how far they fall short of that target; the alternative that approaches the targets with the least deviation comes out on top.Open the card →
- RankingHELLWIGThe Hellwig method ranks units, without using any externally supplied weight, by their distance from a statistical "development pattern" that it builds out of their own data.Open the card →
- RankingLoPMLoPM assigns each property its own limit, a floor, a ceiling or a target value, and scores alternatives by how well they meet that limit before summing the scores by weight.Open the card →
- RankingMACONTRather than relying on a single form of scale equalisation, MACONT blends three different normalisations, scores every alternative in two separate ways, one comparing it against an average rival and one looking at its best-worst extremes, then combines these two scores.Open the card →
- RankingMAIRCAMAIRCA measures the gap between what each alternative "theoretically deserves" as a share and what it "actually delivers" in performance, and puts forward the alternative with the smallest gap.Open the card →
- RankingMARAMARA compares every alternative with a hypothetical "ideal alternative" and measures the gap as the area beneath a line segment; the smaller this area, the further ahead the alternative stands.Open the card →
- RankingMOOSRAMOOSRA divides each alternative's total weighted strength on the benefit criteria by its total weighted burden on the cost criteria, and brings forward the alternative with the largest such ratio.Open the card →
- RankingORESTEORESTE is a method that compares alternatives and the importance of criteria not by exact figures but purely by their ranks, producing a single order.Open the card →
- RankingOWAOWA is an aggregation method that weights criterion values not by which criterion they came from but by the rank they occupy within each alternative, letting the decision-maker's optimistic or cautious attitude show up directly in the result.Open the card →
- RankingPAMPAM turns every alternative into a polygon with as many sides as there are criteria, and ranks alternatives by the area that polygon covers.Open the card →
- RankingPIVPIV ranks alternatives solely by their distance from the best value attainable on each criterion; unlike TOPSIS, it does not take the worst point as a reference.Open the card →
- RankingPROBIDPROBID is a ranking method that judges alternatives not by distance to a single ideal point, but by distance to a whole series of hypothetical "rank" points running from best to worst, and to their average.Open the card →
- RankingPROSA-CPROSA-C corrects the balanced score PROMETHEE II produces with a penalty that measures whether an alternative built that score from a single criterion or evenly across all of them; an alternative that shines on one criterion while staying weak on the rest is pulled back.Open the card →
- RankingQUALIFLEXQUALIFLEX tries every possible ordering of the alternatives in turn and, by summing how well each criterion agrees with that ordering, selects the ordering with the highest total agreement.Open the card →
- RankingRAMRAM accumulates each alternative's total contribution on benefit and cost criteria separately, then collapses them into a single number by placing cost in a power exponent and benefit in a base value: a high cost shrinks the exponent, a high benefit grows the base.Open the card →
- RankingRank Reversal AnalysisRank Reversal Analysis does not compute a ranking method's result once and stop there; it reruns the same method after adding a new candidate to the alternative set or removing one, and counts whether the remaining alternatives' order relative to one another breaks.Open the card →
- RankingRAPSRAPS compares two alternatives directly, measures the size of the gap between them, and ranks every alternative by this "how much better" strength against all its rivals.Open the card →
- RankingREGIMEREGIME compares two alternatives not by the magnitude of their numbers but purely by who is better and who is worse on each criterion, then sums this simple superiority information with the criterion weights to build a ranking.Open the card →
- RankingRIMRather than assuming "more is always better," RIM defines a target range for every criterion and ranks alternatives by how close they sit to that target range.Open the card →
- RankingSECASECA does not take criterion weights from outside; while ranking the alternatives, it derives the weights too, from the same calculation, out of its own data.Open the card →
- RankingSIMUSSIMUS turns each criterion in turn into an "objective" and solves a linear programming problem; the shares it hands to the alternatives fall out of these repeated solutions.Open the card →
- RankingSPROBIDSPROBID is a lighter-weight form of PROBID; it ranks alternatives not against every reference point in between, but only against the references in the best and worst quartile.Open the card →
- RankingTAXONOMYTAXONOMY standardises alternatives on each criterion against their own mean and standard deviation, then converts their distance to a hypothetical "best" reference point into a single measure of development.Open the card →
- RankingWEDBAWEDBA ranks alternatives by their weighted Euclidean distance to two hypothetical points built from the best and worst value on every criterion; the alternative far from the worst and close to the best comes out on top.Open the card →
- OutrankingEXPROM IEXPROM I evaluates the difference between two alternatives on two levels, "somewhat better" and "much better, almost beyond dispute", and leaves pairs that cannot be clearly compared unranked rather than forcing them into an order.Open the card →
