Provider: | PUT |
---|---|
Version: | 0.1 |
Calculates stochastic results for alternative assignments, assignment-based preference relation and class cardinalities. The results are computed by sampling the space of compatible models.
(For outputs, see below)
A list of criteria (<criteria> tag) with information about preference direction (<criteriaValues mcdaConcept=”preferenceDirection”>, 0 - gain, 1 - cost) and number of characteristic points (<criteriaValues mcdaConcept=”numberOfCharacteristicPoints”>, 0 for the most general marginal utility function or integer grater or equal to 2) of each criterion.
A list of alternatives.
Tag: alternatives
Code:
<alternatives>
<alternative id="[...]">
<active>[...]</active>
</alternative>
[...]
</alternatives>
A list of categories (classes). List must be sorted from the worst category to the best.
Tag: categories
Code:
<categories>
<category id="[...]" />
[...]
</categories>
The performances of the alternatives.
Optional: yes, enabled by default
A list of assignment examples of alternatives to intervals of categories (classes) or to a specific category (class).
Tag: alternativesAffectations
Code:
<alternativesAffectations>
<alternativeAffectation>
<alternativeID>[...]</alternativeID>
<categoryID>[...]</categoryID>
</alternativeAffectation>
[...]
<alternativeAffectation>
<alternativeID>[...]</alternativeID>
<categoriesInterval>
<lowerBound>
<categoryID>[...]</categoryID>
</lowerBound>
<upperBound>
<categoryID>[...]</categoryID>
</upperBound>
</categoriesInterval>
</alternativeAffectation>
[...]
<alternativeAffectation>
<alternativeID>[...]</alternativeID>
<categoriesSet>
<categoryID>[...]</categoryID>
[...]
</categoriesSet>
</alternativeAffectation>
[...]
</alternativesAffectations>
Optional: yes, enabled by default
Two lists of assignment pairwise comparisons. A comparison from list with attribute mcdaConcept=”atLeastAsGoodAs” indicates that some alternative should be assigned to class at least as good as class of some other alternative (k = 0) or at least better by k classes (k > 0). A comparison from list with attribute mcdaConcept=”atMostAsGoodAs” indicates that some alternative should be assigned to class at most better by k classes (k > 0) then some other alternative. Note: usage of this kind of preference information significantly slows down computations.
Tag: alternativesComparisons
Code:
<alternativesComparisons mcdaConcept="atLeastAsGoodAs">
<pairs>
<pair>
<initial><alternativeID>[...]</alternativeID></initial>
<terminal><alternativeID>[...]</alternativeID></terminal>
<value><integer>k</integer></value>
</pair>
[...]
</pairs>
</alternativesComparisons>
<alternativesComparisons mcdaConcept="atMostAsGoodAs">
<pairs>
[...]
</pairs>
</alternativesComparisons>
Optional: yes, enabled by default
A list of category (class) cardinality constraints. It allows to define minimal and/or maximal desired category (class) cardinalities. Note: usage of this kind of preference information significantly slows down computations.
Tag: categoriesValues
Code:
<categoriesValues>
<categoryValue>
<categoryID>[...]</categoryID>
<value>
<interval>
<lowerBound><integer>[...]</integer></lowerBound>
<upperBound><integer>[...]</integer></upperBound>
</interval>
</value>
</categoryValue>
[...]
</categoriesValues>
Method parameters.
Parameter values can be defined via the GUI or the XMCDA file, by default via GUI.
Name: strictlyMonotonicValueFunctions
Whether marginal value functions strictly monotonic or not.
Name: numberOfSamples
Number of samples.
Tag: methodParameters
Code:
<methodParameters>
<parameter name="strictlyMonotonicValueFunctions">
<value>
<boolean>%1</boolean>
</value>
</parameter>
<parameter name="numberOfSamples">
<value>
<integer>%2</integer>
</value>
</parameter>
</value>
</parameter>
Stochastic assignments. The value for alternative a_i and category c_j equals to the rate of samples, for which alternative a_i was assigned to category C_j.
Tag: alternativesAffectations
Code:
<alternativesAffectations>
<alternativeAffectation>
<alternativeID>[...]</alternativeID>
<categoryID>[...]</categoryID>
<value>
<real>[...]</real>
</value>
</alternativeAffectation>
[...]
</alternativesAffectations>
Stochastic preference relation. Each value for pair (a_i, a_j) describes the rate of samples, for which alternative a_i was assigned to class at least as good as class of a_j.
Tag: alternativesComparisons
Code:
<alternativesComparisons mcdaConcept="atLeastAsGoodAs">
<pairs>
<pair>
<initial>
<alternativeID>[...]</alternativeID>
</initial>
<terminal>
<alternativeID>[...]</alternativeID>
</terminal>
<value>
<real>[...]</real>
</value>
</pair>
[...]
</pairs>
</alternativesComparisons>
Stochastic class cardinalities. Each category has sequence of n + 1 values, where n is the number of considered alternatives. First value corresponds to the cardinality 0, and next n values to subsequent cardinalities from 1 to n. i-th value for c_j class describes the rate of samples, for which i-1 alternatives were assigned to class c_j.
Tag: categoriesValues
Code:
<categoriesValues>
<categoryValue>
<categoryID>c01</categoryID>
<values>
<value>
<real>[...]</real>
</value>
<value>
<real>[...]</real>
</value>
[...]
</values>
</categoryValue>
[...]
</categoriesValues>
Messages generated by the program.
For further technical details on the web service underlying this program, have a look at its documentation here.