Multi-attribute Decision Making Based on Z-valuation

Aliyev, Rafig R.

doi:10.1016/j.procs.2016.09.393

Cited by 19 publications

(7 citation statements)

References 19 publications

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“…Model 2 Aliyev (2016). presented a distance between Z-numbers based on the cut set theory to address the MCDM problem where the decision information is expressed using Z-numbers.…”

Section: Comparative Analysismentioning

confidence: 99%

“…Kang et al (2018c) proposed a multiple integral formula to compute the total utility of Z-number. Aliyev (2016) considered Z-number as a pair of classical fuzzy numbers to calculate the distance of two Z-number valued vectors. Kang et al (2012b) proposed a method of converting Z-number to a TFN with the same fuzzy expectation as the original Z-number.…”

Section: Introductionmentioning

confidence: 99%

“…1. Extant studies considered Z-number as an ordered pair of classical fuzzy numbers when comparing two Z-numbers (Aliyev 2016;Kang et al 2019Kang et al , 2018c. Based on Zadeh (2011), this kind of operations is unreasonable and unconvincing.…”

Section: Introductionmentioning

confidence: 99%

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Likelihood-based qualitative flexible approach to ranking of Z-numbers in decision problems

Qiao

Wang

et al. 2020

Comp. Appl. Math.

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Information reliability has a remarkable effect on decision-making outcome. Zadeh's Z-number considers information fuzziness and reliability, and can, therefore, help the decision-maker to manage complicated problems. However, due to its complex construct, several issues concerning the computation of Z-numbers require further research. This study develops a novel likelihood-based method of comparing two Z-numbers to solve multi-criteria decision-making (MCDM) problems. Four main parts can be outlined. First, the likelihood of fuzzy restriction of Z-numbers is defined based on the conversion method of Z-number. Second, the likelihood of underlying probability distributions of Z-numbers is also proposed to compare the difference of randomness of Z-information. Third, by adding to a risk preference parameter, this study constructs a comprehensive weighted likelihood of Z-numbers. Finally, a likelihood-based qualitative flexible approach is extended to address the MCDM problems under Z-evaluation. In addition, a numerical example of the selection of ERP systems for ABC enterprise is placed to illustrate the applicability, validity, and effectiveness of the proposed method.

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“…Model 2 Aliyev (2016). presented a distance between Z-numbers based on the cut set theory to address the MCDM problem where the decision information is expressed using Z-numbers.…”

Section: Comparative Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Likelihood-based qualitative flexible approach to ranking of Z-numbers in decision problems

Qiao

Wang

et al. 2020

Comp. Appl. Math.

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“…The use of one or another multi-attribute decision theory depends mainly on decisionmaking situations. 19 MCDM refers to making decisions in the presence of multiple, usually conflicting, criteria. Here, different units of measurement, quality characteristics, and relative weight might be considered for each different criterion.…”

Section: Fuzzy Multi-criteria Analysismentioning

confidence: 99%

“…The type-n fuzzy set generalized type-2 fuzzy set, thereby permitting the membership to be a type-n À 1 fuzzy set. 19 The Fuzzy multi-set introduced by Yager allowed elements to be repeated more than once.…”

Section: Fuzzy Multi-criteria Analysismentioning

confidence: 99%

Optimal maintenance strategy selection based on a fuzzy analytical network process

Borjalilu

Ghambari

2018

International Journal of Engineering Business Management

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Maintenance is one of the most crucial issues in today's competitive manufacturing environment. Nowadays, productive methods are used in manufacturing plants to improve operations capabilities, which alternatively change business environmental factors leading to a competitive market. Consequently, selection and illustration of an optimal maintenance strategy play a significant role in achieving these goals. Also, lack of an integrated model is felt, one that consists of available criteria and options, a systematic approach in setting maintenance instructions and robust maintenance decision-making. So, based on the fuzzy analytical network process (FANP) method, which composes criteria and options, a new approach to selecting optimal maintenance strategy is proposed in this article. Here, using multi-attribute decision-making in conjunction with application of fuzzy numbers structure has been regarded as an efficacious method for determining the significance of each criterion and option. The criteria that are considered in the FANP method are organization, safety, administration, staff, and technical requirements. The options (strategies) that are taken into consideration in this study are time-based preventive maintenance, corrective maintenance, condition-based maintenance, reliability-centered maintenance, and predictive maintenance. After implementing the method proposed for a 5-MW powerhouse (a case study undertaken for the purpose of this study), the predictive maintenance strategy was selected. According to expert opinions, it is the administrative and staff requirements that must be highlighted for selecting the best strategies.

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Z+ - Number Based Alternatives Selection in Investment Problem

Ahmadov

2022

11th International Conference on Theory and Application of Soft Computing, Computing With Words and Perceptions and Artificial

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Multi-attribute Decision Making Based on Z-valuation

Cited by 19 publications

References 19 publications

Likelihood-based qualitative flexible approach to ranking of Z-numbers in decision problems

Likelihood-based qualitative flexible approach to ranking of Z-numbers in decision problems

Optimal maintenance strategy selection based on a fuzzy analytical network process

Z+ - Number Based Alternatives Selection in Investment Problem

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