scholarly journals A Novel MCDM Method Based on Plithogenic Hypersoft Sets under Fuzzy Neutrosophic Environment

Symmetry ◽  
2020 ◽  
Vol 12 (11) ◽  
pp. 1855
Author(s):  
Muhammad Rayees Ahmad ◽  
Muhammad Saeed ◽  
Usman Afzal ◽  
Miin-Shen Yang
Keyword(s):  
Selection Criteria ◽  
Fuzzy Topsis ◽  
Multi Criteria Decision Making ◽  
Choice Problem ◽  
Matlab Code ◽  
Parking Spot ◽  
Order Preference ◽  
Mcdm Method ◽  
Analyze Time Series ◽  
Attribute Value

In this paper, we advance the study of plithogenic hypersoft set (PHSS). We present four classifications of PHSS that are based on the number of attributes chosen for application and the nature of alternatives or that of attribute value degree of appurtenance. These four PHSS classifications cover most of the fuzzy and neutrosophic cases that can have neutrosophic applications in symmetry. We also make explanations with an illustrative example for demonstrating these four classifications. We then propose a novel multi-criteria decision making (MCDM) method that is based on PHSS, as an extension of the technique for order preference by similarity to an ideal solution (TOPSIS). A number of real MCDM problems are complicated with uncertainty that require each selection criteria or attribute to be further subdivided into attribute values and all alternatives to be evaluated separately against each attribute value. The proposed PHSS-based TOPSIS can be used in order to solve these real MCDM problems that are precisely modeled by the concept of PHSS, in which each attribute value has a neutrosophic degree of appurtenance corresponding to each alternative under consideration, in the light of some given criteria. For a real application, a parking spot choice problem is solved by the proposed PHSS-based TOPSIS under fuzzy neutrosophic environment and it is validated by considering two different sets of alternatives along with a comparison with fuzzy TOPSIS in each case. The results are highly encouraging and a MATLAB code of the algorithm of PHSS-based TOPSIS is also complied in order to extend the scope of the work to analyze time series and in developing algorithms for graph theory, machine learning, pattern recognition, and artificial intelligence.

B-School Selection by Fuzzy TOPSIS and AHP

2018 ◽  
pp. 929-955 ◽  
Author(s):  
Vivek Agrawal ◽  
Vikas Tripathi ◽  
Nitin Seth
Keyword(s):  
Fuzzy Topsis ◽  
Multi Criteria Decision Making ◽  
School Evaluation ◽  
Rapid Rise ◽  
Order Preference ◽  
Professional Degree ◽  
The Subject ◽  
Linguistic Assessment ◽  
School Selection ◽  
Selection Of

Rapid liberalization of education sector in India has resulted in increased competition. As a result, we have witnessed rapid rise in number of management institutes. The student's evaluation about an institute/college is based on multiple criteria. Realizing the need a focused review on the literature was made to understand the subject. The review highlighted that conventional methods for B-school evaluation are inadequate for dealing with the imprecise, uncertain or vague nature of linguistic assessment. To overcome this difficulty, due to MCDM problem, Fuzzy multi-criteria decision-making methods are proposed. The aim of this study is to use fuzzy technique for order preference by similarity to ideal solution (TOPSIS) and Analytical Hierarchal process (AHP) methods for the selection of better B-school. The proposed methods have been applied to a B-School selection problem of the students of NCR and results are presented. This chapter contributes to previous researches by adding a new avenue, where the MCDM technique can be useful. The selection of an institution for getting a professional degree is a very tough task for the students and as well as for their guardians. This method can help them to find a better solution by providing a quantitative framework.

scholarly journals A Fuzzy TOPSIS with Z-Number and Alpha-Cut in Identifying the Key Factor of Smoking Behaviours in Jordan

2019 ◽  
Vol 8 (2S3) ◽  
pp. 307-313
Keyword(s):  
Decision Making ◽  
Fuzzy Topsis ◽  
Smoking Behaviour ◽  
Decision Makers ◽  
Additional Restriction ◽  
Multi Criteria Decision Making ◽  
Key Factor ◽  
Order Preference ◽  
Health Organization ◽  
Smoking Behaviours

