scholarly journals CRM-BASED DYNAMIC DECISION-MAKING WITH HESITANT FUZZY INFORMATION FOR THE EVALUATION OF RANGELANDS

2018 ◽  
Vol 24 (5) ◽  
pp. 1979-2002 ◽  
Author(s):  
Xiaodi Liu ◽  
Zengwen Wang ◽  
Shitao Zhang ◽  
Antoinette Hetzler
Keyword(s):  
Decision Making ◽  
Dynamic Decision Making ◽  
Ratio Method ◽  
Ideal Solution ◽  
Economic Aspects ◽  
Fuzzy Information ◽  
Fuzzy Environment ◽  
Global Land ◽  
Negative Ideal Solution ◽  
The Impact

As one of the important components of global land ecosystem, rangeland ecosystem has important value of ecosystem services. With the degeneration of rangeland in recent years, sustainability within rangeland ecosystem has become an increasingly important issue. The aim of this paper is to develop a novel dynamic decision-making approach based on hesitant fuzzy information to evaluate rangeland sustainability that considers ecological, social and economic aspects. Firstly, a modified satisfaction degree of alternative is presented, based on which a mathematical model for determining the stage weights is constructed. Secondly, the compromise ratio method (CRM), whose basic principle is that the optimal alternative should have the nearest distance from positive ideal solution and the longest distance from negative ideal solution simultaneously, is extended to accommodate hesitant fuzzy environment, and then adopted to tackle the dynamic decision-making with hesitant fuzzy information. Compared with the existing methods, the proposed method can eliminate the impact of attribute magnitude and dimension. Lastly, a numerical example on the evaluation of rangelands is provided to illustrate the practicality and superiority of the proposed method.

RELATIVE RATIO METHOD FOR MULTIPLE ATTRIBUTE DECISION MAKING PROBLEMS

2009 ◽  
Vol 08 (02) ◽  
pp. 289-311 ◽  
Author(s):  
DENG-FENG LI
Keyword(s):  
Decision Making ◽  
Operations Research ◽  
Multiple Attribute Decision Making ◽  
Research Field ◽  
Ratio Method ◽  
Ideal Solution ◽  
Relative Ratio ◽  
Multiple Attribute ◽  
Negative Ideal Solution ◽  
The Ideal

The multiple attribute decision making (MADM) is an important research field in decision science and operations research. Recently, several commonly used methods such as the TOPSIS and the VIKOR were proposed to solve the MADM problems. The TOPSIS and VIKOR are based on aggregating functions representing closeness to the ideal, which originated in the compromise programming method. The aim of this paper is to develop a new methodology called the relative ratio (RR) for the MADM problems. In this RR method, a compromise solution/alternative is determined based on the concept that the chosen alternative should be as close to the ideal solution as possible and as far away from the negative-ideal solution as possible simultaneously. The computation principle and procedure of the RR method are described in detail in this paper. Moreover comparisons of the RR method with the TOPSIS as well as the VIKOR are made theoretically and illustrated with a numerical example.

Extended TOPSIS method based on the entropy measure and probabilistic hesitant fuzzy information and their application in decision support system

2021 ◽  
pp. 1-12
Author(s):  
Muhammad Naeem ◽  
Muhammad Ali Khan ◽  
Saleem Abdullah ◽  
Muhammad Qiyas ◽  
Saifullah Khan
Keyword(s):  
Decision Making ◽  
Fuzzy Set ◽  
Distance Measure ◽  
Group Decision ◽  
Hesitant Fuzzy Set ◽  
Entropy Measure ◽  
Fuzzy Information ◽  
Score Functions ◽  
Fuzzy Environment ◽  
Basic Operating

Probabilistic hesitant fuzzy Set (PHFs) is the most powerful and comprehensive idea to support more complexity than developed fuzzy set (FS) frameworks. In this paper, it can explain a novel, improved TOPSIS-based method for multi-criteria group decision-making (MCGDM) problem through the Probabilistic hesitant fuzzy environment, in which the weights of both experts and criteria are completely unknown. Firstly, we discuss the concept of PHFs, score functions and the basic operating laws of PHFs. In fact, to compute the unknown weight information, the generalized distance measure for PHFs was defined based on the Probabilistic hesitant fuzzy entropy measure. Second, MCGDM will be presented with the PHF information-based decision-making process.

