Multi-criteria PROMETHEE method based on possibility degree with Z-numbers under uncertain linguistic environment

Qiao, Dong; Shen, Kai-wen; Wang, Jianqiang; Wang, Tieli

doi:10.1007/s12652-019-01251-z

Cited by 62 publications

(29 citation statements)

References 47 publications

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“…Compared with the classical fuzzy set, the Z-number takes into account the uncertainty in information generation process and the reliability of information. At present, it has been combined with many MCDM methods such as TOPSIS [36,37], VIKOR [38], Multi-Objective Optimization by Ratio Analysis (MOORA) [39], COmbinative Distance-based Assessment (CODAS) [40], PROMETHEE [41], TODIM (an acronym in Portuguese of interactive and multicriteria decision-making) [37], AHP [42], BWM [43] and Data Envelopment Analysis (DEA) [44]. 1] are two TFNs, we can convert the Z-number to an ordinary fuzzy number [45].…”

Section: Z-numbermentioning

confidence: 99%

Sustainable Cloud Service Provider Development by a Z-Number-Based DNMA Method with Gini-Coefficient-Based Weight Determination

et al. 2020

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The sustainable development of cloud service providers (CSPs) is a significant multiple criteria decision making (MCDM) problem, involving the intrinsic relations among multiple alternatives, (quantitative and qualitative) decision criteria and decision-experts for the selection of trustworthy CSPs. Most existing MCDM methods for CSP selection incorporated only one normalization technique in benefit and cost criteria, which would mislead the decision results and limit the applications of these methods. In addition, these methods did not consider the reliability of information given by decision-makers. Given these research gaps, this study introduces a Z-number-based double normalization-based multiple aggregation (DNMA) method to tackle quantitative and qualitative criteria in forms of benefit, cost, and target types for sustainable CSP development. We extend the original DNMA method to the Z-number environment to handle the uncertain and unreliability information of decision-makers. To make trade-offs between normalized criteria values, we develop a Gini-coefficient based weighting method to replace the mean-square-based weighting method used in the original DNMA method to enhance the applicability and isotonicity of the DNMA method. A case study is conducted to demonstrate the effectiveness of the proposed method. Furthermore, comparative analysis and sensitivity analysis are implemented to test the stability and applicability of the proposed method.Sustainability 2020, 12, 3410 2 of 17 future generations to meet their own needs" [2]. Sustainability requires sustainable business practices. For doing so, information systems play an important role in the organization transition towards sustainability initiatives. The sustainable information systems have been considered as an opportunity for organizations to improve productivity, reduce costs, and increase profitability [3]. The flexible, elastic and agile nature of cloud computing provides an opportunity for governmental, academic and business organizations to consider migrating their existing applications to cloud environments to make their business processes agile with minimal cost and management effort [4]. Due to the increase in the number of cloud service providers (CSPs) offering functionally similar cloud services with varying cost, features and quality, it becomes extremely complex and burdensome to select a dependable, scalable, sustainable and high cost-effective cloud service for consumers to fulfil and satisfy their requirements and business strategies. There is a pressing need of comprehensive techniques to help them for the sustainable CSP development [5,6].Sustainable CSP development can be formulated as a multicriteria decision-making (MCDM) problem [5]. It involves the intrinsic relations among multiple alternatives, (quantitative and qualitative) decision criteria and experts for selecting the trustworthy CSPs. Moreover, the CSP evaluation data often involves uncertain, unreliability, multi-scale and imprecise weights of quality of service (QoS)...

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Section: Z-numbermentioning

confidence: 99%

Sustainable Cloud Service Provider Development by a Z-Number-Based DNMA Method with Gini-Coefficient-Based Weight Determination

et al. 2020

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“…(1) Considering the fuzzy information and reliability of this information at the same time, Z-numbers are suitable tools to describe the evaluation values [12,13]. Nonetheless, the operations of Z-numbers are complex [14,15].…”

Section: Literature Reviewmentioning

confidence: 99%

New Framework for Quality Function Deployment Using Linguistic Z-Numbers

Song

Wang

2020

Mathematics

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Quality function deployment (QFD) is a useful design quality control tool in service enterprises and manufacturing enterprises. However, there are several issues in extant QFD frameworks, that is, in three aspects: description of evaluation information, weight determination of expert team members (TMs), and weight identification of customer requirements (CRs). In order to address these issues, a novel QFD framework is first proposed utilizing linguistic Z-numbers (LZNs) with integrated subjective and objective weights of TMs and CRs. The LZNs can represent uncertain information and the reliability of information in a specific way while the fuzzy numbers cannot. Moreover, the order relation analysis (G1) method and improved maximum consensus (MC) method are developed to get the subjective and objective weights of TMs, respectively. Further, the step-wise weight assessment ratio analysis (SWARA) method and statistical distance (SD) method are studied to acquire combined weights of CRs. Next, the proposed QFD framework is applied to a case of logistics service provider, which illustrates the availability and utility of the framework. Then, a sensitivity analysis is conducted to prove the reliability of the framework. Finally, two comparative analyses are performed to declare the advantages of the framework. Results indicate the proposed QFD framework is better than existing models.

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“…From the above analysis, we have proved the availability of our proposed method based on LZWMSM operator. Next, for better illustrating the superiority of our proposed method, we will deal with the example in 5.1 by using a method proposed by Qiao et al [44]. The finally comparison result is shown in Table 4.…”

Section: Further Comparison Analysismentioning

confidence: 99%

“…The finally comparison result is shown in Table 4. [44] and our method is the same. However, the ranking results of the two methods are slightly different.…”

Section: Further Comparison Analysismentioning

confidence: 99%

Maclaurin symmetric Means for Linguistic Z-numbers and Their Application to Multiple-Attribute Decision Making

Лю

Liu

2020

Scientia Iranica

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Linguistic Z-numbers (LZNs), as a more rational extension of linguistic description, not only consider the fuzzy restriction of assessment information but also take the reliability of the information into account. Maclaurin symmetric mean (MSM) operator has the advantage which can take account of interrelationship of different attributes and there are a lot of research results on it. However, it has not been used to handle multi-attribute decision-making (MADM) problems expressed by LZNs. To sum up the advantages of LZNs and MSM, in this paper, we present the linguistic Z-Numbers MSM (LZMSM) and linguistic Z-Numbers weight MSM (LZWMSM) operators, respectively, and several characters and several special cases of them are explored. Moreover, we propose an approach to handle some MADM problems by using LZWMSM operator. In the end, an example is given to illustrate the effectiveness and superiority of this new presented approach by comparing with several existing approaches.

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Multi-criteria PROMETHEE method based on possibility degree with Z-numbers under uncertain linguistic environment

Cited by 62 publications

References 47 publications

Sustainable Cloud Service Provider Development by a Z-Number-Based DNMA Method with Gini-Coefficient-Based Weight Determination

Sustainable Cloud Service Provider Development by a Z-Number-Based DNMA Method with Gini-Coefficient-Based Weight Determination

New Framework for Quality Function Deployment Using Linguistic Z-Numbers

Maclaurin symmetric Means for Linguistic Z-numbers and Their Application to Multiple-Attribute Decision Making

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