scholarly journals Pengambilan Keputusan Multi Hesitant N-Soft Sets

2020 ◽  
Vol 4 (6) ◽  
Author(s):  
Fatia Fatimah
Keyword(s):  
Decision Making ◽  
Online Learning ◽  
Random Sampling ◽  
Group Decision ◽  
Real Life ◽  
Decision Makers ◽  
Soft Sets ◽  
Life Data ◽  
Real Life Data ◽  
Sets Theory

In this article, we introduce a new hybrid model of -soft sets called multi hesitant -soft sets (MHNSS). The multi hesitant -soft sets is extention of -soft sets theory which is needed for multicriteria from some group decision makers. We propose the decision making algorithm of  MHNSS dan apply it with real life data of distance education especially online learning using webinar tutorial. The population are tutors of Universitas Terbuka Padang that using webinar tutorial between April until May 2020. We use random sampling and spread questionnaires online to collect the data. As a result, by using the MHNSS algorithm, we conclude that webinar tutorial is effective for conceptual subjects.

scholarly journals AHP-Group Decision Making Based on Consistency

Mathematics ◽  
2019 ◽  
Vol 7 (3) ◽  
pp. 242 ◽  
Author(s):  
Juan Aguarón ◽  
María Teresa Escobar ◽  
José Moreno-Jiménez ◽  
Alberto Turón
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Real Life ◽  
Decision Makers ◽  
Local Context ◽  
Consensus Matrix ◽  
Stability Intervals ◽  
The Individual ◽  
Individual Consistency

The Precise consistency consensus matrix (PCCM) is a consensus matrix for AHP-group decision making in which the value of each entry belongs, simultaneously, to all the individual consistency stability intervals. This new consensus matrix has shown significantly better behaviour with regards to consistency than other group consensus matrices, but it is slightly worse in terms of compatibility, understood as the discrepancy between the individual positions and the collective position that synthesises them. This paper includes an iterative algorithm for improving the compatibility of the PCCM. The sequence followed to modify the judgments of the PCCM is given by the entries that most contribute to the overall compatibility of the group. The procedure is illustrated by means of its application to a real-life situation (a local context) with three decision makers and four alternatives. The paper also offers, for the first time in the scientific literature, a detailed explanation of the process followed to solve the optimisation problem proposed for the consideration of different weights for the decision makers in the calculation of the PCCM.

scholarly journals A Novel Linguistic Z-Number QUALIFLEX Method and Its Application to Large Group Emergency Decision Making

2020 ◽  
Vol 2020 ◽  
pp. 1-12 ◽  
Author(s):  
Xue-Feng Ding ◽  
Li-Xia Zhu ◽  
Mei-Shun Lu ◽  
Qi Wang ◽  
Yi-Qi Feng
Keyword(s):  
Decision Making ◽  
Group Decision ◽  
Real Life ◽  
Decision Makers ◽  
Decision Matrix ◽  
Large Group ◽  
Emergency Event ◽  
Emergency Decision Making ◽  
Emergency Decision ◽  
Alternative Solutions

After an unconventional emergency event occurs, a reasonable and effective emergency decision should be made within a short time period. In the emergency decision making process, decision makers’ opinions are often uncertain and imprecise, and determining the optimal solution to respond to an emergency event is a complex group decision making problem. In this study, a novel large group emergency decision making method, called the linguistic Z-QUALIFLEX method, is developed by extending the QUALIFLEX method using linguistic Z-numbers. The evaluations of decision makers on the alternative solutions are first expressed as linguistic Z-numbers, and the group decision matrix is then constructed by aggregating the evaluations of all subgroups. The QUALIFLEX method is used to rank the alternative solutions for the unconventional emergency event. Besides, a real-life example of emergency decision making is presented, and a comparison with existing methods is performed to validate the effectiveness and practicability of the proposed method. The results show that the proposed linguistic Z-QUALIFLEX can accurately express the evaluations of the decision makers and obtain a more reasonable ranking result of solutions for emergency decision making.

