5/30/2014 Aosta, May 24th 2012 SESAMO: a decision support system for the Multi Criteria Analysis...

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04/10/23Aosta, May 24th 2012

SESAMO: a decision support system for the Multi Criteria Analysis

Fiorella GRASSO, Stefano MARAN (PP3)

Project Final MeetingAosta, May 24th 2012

Aosta, May 24th 2012

SESAMO

SESAMO is a decision support system based on the methodology of the multi criteria analysis.

The MCA application in SESAMOstep by step

1. Identify the alternatives2. Identify criteria and indicators and

build the evaluation tree3. Aggregate indicators4. Quantify indicators5. Choice the utility functions6. Weight indicators and criteria (with the

contribution of different stakeholders)7. Evaluate the performance of each

alternative8. Perform the sensitivity analysis

(uncertainty influence on alternative performance)

The MCA procedure in SESAMO is articulated in 8 different steps:

1. Identify the alternatives

Firstly, you have to create an MCA project and identify the alternatives.

A project alternative must represent all the possible actions that a designer is able to do to influence future events.

no MIF

20% MIF

40% MIF

1. Identify the alternativesAn alternative is able to have an influence on the indicators representing the system. In other words,

each alternative will produce some modification on some indicators, but not necessarily on all of them.

2. Identify criteria, indicators

The hierarchical structure of the evaluation tree

3. Let’s aggregate indicators

You can assign to a criterion a value that is derived from the aggregation of its children nodes.For example, you can assign to the hydrological regime the weighted average of th regimes for each month of the year. For example, you can assign to the hydrological regime the weighted average of th regimes for each month of the year.

4. Quantify criteria and indicators

the criteria are on the lines

the alternatives are on the columns

Then, we get an evaluation matrix

5. Choice the utility functions• We can express the decision maker satisfaction about a single indicator by

using the Utility Functions

• Through the normalization process of the Utility Functions, the indicators loose their dimension and BECOME COMPARABLE each other because they are transformed in adimensional values.

6. Assign weights

Weights represent the mechanism through which a stakeholder can express his idea about the relative importance among criteria.

6. Assign weights

Free Weights Allocation

This technique consists on assigning a weight to each leaf of the tree, without taking into account the hierarchic structure of the criteria.

6. Assign weights

Hierarchical weights allocation

It is possible to assign coefficients for every group of nodes that are children of the same node, for every level of the tree. Inside each group, the sum of the coefficients must be equal to 1.

0.50.3

0.20.6

7. Performances of the alternatives

This chart highlights which of the selected criteria gives the biggest contribution to the final result.

The ranking of the alternatives

7. Performances of the alternatives

The graph represents the overall performance of the selected alternatives, computed considering all criteria. In this representation, the radius represents the utility value, while the angle represents the weight.

8. Perform the Sensitivity Analysis

A decisional process is strongly influenced by the concepts of uncertainty and subjectivity.

The sensitivity analysis allows to understand how the final ranking of the alternatives can vary if impacts, utility functions or weights assume values that are not the reference values.

In this panel you can analyse how robust is the ranking of the alternatives, in relation to the given vector of weights.

More attention to the environment

More attention to the production

The “dashboard” controls are used to change the height of the weight in relation with the others; you can view the performance of the alternatives

5/30/2014 Aosta, May 24th 2012 SESAMO: a decision support system for the Multi Criteria Analysis...

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