- OutrankingEXPROM IIEXPROM II evaluates the difference between two alternatives on two levels, "somewhat better" and "much better, almost beyond dispute". Unlike EXPROM I, it reduces every alternative to a single net-flow score and gives a complete ranking.Open the card →
- OutrankingPAMSSEM IPAMSSEM I compares alternatives pairwise and measures how far one outranks the other in each pair; in some pairs this comparison yields no clear result, and the two alternatives remain incomparable.Open the card →
- OutrankingPAMSSEM IIPAMSSEM II uses the same concordance and flow calculation as PAMSSEM I, but at the end places every alternative in order by its net flow; it leaves no incomparable pair, always producing a complete ranking.Open the card →
- OutrankingSIRSIR calculates separately how much each alternative outperforms the others and how much it falls behind them, then combines these two values into a single net score to rank the alternatives.Open the card →
- Subjective weightingANPANP models the relationship between criteria and alternatives not as a one-way hierarchy but as a network of mutual interactions, and produces weights from the point where that network settles into equilibrium.Open the card →
- Subjective weightingThe Delphi MethodDelphi collects opinion from experts round by round, without them knowing one another's identity, and shows each round a summary of the previous one to track whether the views are converging on a consensus.Open the card →
- Subjective weightingDIBRDIBR asks the expert to rank criteria by importance and to state only the share between each pair of consecutive criteria; it then derives the weights from these consecutive shares in a chain.Open the card →
- Subjective weightingFUCOMFUCOM asks the expert to rank the criteria by importance and to state only the importance ratio between successive criteria; it then finds the weights through a calculation that matches these ratios as consistently as possible.Open the card →
- Subjective weightingFuzzy DelphiFuzzy Delphi asks experts not for a single number but for a triangular range in the form "at least, most likely, at most"; it pools the opinion across experts by combining these triangles and reduces them to a single central value that becomes a weight.Open the card →
- Subjective weightingLBWALBWA asks the expert first to select the most important criterion, then to split the remaining criteria into a few levels of importance and give each a small influence score within its level; no pairwise comparison is made between criteria.Open the card →
- Subjective weightingPIPRECIAPIPRECIA takes criteria in any order and asks, for each one, a single question: is it more important than the previous criterion, equally important, or less important; unlike SWARA, it does not require the criteria to be pre-ranked by importance.Open the card →
- Subjective weightingREVISED-SIMOSA subjective weighting method that has an expert arrange cards representing criteria from least to most important, measures the size of an importance gap through blank cards placed between them, and fixes the scale with a single extreme ratio.Open the card →
- Subjective weightingROCA subjective weighting method that assigns weights to criteria from ranking information alone, asking for no numerical comparison at all, and computes them with a closed formula.Open the card →
- Subjective weightingSIWECA subjective weighting method that takes direct scores from several experts and derives criterion weights from how consistently discriminating each expert's own scoring is.Open the card →
- Subjective weightingSWINGA subjective weighting method that asks the expert to score, directly out of 100, the benefit of "swinging" each criterion from its worst to its best value, then normalises those scores to produce weights.Open the card →
- Objective weightingCCSDAn objective weighting method that derives criterion weights from both each criterion's own spread and that criterion's relationship with the overall evaluation, by solving a system of non-linear equations.Open the card →
- Objective weightingCILOSCILOS derives criterion weights from the data itself by measuring how much choosing the best alternative on one criterion costs you on every other criterion.Open the card →
- Objective weightingGini Coefficient WeightingAn objective weighting method that derives a criterion's weight from how unequally the alternatives' shares are distributed on that criterion: where the share is concentrated in a few alternatives the criterion receives a high weight, where the share is spread equally across everyone it receives a low weight.Open the card →
- Objective weightingIDOCRIWAn objective weighting method that derives criterion weights by using two different objective measures together: how well the data discriminates between alternatives, and the loss that would follow from disregarding a criterion.Open the card →
- Objective weightingLODECIRather than asking an expert for criterion weights, LODECI derives them from the sharpest difference found between alternatives: however far apart at least one pair of alternatives sits on a criterion, that criterion gains a correspondingly greater say in the decision.Open the card →
- Objective weightingLOPCOWLOPCOW derives criterion weight from the spread within the data itself: the more a criterion makes alternatives "lose out" relative to the best, the more weight that criterion gains.Open the card →
- Objective weightingMPSIMPSI takes an intermediate value that the Preference Selection Index method uses silently, inside itself, to rank alternatives, and presents it directly as a visible criterion weight.Open the card →
- Objective weightingNMDNMD derives criterion weight from the data's own mean: the further, on average, the alternatives sit from the best value on a criterion, the more weight that criterion gains.Open the card →
