Negation of Pythagorean Fuzzy Number Based on a New Uncertainty Measure Applied in a Service Supplier Selection System

Mao, Haiyi; Cai, Rui

doi:10.3390/e22020195

Cited by 13 publications

(3 citation statements)

References 75 publications

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“…Besides, PFSs are general and have their membership function, but the PFSs should be a part of Pythagorean fuzzy numbers (PFNs). Finally, A PFS A is a fuzzy number when its universe is the set of PFNs, and it is satisfied (Ejegwa, 2019;Kiris ¸ci and S ¸ims ¸ek, 2022;Mao and Cai, 2020;Wan et al, 2020). Yager defined three basic representations for membership grades.…”

Section: Pythagorean Fuzzy Sets (Pfss)mentioning

confidence: 99%

Rating pressure factors affecting logistics systems during the pandemic and the ideal logistic decision selection under the Pythagorean fuzzy environment

Mishra¹,

Ergün

Okoth

et al. 2023

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PurposeDue to the current pandemic, the importance of logistics functions and decisions is well understood both at the level of companies and users. Logistics systems and related decisions are of vital importance in making supply chains effective, efficient and without disruption. Logistic pressure factors may emerge at different points along the logistics process, and given the role of logistics decisions as one of the important indicators of competitiveness, the determination of the logistics pressures that are likely to increase the costs of business, and their causative factors are a vital aspect of the logistics decision-making process. The study aims to provide assistance in the selection of the most ideal logistics decision by ranking the pressure factors affecting the logistics system, especially during the pandemic period for logistics enterprises operating in Ordu and Giresun provinces and which have a corporate identity.Design/methodology/approachIn this study, it is aimed to make the most ideal logistics decision selection by ranking the pressure factors affecting the logistics system, especially during the pandemic period for the logistics enterprises operating in Ordu and Giresun provinces and having a corporate identity. For that purpose interval-valued Pythagorean fuzzy (IVPF)–analytic hierarchy process (AHP) based combinative distance-based assessment (CODAS) methodology was used. Additionally sensitivity and comparison analysis were discussed.FindingsCompetitive pressure was found as the most important pressure factor affecting the logistics system during the pandemic period. Change in regulatory rules was the pressure factor found to have the least effect on the logistics system. Using the weights of logistics pressure factors, “Operational Decisions” was found to be the most ideal logistics decision selection.Research limitations/implicationsThe findings provide support for the evaluation of logistical pressures and decision options by presenting a decision model capable of processing ambiguous information. During a pandemic or similar period, the study assists decision makers in determining a new route. The findings will also call business managers' attention to logistical pressure factors and lead them toward more realistic and feasible practices in the logistics decision-making process.Originality/valueThis study provided an effective and applicable solution to a decision-making problem in the logistics sector including logistics pressure factors and the selection of logistics decisions. In this context, a methodology was presented that will allow businesses to self-evaluate their own logistics pressure factors and the selection of optimal solutions.

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Section: Pythagorean Fuzzy Sets (Pfss)mentioning

confidence: 99%

Rating pressure factors affecting logistics systems during the pandemic and the ideal logistic decision selection under the Pythagorean fuzzy environment

Mishra¹,

Ergün

Okoth

et al. 2023

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“…In [3], negation of Z-numbers is proposed. Researchers applied concept of negation in D-S evidence theory also by defining negation of BPA based on pythagorean fuzzy numbers [5], maximum uncertainty allocation [1], reallocation [15], matrix method [4] and belief interval approach [6] and applied that in service supplier selection system [5], medical pattern recognition [6], decision making [13] and many more. In the present work, we have investigated the properties of markov chain that is embedded in the negation of a probability distribution.…”

Section: Negativementioning

confidence: 99%

A note on negation of a probability distribution

Kaur

Srivastava

2022

Soft Comput

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Evaluating the negation of an uncertain event is an open issue. Yager [14] suggested a transformation for evaluating the negation of a probability distribution. He used the idea that any event whose outcome is not certain can be negated by supporting the occurence of other events with no bias or prejudice for any particular outcome. Various authors have tried to generalize the negation transformation proposed by Yager [14]. However we need to focus on developing the basic structure of negation so that the behaviour of the process modelled by negation transformation can be understood in detail.Yager's negation is based on distribution of maximum entropy. If a probability distribution is uncertain(a state other than maximum entropy), the more iterations of negation, the more uncertain this probability event becomes eventually converging to a homogeneous state i.e. maximum entropy. In other words, it is the realization of the process. What is noted that during each negation, Yager's method ensures that the negation is intuitive, the next negation weakens the probability of the event occuring in the previous step. Since negation involves reallocation of probabilities at each step in such a way that the reallocation at each step can be determined from the reallocation at the previous step, therefore it is clear that Yager's negation has various attributes similar to that of a markov chain. In the present work, we have shown that Yager's definition of negation can be modelled as a markov chain which is irreducible, aperiodic with no absorbing states. Two examples has been discussed to strengthen and support the analytical results. Also we have defined an information generating function(IGF) whose derivative evaluated at specific points gives the moments of the self information of negation of a probability distribution. The properties of the generating function along with its relationship with the information generating

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“…A new method is also proposed based on Tsallis entropy [55] which will degenerate to Yager's method in some special cases. In order to verify the new entropy with good performance in uncertainty measurement, a new Pythagoras fuzzy number inversion method is proposed and the new method can be applied in a service supplier selection system [30]. Combining the negative distribution of probability with evidence theory is also a popular application direction.…”

Section: Introductionmentioning

confidence: 99%

Exponential negation of a probability distribution

Deng

Xiong

2022

Soft Comput

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Negation operation is important in intelligent information processing. Different with existing arithmetic negation, an exponential negation is presented in this paper. The new negation can be seen as a kind of geometry negation. Some basic properties of the proposed negation are investigated, we find that the fix point is the uniform probability distribution. The proposed exponential negation is an entropy increase operation and all the probability distributions will converge to the uniform distribution after multiple negation iterations. The convergence speed of the proposed negation is also faster than the existed negation. The number of iterations of convergence is inversely proportional to the number of elements in the distribution. Some numerical examples are used to illustrate the efficiency of the proposed negation.

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Negation of Pythagorean Fuzzy Number Based on a New Uncertainty Measure Applied in a Service Supplier Selection System

Cited by 13 publications

References 75 publications

Rating pressure factors affecting logistics systems during the pandemic and the ideal logistic decision selection under the Pythagorean fuzzy environment

Rating pressure factors affecting logistics systems during the pandemic and the ideal logistic decision selection under the Pythagorean fuzzy environment

A note on negation of a probability distribution

Exponential negation of a probability distribution

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