A New Multi Attribute Decision Making Method Based on the T-Spherical Hesitant Fuzzy Sets

Al-Quran, Ashraf

doi:10.1109/access.2021.3128953

Cited by 24 publications

(11 citation statements)

References 30 publications

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“…In addition, this article only discusses the proposed model in the case of attribute values as SFNs. But in the actual decision, many complex information forms may appear in the evaluation process due to the uncertainty of DMs and the diversity of attributes, such as spherical linguistic FSs (Ashraf et al 2018 ), spherical soft FSs (Perveen et al 2019 ), T-spherical hesitant FSs (Al-Quran 2021 ) and interval-valued T-SFSs (Garg et al 2022 ). Therefore, in future studies, we will also focus on the further extension of the CPT–CoCoSo method in the aforementioned environment to develop more MAGDM models for dealing with various uncertain problems (Zhang et al 2021 ; Liu et al 2021 ; Wu et al 2014 ; Lu et al 2019 ; Wang et al 2019b ).…”

Section: Discussionmentioning

confidence: 99%

Location selection of electric vehicles charging stations by using the spherical fuzzy CPT–CoCoSo and D-CRITIC method

Zhang

Wei

2023

Comp. Appl. Math.

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Location selection of electric vehicle charging stations (LSEVCS) is a complex multi-attribute group decision-making (MAGDM) problem involving multiple experts and multiple conflicting attributes. Spherical fuzzy sets (SFSs) can deeply excavate fuzziness and uncertainty in MAGDM. In this paper, we first propose some new spherical fuzzy distance measures based on Dice and Jaccard indexes to detect the differences between SFSs or inputs. Secondly, considering risk preferences of decision makers, we integrate cumulative prospect theory (CPT) and combined compromise solutions (CoCoSo) method to develop a spherical fuzzy CoCoSo based on CPT (SF-CPT–CoCoSo) model for settling MAGDM issues. At the same time, we extend the improved CRiteria Importance Through Intercriteria Correlation (CRITIC) method, called the distance correlation-based CRITIC (D-CRITIC) method, to reasonably obtain unknown attribute weights under SFSs. Finally, this paper applies the developed model for LSEVCS to verify its practicability. Moreover, sensitivity analysis and comparative discussion with existing methods further demonstrate the robustness and effectiveness of the SF-CPT–CoCoSo model.

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Section: Discussionmentioning

confidence: 99%

Location selection of electric vehicles charging stations by using the spherical fuzzy CPT–CoCoSo and D-CRITIC method

Zhang

Wei

2023

Comp. Appl. Math.

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“…The comparison and the variation of the ranking results are tabulated and represented graphically. We aim to extend the MSM to frameworks defined in Akram and Khan (2021), Naz (2019), andAl-Quran (2021).…”

Section: Discussionmentioning

confidence: 99%

Maclaurin Symmetric Mean Aggregation Operators Based on Spherical Fuzzy Information and Application to Decision-Making

Zedam,

Ullah,

Sajjad

et al. 2023

JCCE

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In contemporary information fusion theory, the Maclaurin symmetric mean (MSM) operator is a traditional mean type aggregation operator (AO) that is an appropriate-able technique for aggregating numerical quantities. The MSM operator’s ability to record the relationships between the several input arguments is one of its standout features. The spherical fuzzy set (SFS) is also a remarkable technique that covers the maximum information from real-life scenarios with the help of four grades. This manuscript consists of the development of the MSM and weighted MSM for the information obtained by SFS. Consequently, the spherical fuzzy MSM (SFMSM) and spherical fuzzy weighted MSM (SFWMSM) operators are developed, and their basic properties are studied. Finally, the developed SFMSM and SFWMSM operators have been applied to the real-life problem of the multi-attribute decision-making problem. All the results are compared and then clearly tabulated and graphed.

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“…Al-Sharqi et al [51] proposed the notion of FP-interval complex neutrosophic soft sets and their applications under uncertainty. Many researchers extended fuzzy sets and soft sets to wards MCDM such as T-spherical hesitant fuzzy sets [52], bipolar fuzzy soft sets [53], almost convergence [54], soft union ideals and near-rings [55,56], LDFS sine-trigonometric aggregation operators [57], LBWA and Z-MABAC methods [58].…”

Section: Kernel Fuzzy Clusteringmentioning

confidence: 99%

Optimization Algorithms of PERT/CPM Network Diagrams in Linear Diophantine Fuzzy Environment

Parimala,

Prakash,

Al-Quran

et al. 2024

CMES

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The idea of linear Diophantine fuzzy set (LDFS) theory with its control parameters is a strong model for machine learning and optimization under uncertainty. The activity times in the critical path method (CPM) representation procedures approach are initially static, but in the Project Evaluation and Review Technique (PERT) approach, they are probabilistic. This study proposes a novel way of project review and assessment methodology for a project network in a linear Diophantine fuzzy (LDF) environment. The LDF expected task time, LDF variance, LDF critical path, and LDF total expected time for determining the project network are all computed using LDF numbers as the time of each activity in the project network. The primary premise of the LDF-PERT approach is to address ambiguities in project network activity times more simply than other approaches such as conventional PERT, Fuzzy PERT, and so on. The LDF-PERT is an efficient approach to analyzing symmetries in fuzzy control systems to seek an optimal decision. We also present a new approach for locating LDF-CPM in a project network with uncertain and erroneous activity timings. When the available resources and activity times are imprecise and unpredictable, this strategy can help decision-makers make better judgments in a project. A comparison analysis of the proposed technique with the existing techniques has also been discussed. The suggested techniques are demonstrated with two suitable numerical examples.

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A New Multi Attribute Decision Making Method Based on the T-Spherical Hesitant Fuzzy Sets

Cited by 24 publications

References 30 publications

Location selection of electric vehicles charging stations by using the spherical fuzzy CPT–CoCoSo and D-CRITIC method

Location selection of electric vehicles charging stations by using the spherical fuzzy CPT–CoCoSo and D-CRITIC method

Maclaurin Symmetric Mean Aggregation Operators Based on Spherical Fuzzy Information and Application to Decision-Making

Optimization Algorithms of PERT/CPM Network Diagrams in Linear Diophantine Fuzzy Environment

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