Provider: | PUT |
---|---|
Version: | 1.0.0 |
Computes aggregated preference indices with reinforced preference effect
This module is an extended version of ‘PrometheePreference’ - it brings the concept of ‘reinforced_preference’, which boils down to the new threshold of the same name and a new input file where the ‘reinforcement factors’ are defined (one for each criterion where ‘reinforced_preference’ threshold is present).
(For outputs, see below)
Criteria to consider.
Alternatives to consider.
The performance of alternatives.
Optional: yes, enabled by default
The performance of profiles (boundary or central).
Preference direction (min or max) specified for each criterion.
Preference, indifference and sigma thresholds for criteria (as constants as well as linear functions). Gaussian function needs inflection point (sigma), rest of functions need preference or indifference thresholds.
Weights of criteria to consider.
Optional: yes, enabled by default
ID number of predefined preference function specified for each criterion.
Definitions of so-called ‘reinforcement factors’, one per each criterion for which ‘reinforcement threshold’ has been defined. For more regarding these concepts see the paper from ‘Reference’ section.
This input is mandatory, if you don’t need the concept of reinforced preference please use ‘PrometheePreference’.
Optional: yes, enabled by default
Definitions of central or boundary profiles connected with classes (categories)
First parameter specifies the type of elements provided for comparison.
Choosing ‘boundary_profiles’ or ‘central_profiles’ requires providing inputs ‘classes_profiles’ and ‘profiles_performance_table’ as well (which are optional by default).
Second parameter specifies the type of function used for comparison of each criterion. Choosing ‘specified’ requires providing inputs “generalised_criterion” which is optional by default. Choosing some of numbers sets same function for all criteria.
Tag: programParameters
Code:
<programParameters>
<parameter id="comparison_with" name="comparison_with">
<values>
<value>
<label>%1</label>
</value>
</values>
</parameter>
<parameter id="criterion" name="generalised_criterion">
<values>
<value>
<label>%2</label>
</value>
</values>
</parameter>
</programParameters>
Aggregated preference matrix computed from the given data. This matrix aggregates partial preference indices from all criteria into single preference index per pair of alternatives or alternatives/profiles.
Preference matrix computed from the given data. This matrix contains partial preference indices for all criteria and all pairs of alternatives or alternatives/profiles.
Messages or errors generated by this module.
For further technical details on the web service underlying this program, have a look at its documentation here.