scholarly journals A Novel Multicriteria Decision-Making Method Based on Distance, Similarity, and Correlation: DSC TOPSIS

2019 ◽  
Vol 2019 ◽  
pp. 1-20 ◽  
Author(s):  
Semra Erpolat Taşabat
Keyword(s):  
Decision Making ◽  
Distance Measure ◽  
Pearson Correlation ◽  
Multicriteria Decision Making ◽  
Distance Measures ◽  
Important Place ◽  
Multicriteria Decision ◽  
Development Levels ◽  
The 1960S ◽  
The Right

Decision-making, briefly defined as choosing the best among the possible alternatives within the possibilities and conditions available, is a far more comprehensive process than instant. While in the decision-making process, there are often a lot of criteria as well as alternatives. In this case, methods referred to as Multicriteria Decision-Making (MCDM) are applied. The main purpose of the methods is to facilitate the decision-maker's job, to guide the decision-maker and help him to make the right decisions if there are too many options. In cases where there are many criteria, effective and useful decisions have been taken for granted at the beginning of the 1960s for the first time and supported by day-to-day work. A variety of methods have been developed for this purpose. The basis of some of these methods is based on distance measures. The most known method in the literature based on the concept of distance is, of course, a method called Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). In this study, a new MCDM method that uses distance, similarity, and correlation measures has been proposed. This new method is shortly called DSC TOPSIS to include the initials of distance, similarity, and correlation words, respectively, prefix of TOPSIS name. In the method, Euclidean was used as distance measure, cosine was used as similarity measure, and Pearson correlation was used as relation measure. Using the positive ideal and negative-ideal values obtained from these measures, respectively, a common positive ideal value and a common negative-ideal value were obtained. Afterward DSC TOPSIS is discussed in terms of standardization and weighting. The study also proposed three different new ranking indexes from the ranking index used in the traditional TOPSIS method. The proposed method has been tested on the variables showing the development levels of the countries that have a very important place today. The results obtained were compared with the Human Development Index (HDI) value developed by the United Nations.

A Fuzzy Multicriteria Decision-Making Approach to Crime Linkage

2018 ◽  
Vol 11 (2) ◽  
pp. 31-50 ◽  
Author(s):  
Soumendra Goala ◽  
Palash Dutta
Keyword(s):  
Decision Making ◽  
Linkage Analysis ◽  
Distance Measure ◽  
Multicriteria Decision Making ◽  
High Volume ◽  
Criminal Cases ◽  
Multicriteria Decision ◽  
Fuzzy Distance ◽  
Crime Linkage

This article describes how serial crimes are very interesting for study in the absence of proper and solid evidence. From a high volume of criminal cases of similar types, it is difficult to detect the crimes that were committed by the same offender or not. The process of linking of crimes which were committed by the same offender or offenders is called Crime Linkage Analysis. In this article, a new hesitant fuzzy distance measure has been introduced and a fuzzy multicriteria decision-making approach has been proposed to help Crime Linkage Analysis, which enables us to find to what extent a pair of crime shares a common offender or offenders.

On Some Advancements within Certain Multicriteria Decision Making Support Methodology

2013 ◽  
Vol 2 (2) ◽  
pp. 143 ◽  
Author(s):  
Pawel Tadeusz Kazibudzki ◽  
Andrzej Z Grzybowski
Keyword(s):  
Decision Making ◽  
Pairwise Comparison ◽  
Multicriteria Decision Making ◽  
Scientific Paper ◽  
Analytic Hierarchy ◽  
Management Activity ◽  
Multicriteria Decision ◽  
Managerial Decisions ◽  
The Right ◽  
Decision Making Support

Deriving true priority vectors from intuitive pairwise comparison matrices (PCMs) and consistency measurement of decision makers judgments about their genuine weights are crucial issues within the multicriteria decision making support methodology called Analytic Hierarchy Process (AHP). The most popular procedure in the ranking process, constitutes the Right Eigenvector Method (REV). The inventor of the AHP convinces that as long as inconsistent PCMs are allowed in the AHP none of the other existing procedures qualify and the REV provides the only right solution in this process. The objective of this scientific paper is to examine if the former opinion can be considered as experimentally confirmed. For this purpose it was decided to apply Monte Carlo methodology. However, rather than simulate and analyze simulations results for a single PCM, as it has been done so far by many other authors, we decided to design and analyze computer simulations results for a singular model of the AHP framework. Our findings lead to inevitable conclusion that the REV cannot longer be perceived as a dominant procedure within the AHP methodology, especially when nonreciprocal PCMs are considered. It was verified empirically in our research that in the situation when nonreciprocal PCMs are considered the REV impoverishes the entire AHP methodology by its lack of PCMs inconsistency measure in such cases. Moreover, it provides less accurate rankings for a particular decision in comparison to other presented methods. It was also unequivocally verified that the enforced reciprocity of PCM leads directly to worse estimates of priorities weights. Altogether, it seems very important from the perspective of methodology supporting multicriteria decision making, the crucial process embedded in most of management activity. In the consequence, because the REV recedes other prioritization procedures available for the AHP methodology, it is advised to consider them instead, especially under some circumstances of an important and very tight managerial decisions.