scholarly journals Extensions of Dombi Aggregation Operators for Decision Making under m-Polar Fuzzy Information

2020 ◽  
Vol 2020 ◽  
pp. 1-20 ◽  
Author(s):  
Muhammad Akram ◽  
Naveed Yaqoob ◽  
Ghous Ali ◽  
Wathek Chammam
Keyword(s):  
Decision Making ◽  
Multicriteria Decision Making ◽  
Aggregation Operators ◽  
Weighted Averaging ◽  
Fuzzy Information ◽  
Ordered Weighted Averaging ◽  
Fuzzy Environment ◽  
Proposed Model ◽  
Electre I ◽  
Geometric Operator

An m-polar fuzzy set is a powerful mathematical model to analyze multipolar, multiattribute, and multi-index data. The m-polar fuzzy sets have appeared as a useful tool to portray uncertainty in multiattribute decision making. The purpose of this article is to analyze the aggregation operators under the m-polar fuzzy environment with the help of Dombi norm operations. In this article, we develop some averaging and geometric aggregation operators using Dombi t-norm and t-conorm to handle uncertainty in m-polar fuzzy (mF, henceforth) information, which are mF Dombi weighted averaging (mFDWA) operator, mF Dombi ordered weighted averaging (mFDOWA) operator, mF Dombi hybrid averaging (mFDHA) operator, mF Dombi weighted geometric (mFDWG) operator, mF Dombi weighted ordered geometric operator, and mF Dombi hybrid geometric (mFDHG) operator. We investigate properties, namely, idempotency, monotonicity, and boundedness, for the proposed operators. Moreover, we give an algorithm to solve multicriteria decision-making issues which involve mF information with mFDWA and mFDWG operators. To prove the validity and feasibility of the proposed model, we solve two numerical examples with our proposed models and give comparison with mF-ELECTRE-I approach (Akram et al. 2019) and mF Hamacher aggregation operators (Waseem et al. 2019). Finally, we check the effectiveness of the developed operators by a validity test.

Decision-making in a dynamic task: effects of goal orientation on stocks and flows performance

2020 ◽  
Vol 14 (3) ◽  
pp. 695-713
Author(s):  
Feifei Yang ◽  
Jiaqi Huang ◽  
Xiao Feng ◽  
Miles M. Yang
Keyword(s):  
Decision Making ◽  
Goal Orientation ◽  
Theoretical Perspective ◽  
Least Square ◽  
Dynamic Decision Making ◽  
Content Type ◽  
Dynamic Task ◽  
Learning Goal ◽  
Stocks And Flows ◽  
The Impact

Purpose This paper aims to investigate the effects of goal orientation on understanding the dynamics of stocks and flows (SF). Design/methodology/approach The authors use the well-established department store task as the experimental task to evaluate people’s understanding of SF and implement a survey to assess different goal orientation levels. Ordinary least square is used to test the effects of goal orientations on the SF performance. Findings The findings suggest that learning goal orientation is positively associated with SF performance. However, prove and avoid performance goal orientation are unrelated to SF performance. Originality/value The study has important theoretical and practical contributions. From a theoretical perspective, the authors examine the impact of goal orientation in dynamic decision-making to advance the knowledge on the role of goal orientation. Practically, the research demonstrates that learning-goal-oriented people perform better in stock and flow tasks, suggesting that goal orientation is an important trait for recruiting organizational members whose work involves SF decision-making tasks.

Satisfaction Degree Based Interactive Decision Making under Hesitant Fuzzy Environment with Incomplete Weights

2014 ◽  
Vol 22 (04) ◽  
pp. 553-572 ◽  
Author(s):  
Huchang Liao ◽  
Zeshui Xu
Keyword(s):  
Decision Making ◽  
Hesitant Fuzzy Set ◽  
Optimization Models ◽  
Multi Criteria Decision Making ◽  
Ideal Solution ◽  
Fuzzy Information ◽  
Satisfaction Degree ◽  
Interactive Decision Making ◽  
New Research ◽  
Topsis Technique

Multi-criteria decision making with hesitant fuzzy information is a new research topic since the hesitant fuzzy set was firstly proposed. This paper investigates a multi-criteria decision making problem where the weight information is partially known. We firstly propose the hesitant fuzzy positive ideal solution and the hesitant fuzzy negative ideal solution. Motivated by the TOPSIS (Technique for Order Preference by Similarity to an ideal Solution) method, we definite the satisfaction degree of an alternative, based on which several optimization models are derived to determinate the weights. Subsequently, in order to make a more reasonable decision, we introduce an interactive method based on some optimization models for multi-criteria decision making problems with hesitant fuzzy information. Finally, a practical example on evaluating the service quality of airlines is provided to illustrate our models and method.

