Self-adaptive query-broadcast in wireless ad-hoc networks using fuzzy best worst method

Ahmad, Naeem; Hasan, Md. Gulzarul

doi:10.1007/s11276-020-02477-y

Cited by 6 publications

(2 citation statements)

References 44 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The same authors in [65] proposed a fuzzy linear BWM framework for service selection for Cloud Service Selection as a Service. Ahmad and Hasan 66 have utilized the fuzzy BWM approach to prioritize and find weights of mobility, node density, energy, and node status for countering the destination unreachability problem. In another type of BWM, best to others and others to worst preferences are collected along with the respective confidence level as single‐valued trapezoidal neutrosophic number 67 .…”

Section: Literature Surveymentioning

confidence: 99%

Multi‐choice best‐worst multi‐criteria decision‐making method and its applications

Hasan¹,

Ashraf

Khan

2021

Int J of Intelligent Sys

Self Cite

View full text Add to dashboard Cite

The best‐worst method (BWM) is a multi‐criteria decision‐making (MCDM) approach for solving several types of real‐life decision‐making problems. The basic BWM determines the priority order by pairwise comparisons of the best and worst criteria. The strength of the preference assigned via numerical value for linguistic interpretations of relative comparisons ranges from 1 to 9, representing preferences among the criterion. However, the amount of strength is entirely dependent on the choice of the decision‐makers. Though expert's opinions may differ due to various reasons such as incomplete information, lack of knowledge, ambiguity in linguistic terms, and so forth. Therefore, it is highly likely that the expert may provide multiple viewpoints for the preferences values. Thus, this study proposes a novel extension of the BWM named the multi‐choice best‐worst method (MCBWM), dealing with the concept of multiple choices of preference relations to compare the criterion. The MCBWM overcomes the limitation of BWM, where the pairwise preferences in the comparisons are multi‐choice parameters rather than single parametric values. Multiple real‐world MCDM applications are illustrated in experimental studies to show the quality, performance, and applicability of our proposed MCBWM. A detailed comparative analysis of the proposed approach has been done with the well‐known existing decision‐making techniques and their optimal results are compared. The proposed method offers a new direction for the MCDM approaches for solving real‐life problems.

show abstract

Section: Literature Surveymentioning

confidence: 99%

Multi‐choice best‐worst multi‐criteria decision‐making method and its applications

Hasan¹,

Ashraf

Khan

2021

Int J of Intelligent Sys

Self Cite

View full text Add to dashboard Cite

show abstract

“…Many applications can be found in the literature. Recently, Naeem et al [5] prioritized strategies for handling the COVID-19 outbreak, Ahmad and Hasan [20] reported the applicability of BWM in the study of wireless networks, Ghaffar et al [21] performed an Identification and analysis of shale development in India, Singh et al [22] evalulated and ranked of Six Sigma enablers, and Xu et al [23] applied BWM in water rights allocation. Sen et al [24] developed a framework for a housing infrastructure system considering flood resilience.…”

Section: Introductionmentioning

confidence: 99%

A Group Decision-Making Approach in MCDM: An Application of the Multichoice Best–Worst Method

2023

Self Cite

View full text Add to dashboard Cite

Multicriteria decision-making (MCDM) techniques have successfully been used to address a wide range of real-world decision-making issues. The best–worst method (BWM) is one of the several deterministic MCDM approaches. A recently proposed method called the multichoice best–worst method (MCBWM) takes into account several linguistic terms for pairwise comparisons of relative preferences among the criteria. It has been shown that the MCBWM approach has advantages over BWM: it reduces the calculation and determines optimal weight values by providing the choices for the optimal solution. This paper proposes a unique method for group decision-making based on MCBWM. We extended the MCBWM to solve group decision-making problems. A novel solution approach was developed and validated for multiple problems. Two examples and one case study were solved using the proposed approach to demonstrate the validity and application of the proposed method. The results were further compared with existing models to validate the proposed approach. We found that the obtained ranking order for all problems is the same and that the proposed model has a higher consistency ratio than the existing approaches. This method can be extended to other mathematical programming models for collective decision making in uncertain situations.

show abstract

Cost-benefit analysis of shale development in India: A best-worst method based MCDM approach

Ghaffar

Nadeem

Hasan³

2021

Journal of King Saud University - Science

View full text Add to dashboard Cite

Self-adaptive query-broadcast in wireless ad-hoc networks using fuzzy best worst method

Cited by 6 publications

References 44 publications

Multi‐choice best‐worst multi‐criteria decision‐making method and its applications

Multi‐choice best‐worst multi‐criteria decision‐making method and its applications

A Group Decision-Making Approach in MCDM: An Application of the Multichoice Best–Worst Method

Cost-benefit analysis of shale development in India: A best-worst method based MCDM approach

Contact Info

Product

Resources

About