Strategic weight manipulation in multiple attribute decision making

Dong, Yucheng; Liu, Yating; Liang, Haiming; Chiclana, Francisco; Herrera‐Viedma, Enrique

doi:10.1016/j.omega.2017.02.008

Cited by 197 publications

(93 citation statements)

References 42 publications

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“…Especially, Dong et al, 46 proposed a resolution framework for the complex and dynamic MAGDM problem, in which decision makers are supposed to have different interests and use heterogeneous individual sets of attributes to evaluate the individual alternatives. Dong et al, 47 meaningfully considered the complex and dishonest context, where a decision maker can strategically set the preferences to obtain her/his desired ranking of alternatives. This paper from a different perspective takes into account heterogeneous individual preferences and converts them into the proportions of the associated membership degrees in each PHEs.…”

Section: Definition 12mentioning

confidence: 99%

A Novel MAGDM Approach With Proportional Hesitant Fuzzy Sets

Xiong¹,

Chen²,

Chin³

2018

IJCIS

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In this paper, we propose an extension of hesitant fuzzy sets, i.e., proportional hesitant fuzzy sets (PHFSs), with the purpose of accommodating proportional hesitant fuzzy environments. The components of PHFSs, which are referred to as proportional hesitant fuzzy elements (PHFEs), contain two aspects of information provided by a decision-making team: the possible membership degrees in the hesitant fuzzy elements and their associated proportions. Based on the PHFSs, we provide a novel approach to addressing fuzzy multi-attribute group decision making (MAGDM) problems. Different from the traditional approach, this paper first converts fuzzy MAGDM (expressed by classical fuzzy numbers) into proportional hesitant fuzzy multi-attribute decision making (represented by PHFEs), and then solves the latter through the proposal of a proportional hesitant fuzzy TOPSIS approach. In this process, preferences of the decision-making team are calculated as the proportions of the associated membership degrees. Finally, a numerical example and a comparison are provided to illustrate the reliability and effectiveness of the proposed approach.

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Section: Definition 12mentioning

confidence: 99%

A Novel MAGDM Approach With Proportional Hesitant Fuzzy Sets

Xiong¹,

Chen²,

Chin³

2018

IJCIS

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“…In this section, we apply our proposal in MAGDM problems [6,8,38,40]. Procedures for MAGDM with HLDs are presented and an illustrative example is demonstrated.…”

Section: Use Of the Proposed Hlds In Magdmmentioning

confidence: 99%

Generalizing linguistic distributions in hesitant decision context

Zhang¹,

Wu²,

Dong³

2017

IJCIS

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The hesitant fuzzy linguistic term set (HFLTS) and the linguistic distribution (LD) are becoming popular tools to describe decision makers' linguistic preferences. By combining HFLTS and LD, this paper proposes a new concept called hesitant linguistic distribution (HLD), and then presents the transformation between HLDs and LDs and the basic comparison and aggregation operations to perform on HLDs. Following, comparisons among several linguistic expressions are made. Finally, the use and behavior mechanism of HLD in multiple attribute group decision making is demonstrated.

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“…As we all know, real GDM situations involve not only the fields of mathematics but also human psychological behavior . Self‐confidence, as one of the human psychological behaviors, has an important impact on decision making .…”

Section: Introductionmentioning

confidence: 99%

Analysis of self-confidence indices-based additive consistency for fuzzy preference relations with self-confidence and its application in group decision making

Liu

Montes

et al. 2018

Int J Intell Syst

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Preference relations have been widely used in group decision‐making (GDM) problems. Recently, a new kind of preference relations called fuzzy preference relations with self‐confidence (FPRs‐SC) has been introduced, which allow experts to express multiple self‐confidence levels when providing their preferences. This paper focuses on the analysis of additive consistency for FPRs‐SC and its application in GDM problems. To do that, some operational laws for FPRs‐SC are proposed. Subsequently, an additive consistency index that considers both the fuzzy preference values and self‐confidence is presented to measure the consistency level of an FPR‐SC. Moreover, an iterative algorithm that adjusts both the fuzzy preference values and self‐confidence levels is proposed to repair the inconsistency of FPRs‐SC. When an acceptable additive consistency level for FPRs‐SC is achieved, the collective FPR‐SC can be computed. We aggregate the individual FPRs‐SC using a self‐confidence indices‐based induced ordered weighted averaging operator. The inherent rule for aggregation is to give more importance to the most self‐confident experts. In addition, a self‐confidence score function for FPRs‐SC is designed to obtain the best alternative in GDM with FPRs‐SC. Finally, the feasibility and validity of the research are demonstrated with an illustrative example and some comparative analyses.

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Strategic weight manipulation in multiple attribute decision making

Cited by 197 publications

References 42 publications

A Novel MAGDM Approach With Proportional Hesitant Fuzzy Sets

A Novel MAGDM Approach With Proportional Hesitant Fuzzy Sets

Generalizing linguistic distributions in hesitant decision context

Analysis of self-confidence indices-based additive consistency for fuzzy preference relations with self-confidence and its application in group decision making

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