Pythagorean Hesitant Fuzzy Information Aggregation and Their Application to Multi-Attribute Group Decision-Making Problems

2018 ◽  
Vol 29 (1) ◽  
pp. 154-171 ◽  
Author(s):  
Muhammad Sajjad Ali Khan ◽  
Saleem Abdullah ◽  
Asad Ali ◽  
Khaista Rahman
Keyword(s):  
Decision Making ◽  
Fuzzy Set ◽  
Group Decision ◽  
Information Aggregation ◽  
Weighted Averaging ◽  
Hesitant Fuzzy Set ◽  
Fuzzy Information ◽  
New Approach ◽  
Fuzzy Environment ◽  
Multidimensional Evaluation

Abstract In this paper, we introduce the concept of the Pythagorean hesitant fuzzy set (PHFS), which is the generalization of the intuitionistic hesitant fuzzy set under the restriction that the square sum of its membership degrees is ≤1. In decision making with PHFSs, aggregation operators play a key role because they can be used to synthesize multidimensional evaluation values represented as Pythagorean hesitant fuzzy values into collective values. Under PHFS environments, Pythagorean hesitant fuzzy ordered weighted averaging and Pythagorean fuzzy ordered weighted geometric operators are used to aggregate the Pythagorean hesitant fuzzy values. The main advantage of these operators is that they provide more accurate and valuable results. Furthermore, these operators are applied to decision-making problems in which experts provide their preferences in the Pythagorean hesitant fuzzy environment to show the validity, practicality, and effectiveness of the new approach. Finally, we compare the proposed approach to the existing methods.

scholarly journals SELECTING THE OPTIMAL RENEWABLE ENERGY USING MULTI CRITERIA DECISION MAKING

2013 ◽  
Vol 14 (5) ◽  
pp. 957-978 ◽  
Author(s):  
Abdolreza Yazdani-Chamzini ◽  
Mohammad Majid Fouladgar ◽  
Edmundas Kazimieras Zavadskas ◽  
S. Hamzeh Haji Moini
Keyword(s):  
Decision Making ◽  
Renewable Energy ◽  
Evaluation Criteria ◽  
Energy Resources ◽  
Multi Criteria Decision Making ◽  
Ideal Solution ◽  
Proposed Model ◽  
Negative Ideal Solution ◽  
Hierarchy Process ◽  
The Ideal

Renewable energies are well-known as one of the most important energy resources not only due to limited other energy resources, but also due to environmental problems associated with air pollutants and greenhouse gas emissions. Renewable energy project selection is a multi actors and sophisticated problem because it is a need to incorporate social, economic, technological, and environmental considerations. Multi criteria decision making (MCDM) methods are powerful tools to evaluate and rank the alternatives among a pool of alternatives and select the best one. COPRAS (COmplex PRoportional ASsessment) is an MCDM technique which determines the best alternative by calculating the ratio to the ideal solution and the negative ideal solution. On the other hand, analytical hierarchy process (AHP) is widely used in order to calculate the importance weights of evaluation criteria. In this paper an integrated COPRAS-AHP methodology is proposed to select the best renewable energy project. In order to validate the output of the proposed model, the model is compared with five MCDM tools. The results of this paper demonstrate the capability and effectiveness of the proposed model in selecting the most appropriate renewable energy option among the existing alternatives.

scholarly journals Sistem Pendukung Keputusan Untuk Menentukan Prestasi Akademik Siswa dengan Metode TOPSIS

