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Ana Sara Costa

Publications and source records attributed to Ana Sara Costa.

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A robust hierarchical nominal classification method based on similarity and dissimilarity using loss function and an improved version of the deck of cards method

Cat-SD is a multiple criteria decision aiding method for dealing with nominal classification problems. Actions are assessed according to multiple criteria and assigned to one or more categories. A set of reference actions is used for defining each category. The assignment of an action to a given category depends on the comparison of the action to each reference set according to likeness thresholds. Distinct sets of criteria weights, interaction coefficients, and likeness thresholds can be defined per category. We propose to apply Multiple Criteria Hierarchy Process (MCHP) to Cat-SD. An adapted MCHP is proposed to take into account possible interaction effects between criteria structured in a hierarchical way. On the basis of the known deck of cards method, we also consider an imprecise elicitation of parameters permitting to take into account interactions and antagonistic effects between criteria. The elicitation procedure we are proposing can be applied to any Electre method. With the purpose of exploring the assignments obtained by Cat-SD considering possible sets of parameters, we propose to apply the Stochastic Multicriteria Acceptability Analysis (SMAA). The SMAA methodology allows to draw statistical conclusions on the classification of the actions. The proposed method, SMAA-hCat-SD, helps the decision maker to check the effects of the variation of parameters on the classification at different levels of the hierarchy. We propose also a procedure, based on the concept of loss function, to obtain a final classification fulfilling some requirements given by the decision maker and taking into account the hierarchy of criteria and the probabilistic assignments obtained applying SMAA. Also this procedure can be applied to any classification Electre method.

cs.AI

A multiple criteria nominal classification method in a web-based platform: Demonstration in a case of recruitment for the Portuguese Army

CAT-SD (CATegorization by Similarity-Dissimilarity) is a recently developed method for handling nominal classification problems in the context of Multiple Criteria Decision Aiding (MCDA). This paper describes the design and implementation of this method, as well as an application dealing with a recruitment process in the Special Forces of the Portuguese Army. In addition, it proposes interaction protocols to elicit the preference parameters of the method to facilitate the construction of a decision model when the analyst guides the decision maker. CAT-SD has been implemented in DecSpace, a user-friendly on-line platform for supporting decision aiding processes using one or more MCDA methods. The study related to the Portuguese Army Special Forces recruitment presents and demonstrates how these protocols and a tool like DecSpace can facilitate the process of applying the method in real-world scenarios.

math.OC