scholarly journals A Decision Making Method using Fuzzy Soft Sets

2014 ◽  
Vol 9 (2) ◽  
Author(s):  
Samsiah Abdul Razak ◽  
Daud Mohamad
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Uncertain Data ◽  
Soft Set ◽  
Decision Makers ◽  
Fuzzy Soft Set ◽  
Soft Sets ◽  
Analytic Hierarchy ◽  
Fuzzy Soft Sets

The introduction of soft set theory by Molodstov has gained attention by many as it is useful in dealing with uncertain data. It is advantageous to use due to its parameterization form of data. This concept has been used in solving many decision making problems and has been generalized in various aspects in particular to fuzzy soft set (FSS) theory. In decision making using FSS, the objective is to select an object from a set of objects with respect to a set of choice parameter using fuzzy values. Although FSS theory has been extensively used in many applications, the importance of weight of parameters has not been highlighted and thus is not incorporated in the calculation. As it depends on one’s perception or opinion, the importance of the parameters may differ from one decision maker to another. Besides, existing methods in FSS only consider one or two decision makers to select the alternatives. In reality, group decision making normally involves more than two decision makers. In this paper we present a method for solving group decision making problems that involves more than two decision makers based on fuzzy soft set by taking into consideration the weight of parameters. The method of lambda – max which frequently utilize in fuzzy analytic hierarchy process (FAHP) has been applied to determine the weight of parameters and an algorithm for solving decision making problems is presented. Finally we illustrate the effectiveness of our method with a numerical example.

scholarly journals Group Decision Making using Interval-Valued Intuitionistic Fuzzy Soft Matrix and Confident Weight of Experts

2014 ◽  
Vol 4 (1) ◽  
pp. 57-77 ◽  
Author(s):  
Sujit Das ◽  
Samarjit Kar ◽  
Tandra Pal
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Intuitionistic Fuzzy Set ◽  
Real Life ◽  
Soft Sets ◽  
Soft Matrix ◽  
Intuitionistic Fuzzy ◽  
Multiple Attribute ◽  
Interval Valued

Abstract This article proposes an algorithmic approach for multiple attribute group decision making (MAGDM) problems using interval-valued intuitionistic fuzzy soft matrix (IVIFSM) and confident weight of experts. We propose a novel concept for assigning confident weights to the experts based on cardinals of interval-valued intuitionistic fuzzy soft sets (IVIFSSs). The confident weight is assigned to each of the experts based on their preferred attributes and opinions, which reduces the chances of biasness. Instead of using medical knowledgebase, the proposed algorithm mainly relies on the set of attributes preferred by the group of experts. To make the set of preferred attributes more important, we use combined choice matrix, which is combined with the individual IVIFSM to produce the corresponding product IVIFSM. This article uses IVIFSMs for representing the experts’ opinions. IVIFSM is the matrix representation of IVIFSS and IVIFSS is a natural combination of interval-valued intuitionistic fuzzy set (IVIFS) and soft set. Finally, the performance of the proposed algorithm is validated using a case study from real life

A novel stochastic group decision-making framework with dual hesitant fuzzy soft set for resilient supplier selection

2021 ◽  
pp. 1-19
Author(s):  
Yuanxiang Dong ◽  
Xinglu Deng ◽  
Xinyu Hu ◽  
Weijie Chen
Keyword(s):  
Decision Making ◽  
Supply Chains ◽  
Group Decision Making ◽  
Supplier Selection ◽  
Group Decision ◽  
Decision Makers ◽  
Soft Sets ◽  
Flexible Tool ◽  
Attribute Weights ◽  
Psychological Behavior