2015 ◽  
Vol 2 (2) ◽  
pp. 153
Author(s):  
Amelia Nur Fitriana ◽  
Harliana Harliana ◽  
Handaru Handaru
Keyword(s):  
Academic Achievement ◽  
Decision Making ◽  
Student Learning ◽  
Ideal Solution ◽  
Topsis Method ◽  
Learning Outcomes Assessment ◽  
Average Value ◽  
Relative Preference ◽  
Utilization Data ◽  
Negative Ideal Solution

Pengambilan keputusan pada suatu lembaga/sekolah merupakan hal yang sangat penting. Kepala sekolah seharusnya mengambil sebuah keputusan berdasarkan perhitungan dan pemikiran jangka panjang agar keputusan menentukan prestasi akademik siswa yang akan diambil tidak salah. Di MA Darul Masholeh masih terdapat masalah dalam membuat laporan pembelajaran siswa, untuk menentukan siswa yang berprestasi hanya ditentukan menggunakan nilai rapot, belum adanya pemanfaatan secara optimal data laporan penilaian hasil belajar siswa, masih adanya kesulitan untuk mengetahui pencapaian dari kegiatan pembelajaran siswa. Dengan menggunakan metode TOPSIS dapat mempermudah guru untuk menentukan prestasi akademik siswasecara tepat dan cepat, dimana metode topsis adalah salah satu metode pengambilan keputusan dimana alternative yang terpilih merupakan alternatif terbaik yang mempunyai jarak terdekat dari solusi ideal positif dan terjauh dari solusi ideal negatif. Dari pengujian 20 alternative dengan 6 kriteria yaitu hafalan al-qur’an, nilai rata-rata rapot, absensi, nilai minimal, total nilai dan piagam prestasi. Dari 20 alternative di dapatkan siswa yang berprestasi yaitu diurutan pertama Wildan dengan nilai preferensi relative 0,66, Kedua Ratna (0,64), ketiga Sinta (0,55), keempat Rini (0,50), Kelima Faisal (0,38) dan terakhir Sadriyah dengan nilai preferensi relative (0,00).Decision-making in an institution/school is very important. School principals should take a decision based on the calculation and long-term thinking in order to decide on the academic achievement of students who will be taken not wrong. In MA Darul Masholeh there is still a problem in reporting student learning, to determine student achievement is only determined using rapot value, the lack of optimal utilization data reporting student learning outcomes assessment, there is still difficult to determine the achievement of student learning activities. By using TOPSIS method can simplify the teacher to determine academic achievement siswasecara precise and fast, which TOPSIS method is one method of decision-making in which the chosen alternative is the best alternative that has the shortest distance from the positive ideal solution and the farthest from the negative ideal solution. Of the 20 alternative testing with 6 criteria that memorizing the Qur'an, the average value rapot, absenteeism, minimum value, the total value and charter achievement. Of the 20 alternative in getting students who excel are listed first Wildfire with relative preference value of 0.66, the Second Ratna (0.64), third Sprott (0.55), fourth Rini (0.50), the Fifth Faisal (0.38) and the last Sadriyah with relative preference value (0.00).

scholarly journals Comparison of the Economic Performance of Turkish Republics in Central Asia with TOPSIS Method

2015 ◽  
Author(s):  
Ziya Gökalp Göktolga ◽  
Engin Karakış ◽  
Hakan Türkay
Keyword(s):  
Decision Making ◽  
Central Asia ◽  
Economic Performance ◽  
Multi Criteria Decision Making ◽  
Ideal Solution ◽  
Topsis Method ◽  
Economic Management ◽  
Macroeconomic Indicators ◽  
Order Preference ◽  
Negative Ideal Solution

The aim of this study is to compare the economic performance of Turkish Republics in Central Asia with Multi Criteria Decision Making (MCDM) methods. Turkish Republics have been experiencing a transition from a centrally planned economy towards a market economy since their independence. In this study important macroeconomic indicators are used to determine economic performance. Economic performance evaluation of the country is an important issue for economic management, investors, creditors and stock investors. Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method outranks the countries according to the proximity of the positive ideal solution and distance of the negative ideal solution. Economic Performance of Turkish Republics in Central Asia (Azerbaijan, Turkmenistan, Kazakhstan, Kyrgyzstan, and Uzbekistan) are compared with TOPSIS method. İnvestigated with TOPSIS method countries best and worst economic performance years are detected during mentioned period and results are analyzed.

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