Fuzzy rule based approach with z-numbers for selection of alternatives using TOPSIS

Yaakob, Abdul Malek; Gegov, Alexander

doi:10.1109/fuzz-ieee.2015.7337862

Cited by 26 publications

(16 citation statements)

References 16 publications

(23 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Next using Eq. (12), and according to the first decision maker as detailed in Tables 8 and 9, the antecedent matrix for the cost system is:…”

Section: Simulation Resultsmentioning

confidence: 99%

“…(1, 3, 3, 5) Fair (F) 4 (3, 5, 5, 7) Medium Good (MG) 5 (5,7,7,9) Good (G) 6 (7, 9, 9, 10) Very Good (VG) 7 (9, 10, 10, 10) The following are the procedures involved in implementing a fuzzy network with merging rule bases to TOPSIS, based on Type 1-fuzzy set. Steps 1-6 are adopted from [16] and [12], while steps 7-10 are introduced as part of the proposed method in this paper.…”

Section: A Type-1 Fuzzy Set Implementationmentioning

confidence: 99%

“…Therefore FNs consider the interaction between subsystems. This ability brings considerable benefits to modelling complex processes, and although FNs have been introduced recently, a cohort of researchers are dedicated to the theoretical development and applications of FNs [3], [4], [6]- [8].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Selection of alternatives using fuzzy networks with rule base aggregation

Yaakob

Gegov

Rahman

2018

Fuzzy Sets and Systems

Self Cite

View full text Add to dashboard Cite

This paper introduces a novel extension of the Technique for Ordering of Preference by Similarity to Ideal Solution (TOPSIS) method. The method is based on aggregation of rules with different linguistic of the output of fuzzy networks to solve multi criteria decision-making problems whereby both benefit and cost criteria are presented as subsystems. Thus the decision maker evaluates the performance of each alternative for decision process and further observes the performance for both benefit and cost criteria. The aggregation sub-stage in a fuzzy system maps the fuzzy membership functions for all rules to an aggregated fuzzy membership function representing the overall output for the rules. This approach improves significantly the transparency of the TOPSIS methods, while ensuring high effectiveness in comparison to established approaches. To ensure practicality and effectiveness, the proposed method is further tested on portfolio selection problems. The ranking produced by the method is comparatively validated using Spearman rho rank correlation. The results show that the proposed method outperforms the existing TOPSIS approaches in term of ranking performance.

show abstract

“…Next using Eq. (12), and according to the first decision maker as detailed in Tables 8 and 9, the antecedent matrix for the cost system is:…”

Section: Simulation Resultsmentioning

confidence: 99%

Section: A Type-1 Fuzzy Set Implementationmentioning

confidence: 99%

See 1 more Smart Citation

Selection of alternatives using fuzzy networks with rule base aggregation

Yaakob

Gegov

Rahman

2018

Fuzzy Sets and Systems

Self Cite

View full text Add to dashboard Cite

show abstract

“…TOPSIS method is used to represent the importance of criteria, rating of the alternative and is based on comparing the expected cost criteria of each alternative against the expected benefit criteria to see whether the benefits outweigh the costs and for how much. Recent researches on TOPSIS with multiple fuzzy rule bases (MFS-TOPSIS) [19] and Znumbers fuzzy rule based approach (Z-FRBS TOPSIS) [18] introduced the influence degree of each decisionmaker in case one decision-maker has more knowledge of the domain and can obtain greater degree of importance comparing with others. In this paper we consider some ideas of TOPSISs first steps in order to construct a decision matrix and to show the importance of criteria time-resource trade-off and alternative mode preference, as well as Z-number reliability of decision-maker.…”

Section: Mode Assignment Problemmentioning

confidence: 99%

Managing temporal uncertainty in multi-mode Z-number fuzzy graph structures

Knyazeva¹,

Bozhenyuk²,

Kaymak³

2019

Proceedings of the 2019 Conference of the International Fuzzy Systems Association and the European Society for Fuzzy Logic and

