Harmonic Aggregation Operator with Trapezoidal Picture Fuzzy Numbers and Its Application in a Multiple-Attribute Decision-Making Problem

Picture fuzzy sets (PFSs) can be used to handle real-life problems with uncertainty and vagueness more effectively than intuitionistic fuzzy sets (IFSs). In the process of information aggregation, many aggregation operators under PFSs are used by different authors in different fields. In this article, a multi-attribute decision-making (MADM) problem is introduced utilizing harmonic mean aggregation operators with trapezoidal fuzzy number (TrFN) under picture fuzzy information. Three harmonic mean operators are developed namely trapezoidal picture fuzzy weighted harmonic mean (TrPFWHM) operator, trapezoidal picture fuzzy order weighted harmonic mean (TrPFOWHM) operator and trapezoidal picture fuzzy hybrid harmonic mean (TrPFHHM) operator. The related properties about these operators are also studied. At last, an MADM problem is considered to interrelate among these operators. Furthermore, a numerical instance is considered to explain the productivity of the proposed operators.

Approaches to Multiple Attribute Decision-Making with Fuzzy Number Intuitionistic Fuzzy Information and Their Application to English Teaching Quality Evaluation

Many experts and scholars focus on the Maclaurin symmetric mean (MSM) operator, which can reflect the interrelationship among the multi-input arguments. It has been generalized to different fuzzy environments and put into use in various actual decision problems. The fuzzy number intuitionistic fuzzy numbers (FNIFNs) could well depict the uncertainties and fuzziness during the English teaching quality evaluation. And the English teaching quality evaluation is frequently viewed as the multiple attribute decision-making (MADM) issue. We expand the MSM equation with FNIFNs to propose the fuzzy number intuitionistic fuzzy MSM (FNIFMSM) equation and fuzzy number intuitionistic fuzzy weighted MSM (FNIFWMSM) equation in this study. A few MADM tools are developed with FNIFWMSM equation. Finally, taking English teaching quality evaluation as an example, this paper illustrates the depicted approach.

Bipolar Complex Fuzzy Hamacher Aggregation Operators and Their Applications in Multi-Attribute Decision Making

On the basis of Hamacher operations, in this manuscript, we interpret bipolar complex fuzzy Hamacher weighted average (BCFHWA) operator, bipolar complex fuzzy Hamacher ordered weighted average (BCFHOWA) operator, bipolar complex fuzzy Hamacher hybrid average (BCFHHA) operator, bipolar complex fuzzy Hamacher weighted geometric (BCFHWG) operator, bipolar complex fuzzy Hamacher ordered weighted geometric (BCFHOWG) operator, and bipolar complex fuzzy Hamacher hybrid geometric (BCFHHG) operator. We present the features and particular cases of the above-mentioned operators. Subsequently, we use these operators for methods that can resolve bipolar complex fuzzy multiple attribute decision making (MADM) issues. We provide a numerical example to authenticate the interpreted methods. In the end, we compare our approach with existing methods in order to show its effectiveness and practicality.

Sistem Penunjang Keputusan Perankingan Kinerja Terbaik Gugus Tugas Percepatan Penanganan COVID-19 Provinsi Maluku Utara Menggunakan Metode Simple Addtive Weighting (SAW)

Tujuan penelitian untuk menentukan perankingan kinerja terbaik gugus tugas percepatan penanganan COVID-19 di Provinsi Maluku Utara dengan penyelesaikan Fuzzy Multiple Attribute Decision Making (FMADM) menggunakan metode Simple Additive Weighting (SAW). Dalam penelitian ini menggunakan 8 (delapan) bidang yang dijadikan sebagai alternative yaitu Bidang Pencegahan (Alternatif-1), Penanganan (Alternatif-2), Keuangan (Alternatif-3), Pengamanan dan GAKUM (Alternatif-4), Logistik (Alternatif-5), dan Akuntabilitas dan Pengawasan (Alternatif- 6), Bidang Pemulihan Layanan Dasar (Alternatif-7), dan Perencanaan, Data, Pakar, dan Analisis (Alternatif-8). Kinerja gugus tugas pecepatan penanganan COVID-19 di Maluku Utara sesuai bidang masing-masing perlu diukur secara matematis.Dalam melakukan proses perhitungan kinerja Gugus tugas Percepatan Penanganan COVID-19 Provinsi Maluku Utara, peneliti menggunakan 6 (enam) criteria sebagai acuan dalam analisis penunjang pengambilan keputusan yaitu C1 = Kedisiplinan Kerja, C2 = Pendidkan terakhir, C3 = Pengalaman Kerja, C4 = Kerja sama, C5= Keaktifan, C6= Kesehatan dan Self Development personel. Sehinggan akan menghasilakan perankingan berdasarkan hasil perhitungan nilai tertinggi. Hasil perhitungannya adalah Alternatif-1 = 0,85 dengan kategori Sangat Baik , Alternatif-7, = 0,82, Alternatif-3 = 0,76, Alternatif-2 = 0,71, Alternatif-6 = 0,71 dan Alternatif-4 = 0,69 dengan kategori Baik, dan Alternatif-8 = 0,66 dan Alternatif-5 = 0,65 dengan kategori Kurang Baik.

