WEB-MAUT-DSS




Create node

Delete node

Project information:

Select an objective:

Units:

Minimum value:

Maximum value:

Most preferred

Attribute values:

Select an attribute:

Select an objective:

Update performances

Remove alternative


Select an objective:

Download
Select chart:

Select the type of weight stability interval:

 
0%

Current average weight:

Weight stability interval:

Non-dominated

alternatives

Potentially optimal

alternatives

 
0%

Pairwise dominance

values

Attribute list:

Attribute ranking:

Drag
&
drop
Most
important

Least
important
Drag
&
drop
Most
important

Least
important

Node Information:

Label:

Name:

Description:

Units:

Minimum value:

Maximum value:

Most preferred

Insert attribute value (label):

Attribute values:

Continuous attribute
Discrete attribute
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Attribute name:

Download
Select chart:

Select the type of weight stability interval:

 
0%

Current average weight:

Weight stability interval:

Message area:

Working area:

Attribute range
(
,
)
Most preferred:
Attributes values
Component utilities
Probability value
Sure amount
(
(
(
0.25
0.75
0.50
0.50
0.75
0.25
)
)
)
~
~
~
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,
)
)
)
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is preferred or
is preferred or
is preferred or
equivalent to
equivalent to
equivalent to
(
(
(
0.5
0.5
0.5
0.5
0.5
0.5
)
)
)
(
(
(
0.5
0.5
0.5
0.5
0.5
0.5
)
)
)
is preferred or
is preferred or
is preferred or
equivalent to
equivalent to
equivalent to
Probability value
(
(
(
p
1-p
p
1-p
p
1-p
)
)
)
~
~
~
with p in
with p in
with p in
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)
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(
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is preferred or
is preferred or
is preferred or
equivalent to
equivalent to
equivalent to
(
(
(
)
)
)
(
(
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)
)
)
is preferred or
is preferred or
is preferred or
equivalent to
equivalent to
equivalent to
(
(
(
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)
)
CE-method
PE-method
Component utility function
Attribute values
Component utilities
(
,
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)
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,
)
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,
)

Descendent node

(

(

(

(

(

Imprecise weights

,

,

,

,

,

)

)

)

)

)

Provide a probability interval for p for which you are indifferent between the lottery and the sure performances:

p

1 - p

~

with p in ( , )

Objective list:

Drag
&
drop

Objective ranking

Most

important


Least

important

Information of the strength of the differences between the weights of the consecutive objectives in the ranking.

Most

important


Least

important

Objective ranking

Differences

Drag
&
drop

Ranking of differences

Most

important


Least

important

Objective ranking

Attribute Name:

Range:

(
,
)

Probability Dist.

Param. 1

Param. 2

Discrete values

Alternative Name:

Alternative performance:


Range

Probability Dist.

Param. 1

Param. 2

Discrete values

Objective:

Select an alternative:

Objective:

Select an alternative:

Objective:

Select an alternative:

Select an alternative:

Download

WEB-MAUT-DSS

The WEB-MAUT-DSS was designed and implemented by Prof. Antonio Jiménez Martín and Alberto Gómez Jiménez

Daniel Fernández Gómez, Daniel Fernández-Pello, Alejandro M. Hernández Segovia, Chenhao Hu, Alberto Pérez Conti, Carlos E. Pérez Núñez, and Jorge Verdugo Arroyo contributed to the development of various functionalities of WEB-MAUT-DSS as part of their Bachelor’s theses at the Universidad Politécnica de Madrid.

The WEB-MAUT-DSS was developed using Shiny-RStudio . It is free for academic purposes

The development of WEB-MAUT-DSS was supported by the grants PID2021-122209OB-C31, RED2022-134540-T and PID2024-155179NB-C22 funded by MICIU/AEI/10.13039/501100011033.

Alternative Name:

Alternative performance:


Range

Probability Dist.

Param. 1

Param. 2

Discrete values

Select information to be added to the report:
Objective hierarchy
Component utilities
Local weights
Attribute weights
Alternative evaluation
Stack bar rankings
Radar charts
Comparative charts
Non-dominated and potentially optimality
Monte Carlo simulation on weights

Select the alternatives:

Select the example project to be uploaded:
1. Restoration of lake Svyatoye contaminated by radionuclides
Ecological Modelling
2. Contracting cleaning services in a European public underground transportation company
Decision Support Systems
3. Reusing domain ontologies on the basis of the NeOn methodology
(sport ontologies)
Int. J. of Information Technology & Decision Making

Attribute Name:

Evaluate the difference between the most important attribute and the least important attribute