Case Based Approach

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Chapter 3 Case Based Distance Approach to Vendor Evaluation
3.1. Case-Based Decision Analysis Approaches
There has been much progress on case-based approaches to MCDA in recent years. As suggested in [14], the case set may include (1) cases on which the DM has made a decision in the past; (2) fictitious but realistic alternatives; or (3) a representative subset of the actual set of alternatives, A. A main advantage of case-based reasoning is that “decision makers may prefer to make exemplary decisions than to explain them in terms of specific functional model parameters”. To achieve these advantages, it is helpful if the cases are sufficiently familiar to the DM that they are easy to evaluate. As well, the case set should contain a broad range of cases, and should not be too small or too large.
3.1.1 Case-based approaches to ranking and sorting
Generally, case-based approaches to preference elicitation in MCDA include the three steps shown in Figure 3.1
1. Represent: Identify representative cases from the full set of alternatives, or else- where, and present them to the DM for preference assessment.
2. Infer: Find preference parameters that reproduce the DM’s judgments on the representative cases as accurately as possible.
3. Assess: If the preference parameters are sufficient, apply them to the full set of alternatives to obtain preferences.
Then, with the appropriate tools, the selected problématique can be addressed.

Fig. 3.1 Case-based Approach to MCDA
The case-based approaches that have been proposed can be roughly grouped into two classes, depending on whether they depend on models with explicit or implicit preferences. For an explicit preference model such as the UTA method [15] or the case-based distance approach [16]...

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...analyze multiple criteria ranking problems based on the proposed case-based distance models is shown in Figure 3.2. It includes the following steps:
• Identify the alternative set: All possible alternatives within appropriate boundaries should be considered.
• Construct the criteria set: Build a criteria set to reflect the DM’s concerns and objectives.
• Select the case set: Choose a small case set among the alternative set and ask experts to provide a ranking on this case set.
• Establish the case-based distance ranking model: Construct the ranking model, optimize it and obtain the criteria weights.
• Verify the feasibility of the model: Use the weight information to calculate the distance of case set and verify whether the ranking order is consistent with the experts’ evaluation result.
• Rank all alternatives: Apply the model to rank all alternatives.

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