The most famous method when dealing with decision making is Multi-Criteria Decision Making (MCDM). One of the easiest technique from MCDM is Fuzzy Technique for Order Preference by Similarity to Ideal Solution (FTOPSIS). However, there are some circumstances in FTOPSIS still needs to be enhanced. Therefore, this paper concentrates on: 1) to develop FTOPSIS with Z-number and α -cut based MCDM problem; the combination of Z-Number and α-cut is seen suitable to solve uncertainty issue due to the additional restriction and reliability parts; 2) to validate the propose method for solving smoking problems in Jordan; three decision makers which are parent, student and health organization are requested to answer all the questionnaires based on smoking behaviour problems. The study presents six steps of FTOPSIS with Z-numbers and αcut to verify the position of the smoking behaviour; 3) to evaluate the efficiency of the proposed method using 10 different number of α-cut. Ten different numbers are 0.1 till 0.9. Results illustrate that many Jordanian smoke because they want to lose their weight. From the study, this proposed method opens a new revolution in MCDM area to provide different ways when dealing with decision making problems. Thus, give us variety of techniques in decision making area.

New type of cancer patients based on triangular cubic hesitant fuzzy TOPSIS method

2019 ◽  
Vol 13 (01) ◽  
pp. 2050002
Author(s):  
Aliya Fahmi ◽  
Muhammad Aslam ◽  
Fuad Ali Ahmed Almahdi ◽  
Fazli Amin
Keyword(s):  
Decision Making ◽  
Fuzzy Number ◽  
Hamming Distance ◽  
Fuzzy Topsis ◽  
Multi Criteria Decision Making ◽  
Ideal Solution ◽  
Topsis Method ◽  
Operational Laws ◽  
New Type ◽  
Mcdm Method

In this paper, we define the new idea of triangular cubic hesitant fuzzy number (TCHFN). We discuss some basic operational laws of triangular cubic hesitant fuzzy number and hamming distance of TCHFNs. We introduce the new concept of triangular cubic hesitant TOPSIS method. Furthermore, we extend the classical cubic hesitant the technique for order of preference by similarity to ideal solution (TOPSIS) method to solve the Multi-Criteria decision-making (MCDM) method based on triangular cubic hesitant TOPSIS method. The new ranking method for TCHFNs is used to rank the alternatives. Finally, an illustrative example is given to verify and demonstrate the practicality and effectiveness of the proposed method.

B-School Selection by Fuzzy TOPSIS and AHP

2016 ◽  
pp. 1-27 ◽  
Author(s):  
Vivek Agrawal ◽  
Vikas Tripathi ◽  
Nitin Seth
Keyword(s):  
Fuzzy Topsis ◽  
Multi Criteria Decision Making ◽  
School Evaluation ◽  
Rapid Rise ◽  
Order Preference ◽  
Professional Degree ◽  
The Subject ◽  
Linguistic Assessment ◽  
School Selection ◽  
Selection Of

Rapid liberalization of education sector in India has resulted in increased competition. As a result, we have witnessed rapid rise in number of management institutes. The student's evaluation about an institute/college is based on multiple criteria. Realizing the need a focused review on the literature was made to understand the subject. The review highlighted that conventional methods for B-school evaluation are inadequate for dealing with the imprecise, uncertain or vague nature of linguistic assessment. To overcome this difficulty, due to MCDM problem, Fuzzy multi-criteria decision-making methods are proposed. The aim of this study is to use fuzzy technique for order preference by similarity to ideal solution (TOPSIS) and Analytical Hierarchal process (AHP) methods for the selection of better B-school. The proposed methods have been applied to a B-School selection problem of the students of NCR and results are presented. This chapter contributes to previous researches by adding a new avenue, where the MCDM technique can be useful. The selection of an institution for getting a professional degree is a very tough task for the students and as well as for their guardians. This method can help them to find a better solution by providing a quantitative framework.