Suppliers can be regarded as unavoidable sources of external risks in modern supply chains, which may cause disruption of supply chains. A resilient supplier usually has a high adaptive ability to reduce the vulnerability against disruptions and recover from disruption to keep continuity in operations. This paper develops an effective multi-attribute group decision-making (MAGDM) framework for resilient supplier selection. Because of the many uncertainties in resilient supplier selection, the dual hesitant fuzzy soft sets (DHFSSs), a very flexible tool to express uncertain and complex information of decision-makers, is utilized to cope with it. In order to obtain the resilient supplier’s partial order relationship and consider the psychological behavior of decision-makers, this paper proposes the MAGDM framework with DHFSSs based on the TOPSIS method and prospect theory for resilient supplier selection. Furthermore, we consider the consensus level among experts of different backgrounds and experiences and propose a consensus measure method based dual hesitant fuzzy soft numbers (DHFSNs) before selecting a resilient supplier. The expert weights are calculated by the group consensus level between the expert and the group opinions. Meanwhile, we define the entropy of DHFSSs to determine the attribute weights objectively in the decision-making process. Based on this, the proposed method is applied to a practical manufacturing enterprise with an international supply chain for a resilient supplier selection problem. Finally, by performing a sensitivity analysis and a comparative analysis, the results demonstrate the robustness and validity of the proposed method.

scholarly journals Individual Reference Intervals for Personalized Interpretation of Clinical and Metabolomics Measurements

2021 ◽  
Author(s):  
Murih Pusparum ◽  
G&oumlkhan Ertaylan ◽  
Olivier Thas
Keyword(s):  
Decision Making ◽  
Clinical Practice ◽  
Clinical Decision Making ◽  
Real Life ◽  
Reference Interval ◽  
Clinical Decision ◽  
Upper And Lower Bounds ◽  
Life Data ◽  
Real Life Data ◽  
Data Points

The Population Reference Interval (PRI) refers to the range of outcomes that are expected in a healthy population for a clinical or a diagnostic measurement. This interval is widely used in daily clinical practice and is essential for assisting clinical decision making in diagnosis and treatment. In this study, we demonstrate that each individual indeed has a range for a given variable depending on personal biological traits. This Individual Reference Interval (IRI) can be calculated and be utilized in clinical practice, in combination with the PRI for improved decision making where multiple data points are present per variable. As calculating IRI requires several data points from the same individual to determine a personal range, here we introduce novel methodologies to obtain the correct estimates of IRI. We use Linear Quantile Mixed Models (LQMM) and Penalized Joint Quantile Models (PJQM) to estimate the IRI's upper and lower bounds. The estimates are obtained by considering both the within and between subjects' variations. We perform a simulation study designed to benchmark both methods' performance under different assumptions, resulted in PJQM giving a better empirical coverage than LQMM. Finally, both methods were evaluated on real-life data consisting of eleven clinical and metabolomics parameters from the VITO IAM Frontier study. The PJQM method also outperforms LQMM on its predictive accuracy in the real-life data setting. In conclusion, we introduce the concept of IRI and demonstrate two methodologies for calculating it to complement PRIs in clinical decision making.

Doubly Extended Fuzzy TOPSIS Method for Group Decision Making

2019 ◽  
Vol 66 (1) ◽  
pp. 27-50
Author(s):  
Dariusz Kacprzak
Keyword(s):  
Decision Making ◽  
Decision Maker ◽  
Group Decision Making ◽  
Group Decision ◽  
Real Life ◽  
Fuzzy Topsis ◽  
Decision Makers ◽  
Final Decision ◽  
Topsis Method ◽  
Decision Matrix

Multiple Criteria Decision Making methods, such as TOPSIS, have become very popular in recent years and are frequently applied to solve many real-life situations. However, the increasing complexity of the decision problems analysed makes it less feasible to consider all the relevant aspects of the problems by a single decision maker. As a result, many real-life problems are discussed by a group of decision makers. In such a group each decision maker can specialize in a different field and has his/her own unique characteristics, such as knowledge, skills, experience, personality, etc. This implies that each decision maker should have a different degree of influence on the final decision, i.e., the weights of decision makers should be different. The aim of this paper is to extend the fuzzy TOPSIS method to group decision making. The proposed approach uses TOPSIS twice. The first time it is used to determine the weights of decision makers which are then used to calculate the aggregated decision matrix for all the group decision matrices provided by the decision makers. Based on this aggregated matrix, the extended TOPSIS is used again, to rank the alternatives and to select the best one. A numerical example illustrates the proposed approach.

