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Soft Computing
Published in: Soft Computing 12/2020

13-11-2019 | Methodologies and Application

Some new information measures for hesitant fuzzy PROMETHEE method and application to green supplier selection

Authors: Shu-ping Wan, Wen-chang Zou, Long-gen Zhong, Jiu-ying Dong

Published in: Soft Computing | Issue 12/2020

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Abstract

Due to the increasing complexity and uncertainty in green supplier selection, there would be some hesitations for decision makers (DMs) to provide evaluation information of suppliers. Hesitant fuzzy set is a suitable tool to model such hesitations. This paper develops a hesitant fuzzy Preference Ranking Organization Method for Enrichment Evaluations (PROMETHEE) for multi-criteria group decision-making and applies to green supplier selection. First, a new hesitancy index of hesitant fuzzy element (HFE) is defined. Then, a generalized hesitant fuzzy Hausdorff distance is proposed considering the individual deviation of membership values and the hesitancy index simultaneously. A combined hesitant fuzzy entropy is presented integrating the defined fuzziness entropy and hesitancy entropy of HFEs. Subsequently, a linear programming model is established to derive DMs’ weights objectively. To determine the criteria weights for each DM, a nonlinear programming model is built through minimizing the relative entropy. The PROMETHEE is employed to obtain individual ranking of alternatives for each DM. To obtain the collective ranking of alternatives, a multi-objective assignment model is constructed and transformed into a single-objective assignment model for resolution. Thereby, a hesitant fuzzy PROMETHEE method is presented. A green supplier selection example is demonstrated to validate the proposed method.
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Metadata
Title
Some new information measures for hesitant fuzzy PROMETHEE method and application to green supplier selection
Authors
Shu-ping Wan
Wen-chang Zou
Long-gen Zhong
Jiu-ying Dong
Publication date
13-11-2019
Publisher
Springer Berlin Heidelberg
Published in
Soft Computing / Issue 12/2020
Print ISSN: 1432-7643
Electronic ISSN: 1433-7479
DOI
https://doi.org/10.1007/s00500-019-04446-w

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