View full text Add to dashboard Cite

In this paper we introduce an NP-hard optimization problem and examine preferences of decision-maker towards imprecise alternatives (modes) in a fuzzy temporal graph structure model. Fuzzy Z-number preference matrix is introduced and types of generalized precedence relations in fuzzy multimode resource-constrained project scheduling problem (F-MRCPSP) based on expert estimation are discussed. Implementation of Z-numbers allows handling uncertain data and modelling preferences of expert towards uncertain variables. Multi-mode way for activity performance allows considering temporal uncertainty, expert estimations, flexibility in switching from mode to mode and resource levelling profile problem. Geometrical interpretation for fuzzy multi-mode problem (F-MRCPSP) based on box packing is given.

show abstract

“…Azadeh et al[54] use Z-number with the AHP method. Yaakob and Gegov[55] Z-number uses the TOPSIS method. Salari et al[56] elaborate a novel earned value management model using Z-number.…”

mentioning

confidence: 99%

Ranking and Assessment of the Efficiency of Social Media using the Fuzzy AHP-Z Number Model - Fuzzy MABAC

Bobar¹,

Božanić²,

Djurić³

et al. 2020

ACTA POLYTECH HUNG

View full text Add to dashboard Cite

Methods of ranking and evaluation of the effectiveness of Social Media (SM) given and applied in this paper are the basis for the selection of online media that the public administration uses when communicating with citizens. The methodology presented is based on multicircular decision-making using the Fuzzy Analytical Hierarchical Process (fuzzy AHP) -Z number model -Fuzzy Multi-Attributive Border Approximation Area Comparison (fuzzy MABAC), which eliminates the traditional intuitive ratings of PR services. This resulted in poor use of available channels of communication or ineffective communication. Positive results of the application of presented methods are especially evident in increasing the number of channels of communication on the Internet and the realization of communication goals for greater participation of citizens in public administration. Z. Bobar et al. Ranking and Assessment of the Efficiency of Social Media using the Fuzzy AHP-z Number Model -Fuzzy MABAC -44 -where social media is seen to transform the relationship of public service and the citizenry [2]. In the process of communication with public, government institutions and businesses are not able to use the virtually unlimited number of media available on the Internet with equal efficiency. The selection of social media to be used as a communication channel ensuring reach amongst the targeted public online with desired efficiency is one of the challenges faced by these services in implementing a given communication strategy.In line with the new trends in the usage of social media for business purposes, a series of studies have examined the justification of using social media in the communication of public administration with the citizenry. Some focused on functional availability [3], benefits and risks [4], and the impact of social media use [5]. The common trait found in all these studies is the analysis and assessment of multiple social media according to a single criterion, or the analysis and evaluation of a single social media based on multiple criteria. However, communicators are often confronted with the need to choose among available social media. They have to identify the criteria and the methodology for making such a choice to reduce the risk of failure in communicating via social media.Considering the trends in social media usage and the perspective of involving such media in the activities of public administration as well as that of other organizations, the aim of this research is:1. To define the general criteria for choosing social media for communication between government bodies and the target public; and 2. To develop the methodology for social media ranking in view of the selection of a particular communication channel suited to a communication strategy.This paper examines the various options for rating and ranking social media by using parameters that influence the efficiency of communication, defined on the grounds of criteria partially used in the evaluation and ranking of social media, as well as on expert assessments...

show abstract

Fuzzy rule based approach with z-numbers for selection of alternatives using TOPSIS

Cited by 26 publications

References 16 publications

Selection of alternatives using fuzzy networks with rule base aggregation

Selection of alternatives using fuzzy networks with rule base aggregation

Managing temporal uncertainty in multi-mode Z-number fuzzy graph structures

Ranking and Assessment of the Efficiency of Social Media using the Fuzzy AHP-Z Number Model - Fuzzy MABAC

Contact Info

Product

Resources

About