- Objective weightingPCA WeightingPCA Weighting derives criterion weight from the shared movement between criteria: the more a criterion draws on the few "principal axes" that actually separate the alternatives, the more weight it earns.Open the card →
- Objective weightingSD-WEIGHTThe plainest objective weighting method there is: it derives a criterion's weight not by asking an expert but from how much the alternatives differ from one another on that criterion.Open the card →
- Objective weightingSPCAn objective method that treats the exact midpoint between a criterion's smallest and largest value as its "symmetry point" and derives criterion weights from how far the alternatives spread away from that point.Open the card →
- Objective weightingWENSLOAn objective method that treats each criterion's cumulative values as a zigzag line and derives criterion weight from the ratio of that line's length to its average slope.Open the card →
- SensitivityKendall's TauA coefficient that compares two rankings pair by pair, reduces the difference between concordant and discordant pairs to a single figure, and measures how closely two rankings coincide.Open the card →
- SensitivityKendall's WA method that reduces how closely the rankings given by three or more rankers (experts, methods, criteria) resemble one another to a single concordance coefficient between zero and one.Open the card →
- SensitivitySpearman Rank CorrelationA method that measures how alike two separate rankings are with a single number: plus one means perfect agreement, minus one means perfect disagreement, and zero means no relationship at all.Open the card →
- Aggregation and votingChoquet IntegralThe Choquet integral combines criteria not with fixed weights but with an "importance measure" assigned to groups of criteria, so that synergy and redundancy relationships between criteria are taken into account.Open the card →
- PROMETHEE extensionsPROMETHEE IThis is the form within the PROMETHEE family that keeps the incoming and outgoing flows separate rather than merging them into a single net flow, and honestly leaves some pairs of alternatives "incomparable." Its output is not a complete ranking but a partial dominance relation.Open the card →
- PROMETHEE extensionsPROMETHEE IIIThis is the form within the PROMETHEE family that presents every alternative's net flow not as a single number but as a confidence interval. Two alternatives are ranked strictly only if their intervals do not overlap; if the intervals overlap, the two are treated as indifferent.Open the card →
- PROMETHEE extensionsPROMETHEE VIThis is the form of PROMETHEE that turns the ranking into an interval for situations where the weights are not known exactly. Every alternative's net flow is not a single number but the lowest and highest value it can take while the weights vary within a plausible band.Open the card →
- ELECTRE extensionsELECTRE IVThis is the member of the ELECTRE family that assigns no weight to criteria at all. It works with three thresholds per criterion (indifference, preference, veto), and its output is not a complete ranking but a partial pre-order that emerges from a two-way distillation.Open the card →
- DEA extensionsData envelopment analysis BCC (variable returns to scale)This is the form of DEA for situations where the units being compared differ in size and that size difference must not distort the efficiency comparison. The output remains an efficiency score, together with every unit's returns-to-scale classification (advantaged at small scale, or at large scale).Open the card →
- DEA extensionsDEA cross-efficiencyThis is the form of DEA where every unit is evaluated not only by its own chosen weights but also by every other unit's chosen weights, with units scoring one another reciprocally. The output is a single cross-efficiency average for every unit, and this average places the units in a complete ranking.Open the card →
- DEA extensionsDEA Range-Adjusted Measure of Inefficiency (RAM)RAM is a form of DEA that measures and sums, separately for each measure against its own value range, the input excess and output shortfall that a classical radial (percentage) score can overlook. The output is again an inefficiency score between 0 and 1, but this score captures not only the proportional contraction but also any remaining slack.Open the card →
- DEA extensionsSlacks-Based Measure DEA (SBM)SBM is a form of DEA that, instead of a classical proportional contraction ratio, directly measures every input excess and output shortfall on its own scale. The result is again an efficiency score between 0 and 1, but this score rests not on a ratio but directly on the slack share.Open the card →
- DEA extensionsSuper-Efficiency DEASuper-efficiency DEA is a form that allows units classical DEA rates as equally "efficient" (theta=1) to be ranked amongst themselves as well. Each unit is re-evaluated with its own data excluded from the reference set; this brings out a degree of superiority even among efficient units.Open the card →
- SPOTIS extensionsBalanced SPOTISBalanced SPOTIS is the form of SPOTIS that, alongside the fixed ideal, also takes into account a "realistic target" point set by the decision-maker. It blends the distance to the two reference points with a single coefficient, and still ranks alternatives by one distance value.Open the card →
- SMART extensionsSMART weightingSMART weighting runs, on its own, the step of SMART that converts importance ratings into weights. Its input is not an alternative table but only the importance ratings given to criteria; its output is a weight vector that sums to 1.Open the card →
Methods without a card yet
These methods do not yet have an academy card; they can be used in an analysis, and each opens here once its card is ready.
- VIKOR-SMAA - VIKOR with Stochastic Multicriteria Acceptability Analysis2001