Asset Details
Do you wish to reserve the book?
Multi-criteria decision-making method based on dominance degree and BWM with probabilistic hesitant fuzzy information
Hey, we have placed the reservation for you!
By the way, why not check out events that you can attend while you pick your title.
Oops! Something went wrong.
Looks like we were not able to place the reservation. Kindly try again later.
Are you sure you want to remove the book from the shelf?
Multi-criteria decision-making method based on dominance degree and BWM with probabilistic hesitant fuzzy information
Do you wish to request the book?
Multi-criteria decision-making method based on dominance degree and BWM with probabilistic hesitant fuzzy information
Please be aware that the book you have requested cannot be checked out. If you would like to checkout this book, you can reserve another copy
We have requested the book for you!
Your request is successful and it will be processed during the Library working hours. Please check the status of your request in My Requests.
Oops! Something went wrong.
Looks like we were not able to place your request. Kindly try again later.
Journal Article
Multi-criteria decision-making method based on dominance degree and BWM with probabilistic hesitant fuzzy information
2019
Overview
In this paper, multi-criteria decision-making (MCDM) methods with probabilistic hesitant fuzzy information are proposed based on the dominance degree of probabilistic hesitant fuzzy elements (PHFEs) and best worst method (BWM). First, we discuss the probabilistic distribution function of PHFE and the dominance degree matrix between two PHFEs. The dominance degree matrix is constructed based on the probabilistic distribution function of PHFE, which can be characterized as a fuzzy complementary judgment matrix. Second, BWM is extended to fuzzy preference relations based on the constructed dominance degree matrix. Subsequently, an algorithm is designed for selecting the best and worst weight vectors, and then two models are developed based on additive consistency and multiplicative consistency of fuzzy preference relations to derive the criteria weights. In addition, an algorithm is presented to improve the consistency of the dominance degree matrix when a desired consistency level is not achieved. Finally, the selection of best investment company is provided as an example to demonstrate the feasibility and effectiveness of the proposed methods.
Publisher
Springer Berlin Heidelberg,Springer Nature B.V
Subject
