A New Prospect Projection Multi-Criteria Decision-Making Method for Interval-Valued Intuitionistic Fuzzy Numbers

Gao, Jianwei; Liu, Huihui

doi:10.3390/info7040064

Cited by 8 publications

(5 citation statements)

References 54 publications

(113 reference statements)

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“…(4) In terms of solution reliability, in the literature [90,91], the obtained results by using the model could change with a change in the parameter θ, which will cause some confusion to the decision-makers in the decision-making process. Meanwhile, in this paper, since the obtained attribute weights are stable, a unique ranking result can be obtained.…”

Section: The Ranking Results Of Alternative Suppliersmentioning

confidence: 99%

A Supplier Selection Decision-Making Approach for Complex Product Development Based on Hesitant Fuzzy Information

Li,

Su,

Yuan

et al. 2023

Axioms

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During the development process of complex products, selecting the best desirable alternative supplier is a challenge since an improperly selected alternative may cause losing capacity and increasing the cycle time and cost of development for a company. For this multiple-attribute decision-making problem of supplier selection, in this paper, a supplier selection problem in which the decision data are hesitant fuzzy information and the attribute weight is unknown in complex product development is investigated, and a supplier selection decision-making approach based on hesitant fuzzy information is proposed. Firstly, a bidirectional projection based on hesitant fuzzy information is established, and then the measurement equation for the degree of closeness is improved. Further, an attribute weight determination model which minimizes the projection total deviation for the hesitant fuzzy elements is constructed. By solving this model, scientific and reasonable attribute weights are provided. Subsequently, an illustrative example is employed to not only give the ranking result of alternative suppliers but also demonstrate the validity and feasibility of the developed approach. Meanwhile, sensitivity analysis and comparative analysis are put forward to illustrate the stability of the given final ranking result and the advantages and reliability of the constructed method. For alternative or strategy selection, this proposed approach can be used as a decision-making means when uncertainties are inherent.

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Section: The Ranking Results Of Alternative Suppliersmentioning

confidence: 99%

A Supplier Selection Decision-Making Approach for Complex Product Development Based on Hesitant Fuzzy Information

Li,

Su,

Yuan

et al. 2023

Axioms

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“…As a consequence of this, the TODIM method is founded on prospect theory and its application to the multi-criteria context. Other multi-criteria methods combined with prospect theory can be found in the articles by Lerche and Geldermann (2015), Gao and Liu (2016), Krohling and Souza (2012) and Qin et al (2015).…”

Section: The Todim Methodsmentioning

confidence: 99%

The TODIM multi-criteria method applied to the ANBIMA ranking of Brazilian investment funds

Sallum¹,

Gomes

Machado

2020

IJBSR

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ANBIMA, the Brazilian Financial and Capital Markets Association, monthly presents the ranking of investment funds management by category. This ranking makes available information about the management of resources from players that invested in funds in Brazil. The institutions that are included in this ranking are ordered based on the total amount of the net equity under management in all categories of investment funds. The research presented in this article applies the TODIM multi-criteria method for building the ANBIMA ranking of June 2017 using the ten best-positioned institutions. In order to accomplish this, each participating institution is considered as an alternative and each category of investment fund functions as a criterion. This allows for a comparison between the ANBIMA ranking against the ranking obtained by using the TODIM method. This comparison points to the possibility of making use of a new, enriched system to order the institutions based on pairwise analyses and taking into account expressions of gains and losses.

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“…There are different types of uncertainty that are taken into account when solving the MCDM tasks dependent on the problem considered. Among them, the following types of uncertainty and uncertainty focused theories in application to the MCDM should be dedicated: interval uncertainty [1], ordinal fuzzy sets theory [2], interval-valued fuzzy sets theory [3], type 2 fuzzy sets [4] (see the recent comprehensive review in [5] and the last applications in [6]), intuitionistic fuzzy sets [7], interval-valued fuzzy sets [8], hesitant fuzzy sets [9], Dempster-Shafer theory of evidence [10], evidential reasoning [11], rule-base evidential reasoning [12], rough sets theory [13] and soft set theory [14].…”

Section: Introductionmentioning

confidence: 99%

“…For simplicity of the analysis, let us assume that α NH 3 =1. Then from the above expression (8), given that n = 60, we get D = 0.4. We can see that formally, based on (8), the ecological situation in the vicinity of the ice cream factory is still better than in the vicinity of the chemical plant.…”

mentioning

confidence: 99%

A Fuzzy Multiple Criteria Decision Making Approach with a Complete User Friendly Computer Implementation

Dymova

Kaczmarek

Sevastjanov

et al. 2021

Entropy

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The paper presents the generalization of the almost forty years of experience in the field of setting and solving the multiple criteria decision-making (MCDM) problems in various branches of a human activity under different types of uncertainties that inevitably accompany such problems. Based only on the pragmatic intentions, the authors avoid the detailed descriptions of the known methods for the decision-making, while instead focusing on the most frequently used mathematical tools and methodologies in the decision-making practice. Therefore, the paper may be classified as a special kind of illustrative review of the mathematical tools that are focused on applications and are the most used in the solutions of MCDM problems. As an illustrative example, a complete user-friendly computer implementation of such tools and methodology is presented with application to the simple “buying a cat” problem, which, however, possesses all the attributes of the hierarchical fuzzy MCDM task.

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A New Prospect Projection Multi-Criteria Decision-Making Method for Interval-Valued Intuitionistic Fuzzy Numbers

Cited by 8 publications

References 54 publications

A Supplier Selection Decision-Making Approach for Complex Product Development Based on Hesitant Fuzzy Information

A Supplier Selection Decision-Making Approach for Complex Product Development Based on Hesitant Fuzzy Information

The TODIM multi-criteria method applied to the ANBIMA ranking of Brazilian investment funds

A Fuzzy Multiple Criteria Decision Making Approach with a Complete User Friendly Computer Implementation

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