Community Detection Based on Density Peak Clustering Model and Multiple Attribute Decision-Making Strategy TOPSIS

Community detection is one of the key research directions in complex network studies. We propose a community detection algorithm based on a density peak clustering model and multiple attribute decision-making strategy, TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution). First, the two-dimensional dataset, which is transformed from the network by taking the density and distance as the attributes of nodes, is clustered by using the DBSCAN algorithm, and outliers are determined and taken as the key nodes. Then, the initial community frameworks are formed and expanded by adding the most similar node of the community as its new member. In this process, we use TOPSIS to cohesively integrate four kinds of similarities to calculate an index, and use it as a criterion to select the most similar node. Then, we allocate the nonkey nodes that are not covered in the expanded communities. Finally, some communities are merged to obtain a stable partition in two ways. This paper designs some experiments for the algorithm on some real networks and some synthetic networks, and the proposed method is compared with some popular algorithms. The experimental results testify for the effectiveness and show the accuracy of our algorithm.

Some Single-Valued Neutrosophic Uncertain Linguistic Maclaurin Symmetric Mean Operators and Their Application to Multiple-Attribute Decision Making

The Maclaurin symmetric mean (MSM) operator has a good aggregation effect. It can capture the relationships between multiple input parameters, and the neutrosophic uncertain linguistic numbers can well represent some indeterminate and incomplete information. In this paper, we combine the MSM operator with the singled-valued neutrosophic uncertain linguistic set and propose some MSM operators based on single-valued neutrosophic uncertain linguistic environment, such as single-valued neutrosophic uncertain linguistic Maclaurin symmetric mean(SVNULMSM) operator and single-valued neutrosophic uncertain linguistic generalized Maclaurin symmetric mean(SVNULGMSM) operator. First of all, according to the neutrosophic set and uncertain linguistic numbers, we propose the single-valued neutrosophic uncertain linguistic numbers and give some operating rules. Furthermore, considering the influence of attribute weight on the results, we introduce the weighted SVNULMSM operator and weighted SVNULGMSM operator. Then, we propose a method to deal with MSDM problems and give the specific steps to solve the problem. Finally, an investment example is used to verify the effectiveness of our method, and the superiority of the method is proved by comparing with other methods.

Behavioral Risky Multiple Attribute Decision Making with Interval Type-2 Fuzzy Ranking Method and TOPSIS Method

Considering the decision maker’s psychological state will influence their evaluation result in the risky multi-attribute decision-making problem, and the uncertainty of evaluation information. In this paper, we will propose a behavioral risky multiple attribute decision making with interval type-2 fuzzy ranking method and TOPSIS method. The interval type-2 fuzzy set is used to express the uncertainty of evaluation information, the prospect theory is applied to describe people’s psychological state in the processing of risk decision making. First, we define a new ranking method for interval type-2 fuzzy set to compare the interval type-2 fuzzy evaluation information and the expectation. Second, we give a relative distance for interval type-2 fuzzy set to get the distance between the interval type-2 fuzzy evaluation information and expectation. Third, we use the prospect theory, the new defined ranking method and the new defined distance formula to obtain the comprehensive prospect value. Fourth, we use the improved TOPSIS method and the comprehensive prospect value to rank the alternatives. Based on the above-mentioned steps, we give the solution for risky interval type-2 fuzzy multiple attribute decision-making problem, which named as the behavioral risky multiple attribute decision making with interval type-2 fuzzy ranking method and TOPSIS method. Finally, we use an example to show the rationality of this method.