A Fuzzy TOPSIS based Approach for ITSM Software Selection

2014 ◽  
Vol 5 (2) ◽  
pp. 1-26 ◽  
Author(s):  
Saeed Rouhani ◽  
Ahad Zare Ravasan
Keyword(s):  
Selection Criteria ◽  
Service Management ◽  
Evaluation Method ◽  
Fuzzy Topsis ◽  
Service Improvement ◽  
Fuzzy Evaluation ◽  
It Services ◽  
Functional Requirements ◽  
Software Selection ◽  
Order Preference

Nowadays a growing interest in Information Technology Service Management (ITSM) proves the trends and needs of their implementation in organizations. In order to implement an ITSM project successfully in an organization, it is essential to select a suitable ITSM software. Evaluation and selection of the ITSM software packages is complicated and time consuming decision making process. This paper presents an approach for dealing with such a problem. This approach introduces functional, non-functional and fuzzy evaluation method for ITSM software selection. The presented ITIL based approach breaks down ITSM software selection criteria into two broad categories namely functional (service strategy, service design, service transition, service operation, continual service improvement according to ITIL V3) and non-functional requirements (quality, technical, vendor, implementation) including totally 46 selection criteria. A facile Fuzzy Technique for Order Preference by Similarity to Ideal Solution (FTOPSIS) was customized for ITSM software selection based on identified criteria. The proposed approach is applied to a local Iranian company in the field of IT services in order to select and acquire an ITSM software and the provided numerical example illustrates the applicability of the approach for ITSM software selection. The approach can help practitioners assess ITSM software more properly and have a better software acquisition decision with growth in customer satisfaction and service time reduction.

Selection of Materials Using Multi Criteria Decision Making Method by Considering Physical and Mechanical Properties of Jute/Al2O3 Composites

2014 ◽  
Vol 592-594 ◽  
pp. 729-733 ◽  
Author(s):  
Priyadarshi Tapas Ranjan Swain ◽  
Sandhyarani Biswas
Keyword(s):  
Decision Making ◽  
Hybrid Composites ◽  
Physical And Mechanical Properties ◽  
Distance Measures ◽  
Correct Result ◽  
Multi Criteria Decision Making ◽  
Ideal Solution ◽  
Order Preference ◽  
Mcdm Method ◽  
Selection Of

Multi-Criteria Decision Making (MCDM) method plays a key role to find out the best option from all possible alternatives. From different application areas Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is one of the Multi-Criteria Decision Making (MCDM) method to find out the correct result. TOPSIS is a real-world and valuable procedure for ranking and selection of a number of externally determined substitutes through distance measures. In this paper, application of techniques for order preference by similarity of an ideal solution (TOPSIS) method is applied for solving multiple criteria (objective) optimization problem in mechanical and physical properties of jute/Al2O3 fiber based hybrid composites. The best performance value of composite is designed from ideal solution and as well as the worst performance value of composite is designed for negative-ideal solution. The results have demonstrated the model to be both robust and efficient.

The Technique for Order of Preference by Similarity to Ideal Solution Method in Fuzzy Environment

2020 ◽  
pp. 139-168
Author(s):  
Merve Cengiz Toklu
Keyword(s):  
Decision Making ◽  
Evaluation Criteria ◽  
Fuzzy Topsis ◽  
Decision Makers ◽  
Decision Making Process ◽  
Multi Criteria Decision Making ◽  
Ideal Solution ◽  
Topsis Method ◽  
Order Preference ◽  
Fuzzy Logic Approach

Decision-making process is the selection of the most appropriate one among the alternatives. Different selection criteria are considered in the decision-making process. Simultaneous assessment of different evaluation criteria may not always be possible. Multi-criteria decision-making techniques provide an easily applicable mathematical solution in this respect. Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method is one of the multi-criteria decision-making techniques. This method is used in many problems in literature and allows multiple decision makers to choose the most suitable alternative by evaluating them together with different criteria. Assessments of decision makers may include linguistic statements. In this case, the Fuzzy Logic approach can be used. In this chapter, Fuzzy TOPSIS method is explained with a detailed numerical example.

scholarly journals Trapezoidal Linguistic Cubic Fuzzy TOPSIS Method and Application in a Group Decision Making Program