scholarly journals Distance Based Entropy Measure of Interval-Valued Intuitionistic Fuzzy Sets and Its Application in Multicriteria Decision Making

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Tabasam Rashid ◽  
Shahzad Faizi ◽  
Sohail Zafar
Keyword(s):  
Decision Making ◽  
Fuzzy Set ◽  
Distance Measure ◽  
Intuitionistic Fuzzy Set ◽  
Multicriteria Decision Making ◽  
Fuzzy Entropy ◽  
Entropy Measure ◽  
Multicriteria Decision ◽  
Intuitionistic Fuzzy ◽  
Interval Valued

Fuzzy entropy means the measurement of fuzziness in a fuzzy set and therefore plays a vital role in solving the fuzzy multicriteria decision making (MCDM) and multicriteria group decision making (MCGDM) problems. In this study, the notion of the measure of distance based entropy for uncertain information in the context of interval-valued intuitionistic fuzzy set (IVIFS) is introduced. The arithmetic and geometric average operators are firstly used to aggregate the interval-valued intuitionistic fuzzy information provided by the decision makers (DMs) or experts corresponding to each alternative, and then the fuzzy entropy of each alternative is calculated based on proposed distance measure. Several numerical examples are solved to demonstrate the application to MCDM and MCGDM problems to show the effectiveness of the proposed approach.

scholarly journals Fuzzy VIKOR approach for selection of big data analyst in procurement management

2016 ◽  
Vol 10 (1) ◽  
Author(s):  
Surajit Bag
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Big Data Analytics ◽  
Multicriteria Decision Making ◽  
Human Resource Managers ◽  
Multicriteria Decision ◽  
Fuzzy Vikor ◽  
Data Analyst ◽  
Business Acumen ◽  
The Right

Background: Big data and predictive analysis have been hailed as the fourth paradigm of science. Big data and analytics are critical to the future of business sustainability. The demand for data scientists is increasing with the dynamic nature of businesses, thus making it indispensable to manage big data, derive meaningful results and interpret management decisions.Objectives: The purpose of this study was to provide a brief conceptual review of big data and analytics and further illustrate the use of a multicriteria decision-making technique in selecting the right skilled candidate for big data and analytics in procurement management.Method: It is important for firms to select and recruit the right data analyst, both in terms of skills sets and scope of analysis. The nature of such a problem is complex and multicriteria decision-making, which deals with both qualitative and quantitative factors. In the current study, an application of the Fuzzy VIsekriterijumska optimizacija i KOmpromisno Resenje (VIKOR) method was used to solve the big data analyst selection problem.Results: From this study, it was identified that Technical knowledge (C1), Intellectual curiosity (C4) and Business acumen (C5) are the strongest influential criteria and must be present in the candidate for the big data and analytics job.Conclusion: Fuzzy VIKOR is the perfect technique in this kind of multiple criteria decisionmaking problematic scenario. This study will assist human resource managers and procurement managers in selecting the right workforce for big data analytics.

scholarly journals Grey Relational Bidirectional Projection Method for Multicriteria Decision Making with Hesitant Intuitionistic Fuzzy Linguistic Information

2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Yuqi Zang ◽  
Xiaodong Zhao ◽  
Shiyong Li ◽  
Adnan Nazir
Keyword(s):  
Decision Making ◽  
Projection Method ◽  
Multicriteria Decision Making ◽  
Comparison Method ◽  
Distance Measures ◽  
Linguistic Information ◽  
Multicriteria Decision ◽  
Intuitionistic Fuzzy ◽  
Grey Relational ◽  
Fuzzy Linguistic

We investigate a novel approach for multicriteria decision making (MCDM) with hesitant intuitionistic fuzzy linguistic information. To compare the hesitant intuitionistic fuzzy linguistic term sets (HIFLTSs), we propose a comparison method of HIFLTSs. A family of distance measures of HIFLTSs is developed. After that, we propose the grey relational bidirectional projection method based on the proposed comparison method and distance measures of IVHFLNs for dealing with MCDM problems. Furthermore, we establish a nonlinear optimization model to obtain the weight vector of criteria. Finally, an illustrative example is given to demonstrate the effectiveness and flexibility of the proposed approach.

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