scholarly journals Warehouse location selection with TOPSIS group decision-making under different expert priority allocations

2020 ◽  
Vol 12 (4) ◽  
pp. 22-39
Author(s):  
Lanndon Ocampo ◽  
Gianne Jean Genimelo ◽  
Jerome Lariosa ◽  
Raul Guinitaran ◽  
Philip John Borromeo ◽  
...  
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Real Life ◽  
Distribution Networks ◽  
Multiple Criteria ◽  
Decision Makers ◽  
Final Decision ◽  
Location Selection ◽  
Warehouse Location

Abstract Warehouses are crucial infrastructures in supply chains. As a strategic task that would potentially impact various long-term agenda, warehouse location selection becomes an important decision-making process. Due to quantitative and qualitative multiple criteria in selecting alternative warehouse locations, the task becomes a multiple criteria decision-making problem. Current literature offers several approaches to addressing the domain problem. However, the number of factors or criteria considered in the previous works is limited and does not reflect real-life decision-making. In addition, such a problem requires a group decision, with decision-makers having different motivations and value systems. Analysing the varying importance of experts comprising the group would provide insights into how these variations influence the final decision regarding the location. Thus, in this work, we adopted the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to address a warehouse location decision problem under a significant number of decision criteria in a group decision-making environment. To elucidate the proposed approach, a case study in a product distribution firm was carried out. Findings show that decision-makers in this industry emphasise criteria that maintain the distribution networks more efficiently at minimum cost. Results also reveal that varying priorities of the decision-makers have little impact on the group decision, which implies that their degree of knowledge and expertise is comparable to a certain extent. With the efficiency and tractability of the required computations, the TOPSIS method, as demonstrated in this work, provides a useful, practical tool for decision-makers with limited technical computational expertise in addressing the warehouse location problem.

scholarly journals Application of the Bipolar Neutrosophic Hamacher Averaging Aggregation Operators to Group Decision Making: An Illustrative Example

Symmetry ◽  
2019 ◽  
Vol 11 (5) ◽  
pp. 698 ◽  
Author(s):  
Muhammad Jamil ◽  
Saleem Abdullah ◽  
Muhammad Yaqub Khan ◽  
Florentin Smarandache ◽  
Fazal Ghani
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Real Life ◽  
Aggregation Operators ◽  
Decision Makers ◽  
Weighted Averaging ◽  
Neutrosophic Set ◽  
Ordered Weighted Averaging ◽  
New Methods

The present study aims to introduce the notion of bipolar neutrosophic Hamacher aggregation operators and to also provide its application in real life. Then neutrosophic set (NS) can elaborate the incomplete, inconsistent, and indeterminate information, Hamacher aggregation operators, and extended Einstein aggregation operators to the arithmetic and geometric aggregation operators. First, we give the fundamental definition and operations of the neutrosophic set and the bipolar neutrosophic set. Our main focus is on the Hamacher aggregation operators of bipolar neutrosophic, namely, bipolar neutrosophic Hamacher weighted averaging (BNHWA), bipolar neutrosophic Hamacher ordered weighted averaging (BNHOWA), and bipolar neutrosophic Hamacher hybrid averaging (BNHHA) along with their desirable properties. The prime gain of utilizing the suggested methods is that these operators progressively provide total perspective on the issue necessary for the decision makers. These tools provide generalized, increasingly exact, and precise outcomes when compared to the current methods. Finally, as an application, we propose new methods for the multi-criteria group decision-making issues by using the various kinds of bipolar neutrosophic operators with a numerical model. This demonstrates the usefulness and practicality of this proposed approach in real life.

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