Attribute Selection Method based on Objective Data and Subjective Preferences in MCDM

Xiaofei Ma, Yi Feng, Yi Qu, Yang Yu

Abstract


Decision attributes are important parameters when choosing an alternative in a multiple criteria decision-making (MCDM) problem. In order to select the optimal set of decision attributes, an analysis framework is proposed to illustrate the attribute selection problem. Then a two-step attribute selection procedure is presented based on the framework: In the first step, attributes are filtered by using correlation algorithm. In the second step, a multi-objective optimization model is constructed to screen attributes from the results of the first step. Finally, a case study is given to illustrate and verify this method. The advantage of this method is that both external attribute data and subjective decision preferences are utilized in a sequential procedure. It enhances the reliability of decision attributes and matches the actual decision-making scenarios better.

Keywords


attribute selection, multi-criteria decision-making (MCDM), multiobjective optimization, attribute correlation

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References


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DOI: https://doi.org/10.15837/ijccc.2018.3.3188



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