2019 ◽  
Vol 29 (1) ◽  
pp. 1283-1300 ◽  
Author(s):  
Aliya Fahmi ◽  
Saleem Abdullah ◽  
Fazli Amin ◽  
Muhammad Aslam ◽  
Shah Hussain
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Fuzzy Number ◽  
Fuzzy Numbers ◽  
Group Decision ◽  
Hamming Distance ◽  
Fuzzy Topsis ◽  
Multi Criteria Decision Making ◽  
Topsis Method ◽  
Mcdm Method

Abstract The aim of this paper is to define some new operation laws for the trapezoidal linguistic cubic fuzzy number and Hamming distance. Furthermore, we define and use the trapezoidal linguistic cubic fuzzy TOPSIS method to solve the multi criteria decision making (MCDM) method. The new ranking method for trapezoidal linguistic cubic fuzzy numbers (TrLCFNs) are used to rank the alternatives. Finally, an illustrative example is given to verify and prove the practicality and effectiveness of the proposed method.

scholarly journals The importance of BIM capability assessment

2019 ◽  
Vol 27 (1) ◽  
pp. 24-48 ◽  
Author(s):  
Abdul-Majeed Mahamadu ◽  
Patrick Manu ◽  
Lamine Mahdjoubi ◽  
Colin Booth ◽  
Clinton Aigbavboa ◽  
...  
Keyword(s):  
Selection Criteria ◽  
Fuzzy Topsis ◽  
Content Type ◽  
Evaluation Of Performance ◽  
Building Information ◽  
Order Preference ◽  
Actual Contribution ◽  
Design Firms ◽  
Sets Theory

Purpose The emergence of building information modelling (BIM) has led to the need for pre-qualification and selection of organisations capable of working within a BIM environment. Several criteria have been proposed for the assessment of an organisation’s BIM capability during the pre-qualification and selection phase of projects. However, no studies have sought to empirically establish whether organisations selected on the basis of such criteria have actually been the most successful at delivering BIM on projects. The purpose of this paper is to address the aforementioned gap through a comparison of predicted BIM capability and post-selection performance. Design/methodology/approach BIM capability of firms in a case study was predicted using 28 BIM pre-qualification and selection criteria, prioritised based on their perceived contribution to BIM delivery success from a survey of practitioners on BIM-enabled projects. The comparison of predicted BIM capability and post-selection performance was, on the other hand, achieved through the application of the Technique to Order Preference by Similarity to Ideal Solution and fuzzy sets theory (Fuzzy-TOPSIS). Findings Findings underscore the reliability of the 28 BIM pre-qualification and selection criteria as well as the priority weightings proposed for their use in predicting BIM capability and likelihood of performance. The findings have highlighted the importance of criteria related as previous BIM use experience as well as information processing maturity as critical indicators of the capability of organisations, particularly design firms. Originality/value Overall, the findings highlight the need for prioritisation of BIM pre-qualification and selection criteria on the basis of their actual contribution to delivery success from post-selection evaluation of performance.

scholarly journals A Multi-Criteria Decision-Making Method Based on Single-Valued Neutrosophic Partitioned Heronian Mean Operator

Mathematics ◽  
2020 ◽  
Vol 8 (7) ◽  
pp. 1189
Author(s):  
Chao Tian ◽  
Juan Juan Peng ◽  
Zhi Qiang Zhang ◽  
Mark Goh ◽  
Jian Qiang Wang
Keyword(s):  
Decision Making ◽  
Selection Criteria ◽  
Aggregation Operators ◽  
Fuzzy Measure ◽  
Multi Criteria Decision Making ◽  
Special Cases ◽  
Mcdm Method ◽  
Heronian Mean

A multi-criteria decision-making (MCDM) method with single-valued neutrosophic information is developed based on the Partitioned Heronian Mean (PHM) operator and the Shapley fuzzy measure, which recognizes correlation among the selection criteria. Motivated by the PHM operator and Shapley fuzzy measure, two new aggregation operators, namely the single-valued neutrosophic PHM operator and the weighted single-valued neutrosophic Shapley PHM operator, are defined, and their corresponding properties and some special cases are investigated. An MCDM model is applied to solve the single-valued neutrosophic problem where weight information is not completely known. An example is provided to validate the proposed method.

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