A new linguistic aggregation operator and its application to multiple attribute decision making

Lan, Jibin; Chen, Yu‐Wen; Ning, Mengyao; Wang, Zhongxing

doi:10.1016/j.orp.2015.09.001

Cited by 18 publications

(2 citation statements)

References 44 publications

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“…28 , 29 The use of linguistic terms are another way to model human cognition. In general, experts deal with many problems using linguistic terms to express qualitative information such as “bad,” “tolerable”, “average,” and “good.” 30 In some complex decision-making environments, experts express their opinions by combining linguistic terms with IFS, so that imprecise information from subjective and objective environments can be better represented. As a result, the intuitionistic linguistic number (ILN) was developed, which is a combination of intuitionistic fuzzy numbers and linguistic terms, 31 which can comprehensively describe the fuzzy features of things.…”

Section: Introductionmentioning

confidence: 99%

Improving Hospital Based Medical Procurement Decisions with Health Technology Assessment and Multi-Criteria Decision Analysis

Chai

Wang

et al. 2021

INQUIRY

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This research proposes a new medical procurement decision-making tool named Evaluation of Medical Technology Procurement (EMTP), which combines Mini-health Technology Assessment (Mini HTA) with the analytic hierarchy process (AHP), as well as the intuitionistic linguistic multi-criteria group decision model for multi-criteria decision analysis (MCDA). This tool was applied to a medical device procurement decision in a large provincial general hospital with more than 5000 beds in China as a case study. Specifically, the AHP evaluation framework is first established to determine the evaluation dimensions and criteria. This goal is achieved by applying the AdHopHTA Mini-HTA template and gathering data from questionnaires completed by experts from 33 major public hospitals in Anhui Province, China. The professionals within the application hospital were invited to evaluate the alternative products in a pairwise comparison and obtain a ranking of their advantages and disadvantages. This goal is achieved using the intuitionistic linguistic fuzzy model to deal with the subjectivity and uncertainty that may be present in the professional evaluation by experts in different fields. At the same time, the Keeney-Raiffa MCDA (KRM) method was used to demonstrate the accuracy of the application results. The results show that our tool can achieve the same effect as the verification method while being more efficient, easier to use, and requiring fewer participants. The advantages and disadvantages of several evaluation methods combined with multi-criteria methods are discussed, including verification methods, pointing out the advantages and limitations of this research tool as well as the prospects for the future.

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Section: Introductionmentioning

confidence: 99%

Improving Hospital Based Medical Procurement Decisions with Health Technology Assessment and Multi-Criteria Decision Analysis

Chai

Wang

et al. 2021

INQUIRY

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“…In existing studies, many different methods have been developed for multiple attribute decision analysis (MADA). Representative methods include multiple attribute utility function (MAUF) methods (Balla et al 2014;Keeney and Raiffa 1993;Butler et al 1997;Butler et al 2001;Wakker et al 2004), multiple attribute value function methods (Belton and Stewart 2002;Chin et al 2015;Fischer 1995;Kadziński et al 2014;Keeney 2002;Lan et al 2015;Zhang et al 2017), outranking methods such as PROMETHEE methods (Chen 2014a;Miłosz and Krzysztof 2016) and ELECTRE methods (Chen 2014b;Corrente et al 2016), and distance based methods such as the extensions of TOPSIS method (Baykasoğlu and Gölcük 2015;Wang et al 2016) and VIKOR method (Qin et al 2015;Madjid et al 2016). One similarity among those different methods is that attribute weights are taken into account although the meanings of the weights may be different.…”

Section: Introductionmentioning

confidence: 99%

Determining attribute weights for multiple attribute decision analysis with discriminating power in belief distributions

Xue

2018

Knowledge-Based Systems

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Attribute weight assignment plays an important role in multiple attribute decision analysis (MADA). When the performances of alternatives on each attribute are expressed by distributions instead of single values, how to use the differences in the performances to obtain attribute weights is an interesting but difficult issue. To address this issue, in this paper, we propose a method for obtaining attribute weights from discriminating power in belief distributions. With the consideration of the differences among the utilities of all assessment grades used to profile belief distributions, the dissimilarity based discriminating power, the standard deviation based discriminating power, and the Gini's mean difference based discriminating power of the performances of all alternatives on each attribute are constructed to determine three sets of respective weights of attributes. They are convexly combined using three coefficients to generate integrated weights of attributes. To relieve the burden on a decision maker to provide precise values for the three coefficients, they are allowed to change between 0 and 1, as long as their sum is equal to 1. Under such constraints on the three coefficients, an optimization model is constructed to determine the minimum and maximum expected utilities of each alternative. From the expected utilities, all alternatives are then compared using Hurwicz rule with the provided optimism degree interval to generate solutions to MADA problems. The transitivity of the comparison outcomes among three alternatives under a given optimism degree interval is theoretically analyzed to guarantee the rationality of the outcomes. A focal form selection problem is investigated to demonstrate the applicability and validity of the proposed method.

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Intuitionistic linguistic group decision-making methods based on generalized compensative weighted averaging aggregation operators

Wang

Sangaiah

et al. 2017

Soft Comput

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A new linguistic aggregation operator and its application to multiple attribute decision making

Cited by 18 publications

References 44 publications

Improving Hospital Based Medical Procurement Decisions with Health Technology Assessment and Multi-Criteria Decision Analysis

Improving Hospital Based Medical Procurement Decisions with Health Technology Assessment and Multi-Criteria Decision Analysis

Determining attribute weights for multiple attribute decision analysis with discriminating power in belief distributions

Intuitionistic linguistic group decision-making methods based on generalized compensative weighted averaging aggregation operators

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