scholarly journals Spherical Cubic Fuzzy Extended TOPSIS Method and Its Application in Multicriteria Decision-Making

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Tehreem ◽  
Amjad Hussain ◽  
Ahmed Alsanad ◽  
Mogeeb A. A. Mosleh
Keyword(s):  
Decision Making ◽  
Multicriteria Decision Making ◽  
Maximum Deviation ◽  
Topsis Method ◽  
Multicriteria Decision ◽  
Numerical Example ◽  
Structured Analysis ◽  
Incomplete Weight ◽  
Incomplete Weight Information

This paper aims to propose a new methodology for spherical cubic fuzzy (SCF) multicriteria decision-making (MCDM) utilizing the TOPSIS method that uses incomplete weight information. At first, the maximum deviation model is suggested to determine the criteria of weight values. An MCDM methodology is introduced using SCF information, based on the proposed method. Also, to validate the effectiveness of the proposed information, a numerical example is given. Finally, a comprehensive and structured analysis of existing work in comparison with previous work is given.

Extended topsis method based on Pythagorean cubic fuzzy multi-criteria decision making with incomplete weight information

2020 ◽  
Vol 38 (2) ◽  
pp. 2285-2296 ◽  
Author(s):  
Muhammad Sajjad Ali Khan ◽  
Faisal Khan ◽  
Joseph Lemley ◽  
Saleem Abdullah ◽  
Fawad Hussain
Keyword(s):  
Decision Making ◽  
Multi Criteria Decision Making ◽  
Topsis Method ◽  
Incomplete Weight ◽  
Incomplete Weight Information

Decision Making Model Based on the Z-Information

2020 ◽  
Vol 26 (11) ◽  
pp. 625-630
Author(s):  
O. M. Poleshchuk ◽  
Keyword(s):  
Decision Making ◽  
Multicriteria Decision Making ◽  
Decision Models ◽  
Probabilistic Assessment ◽  
Multicriteria Decision ◽  
Numerical Example ◽  
Model Based ◽  
Definition Of ◽  
Decision Making Model ◽  
The Ideal

A model of multicriteria decision making is developed taking into account the reliability of the data obtained. To formalize the information containing the data and assess their reliability, Z-numbers are used, the definition of which was given by Lotfie Zadeh in 2011. Most of the well-known decision models based on Z-numbers are limited by the assumption of a probabilistic assessment of the reliability of the data, which significantly narrows the scope of these models. This article partially removes the restrictive requirements when working with Z-numbers. For components of Z-numbers, aggregate indicators are calculated using a-cuts, based on which the similarity indicator between Z-numbers is determined. Choosing the best alternative is based on the minimum indicator of similarity with the ideal alternative. A numerical example is presented that shows the operation of the model and its effectiveness under conditions of multi-criteria selection.

scholarly journals Sistem Pendukung Keputusan Menentukan Tingkat Resiko Penjualan Online Dengan Menggunakan Metode TOPSIS

2021 ◽  
Vol 4 (1) ◽  
pp. 20-25
Author(s):  
Yosapat Sembiring ◽  
Paska Marto Hasugian
Keyword(s):  
Decision Making ◽  
Data Management ◽  
Programming Language ◽  
Multicriteria Decision Making ◽  
Decision Making Process ◽  
Topsis Method ◽  
Multicriteria Decision ◽  
Online Sales ◽  
Research Problems ◽  
Level Of Risk

At this time many people have started selling online. Even though only with makeshift items to make online sales, not a few people have succeeded in making these online sales. The TOPSIS method is one of the multicriteria decision-making methods, this method is one that is widely used to complete practical decision making. The more factors that must be considered in the decision making process, the more difficult it will be to make a decision on an issue. identification of research problems is the application of the DSS in determining the level of risk of online sales. This system was built using the PHP programming language with data management using the MySQL database. Rank results 1. Furniture = 0.8062 2.Electronics = 0.5810 3. Fashion = 0.1230

scholarly journals A Modified TOPSIS Method Based onDNumbers and Its Applications in Human Resources Selection

2016 ◽  
Vol 2016 ◽  
pp. 1-14 ◽  
Author(s):  
Liguo Fei ◽  
Yong Hu ◽  
Fuyuan Xiao ◽  
Luyuan Chen ◽  
Yong Deng
Keyword(s):  
Decision Making ◽  
Human Resources ◽  
Multicriteria Decision Making ◽  
Uncertain Information ◽  
Human Beings ◽  
Topsis Method ◽  
Decision Matrix ◽  
Multicriteria Decision ◽  
Decision Making Problem ◽  
Modified Topsis

Multicriteria decision-making (MCDM) is an important branch of operations research which composes multiple-criteria to make decision. TOPSIS is an effective method in handling MCDM problem, while there still exist some shortcomings about it. Upon facing the MCDM problem, various types of uncertainty are inevitable such as incompleteness, fuzziness, and imprecision result from the powerlessness of human beings subjective judgment. However, the TOPSIS method cannot adequately deal with these types of uncertainties. In this paper, aD-TOPSIS method is proposed for MCDM problem based on a new effective and feasible representation of uncertain information, calledDnumbers. TheD-TOPSIS method is an extension of the classical TOPSIS method. Within the proposed method,Dnumbers theory denotes the decision matrix given by experts considering the interrelation of multicriteria. An application about human resources selection, which essentially is a multicriteria decision-making problem, is conducted to demonstrate the effectiveness of the proposedD-TOPSIS method.

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