Abstract
In this study, an improved VIKOR method was presented to deal with multi-attribute decision-making based on three parameters interval fuzzy number. The attribute weights were unknown but alternative priority of object preference was given. A new non-linear rewards and punishment method in positive interval was proposed to make the attributes normal, information covered reliability and relative superiority degree two methods were used to compare and sort the Three Parameters Interval Fuzzy Number (TPIFN) and a quadratic programming based on contribution was constructed to get attribute weights, then defined the information entropy distance between TPIFN and the optimum object orders was obtained by VIKOR. The numerical example was provided to demonstrate the feasibility and validity.
Highlights
Fuzzy analysis leads an important role in MultiAttribute Decision Making (MADM) and it has made a great progress
With alternative priority of known in advance, information covered reliability and relative superiority degree methods are given and a quadratic programming is constructed to get attribute weights, Three Parameters Interval Fuzzy Number (TPIFN) distance formula based on information entropy is defined and is introduced to VIKOR to make decision
An improved VIKOR method was presented to deal with multi-attribute decision-making based on three parameters interval fuzzy number
Summary
Fuzzy analysis leads an important role in MultiAttribute Decision Making (MADM) and it has made a great progress. In view of above, improved non-linear rewards and punishment method in [0, 1] is proposed to normalize the TPIFN. With alternative priority of known in advance, information covered reliability and relative superiority degree methods are given and a quadratic programming is constructed to get attribute weights, TPIFN distance formula based on information entropy is defined and is introduced to VIKOR to make decision.
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