scholarly journals Determination the Optimum Level of Amaranth Grain in Broilers Pelleted Diet Based On Multiple Attribute Decision Making Method (TOPSIS Model) and Production Index

2020 ◽  
Vol 11 (27) ◽  
pp. 1-8
Author(s):  
Amir Hossein Alizadeh-Ghamsari ◽  
Seyed Abdullah Hosseini ◽  
◽  
Keyword(s):  
Decision Making ◽  
Multiple Attribute Decision Making ◽  
Optimum Level ◽  
Production Index ◽  
Amaranth Grain ◽  
Multiple Attribute ◽  
Pelleted Diet ◽  
Topsis Model

A Correlation-Based TOPSIS Method for Multiple Attribute Decision Making with Single-Valued Neutrosophic Information

2020 ◽  
Vol 19 (01) ◽  
pp. 343-358 ◽  
Author(s):  
Shouzhen Zeng ◽  
Dandan Luo ◽  
Chonghui Zhang ◽  
Xingsen Li
Keyword(s):  
Decision Making ◽  
Correlation Coefficient ◽  
Correlation Coefficients ◽  
Multiple Attribute Decision Making ◽  
Neutrosophic Set ◽  
Significant Feature ◽  
Multiple Attribute ◽  
Order Preference ◽  
Topsis Approach ◽  
Topsis Model

The single-valued neutrosophic set (SVNS) is considered as an attractive tool for handling highly uncertain and vague information. With this regard, different from the most current distance-based technique for order preference by similarity to ideal solution (TOPSIS) methods, this study proposes a correlation-based TOPSIS model for addressing the single-valued neutrosophic (SVN) multiple attribute decision making (MADM) problems. To achieve this aim, we first develop a novel conception of SVN correlation coefficient, whose significant feature is that it lies in the interval [[Formula: see text],1], which is in accordance with the classical correlation coefficient in statistics, whereas all the existing SVN correlation coefficients in the literature are within unit interval [0,1]. Afterwards, a weighted SVN correlation coefficient is also introduced to infuse the importance of attributes. Moreover, a correlation-based comprehensive index is further proposed to establish the central structure of TOPSIS model, called the SVN correlation-based TOPSIS approach. Finally, a numerical example and relevant comparative analysis are implemented to explain the applicability and effectiveness of the mentioned methodology.

PENERAPAN METODE SIMPLE ADDITIVE WEIGHTING DALAM PENETAPAN TENAGA KEPENDIDIKAN BERPRESTASI

2018 ◽  
Vol 1 (2) ◽  
pp. 45-54
Author(s):  
Helpi Nopriandi
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Decision Support Systems ◽  
Support Systems ◽  
Multiple Attribute Decision Making ◽  
Multiple Attribute ◽  
Simple Additive Weighting

Tenaga Kependidikan merupakan anggota masyarakat yang mengabdikan diri dan diangkat untuk menunjang penyelenggaraan pendidikan. Decision Support Systems atau lebih dikenal dengan Sistem Pendukung Keputusan adalah bagian dari sebuah sistem informasi yang berbasis komputer termasuk sistem yang berbasis ilmu pengetahuan dan dipakai untuk mendukung pengambil  keputusan dalam suatu organisasi atau perusahaan. untuk memudahkan pimpinan dalam mengambil sebuah keputusan dibuatlah suatu sistem pengambil keputusan dengan menggunakan Fuzzy Multiple Attribute Decision Making  (FMADM) digunakan untuk mencari alternatif optimalkan dari sejumlah alternatif dengan kriteria tertentu, sedangkan metode Simple Additive Weighting (SAW). Metode SAW sering juga dikenal istilah metode penjumlahan terbobot. Konsep dasar metode SAW adalah mencari penjumlahan terbobot dari rating kinerja pada setiap alternatif dari semua atribut.

scholarly journals Extended VIKOR-QUALIFLEX Method Based on Trapezoidal Fuzzy Two-Dimensional Linguistic Information for Multiple Attribute Decision-Making with Unknown Attribute Weight

Mathematics ◽  
2020 ◽  
Vol 9 (1) ◽  
pp. 37
Author(s):  
Ye Li ◽  
Yisheng Liu
Keyword(s):  
Decision Making ◽  
Qualitative Evaluation ◽  
Multiple Attribute Decision Making ◽  
Two Dimensional ◽  
Linguistic Variables ◽  
Linguistic Information ◽  
Attribute Weight ◽  
Model Based ◽  
Subjective Weight ◽  
Multiple Attribute

Considering the advantages of trapezoid fuzzy two-dimensional linguistic variables (TrF2DLVs), which can not only accurately describe the qualitative evaluation but also use qualitative linguistic variables (LVs) to describe the confidence level of this evaluation in the second dimension, this paper proposes a novel method based on trapezoidal fuzzy two-dimensional linguistic information to solve multiple attribute decision-making (MADM) problems with unknown attribute weight. First, a combination weight model is constructed, which covers a subjective weight determination model based on the proposed trapezoidal fuzzy two-dimensional linguistic best-worst method (TrF2DL-BWM) and an objective weight determination model based on the proposed CRITIC method. Then, in order to accurately rank the alternatives, an extended VIKOR-QUALIFLEX method is proposed, which can measure the concordance index of each ranking combination by means of group utility and individual maximum regret value of each evaluation alternative. Finally, a practical problem of lean management assessment for industrial residential projects is solved by the proposed method, and the effectiveness and advantages of the method are demonstrated by comparative analysis and discussion.

Link prediction in multiplex networks using a novel multiple-attribute decision-making approach

2021 ◽  
pp. 106904
Author(s):  
Hongsheng Luo ◽  
Longjie Li ◽  
Yakun Zhang ◽  
Shiyu Fang ◽  
Xiaoyun Chen
Keyword(s):  
Decision Making ◽  
Link Prediction ◽  
Multiple Attribute Decision Making ◽  
Multiplex Networks ◽  
Multiple Attribute
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