scholarly journals PRIORITIZING THE WEIGHTS OF THE EVALUATION CRITERIA UNDER FUZZINESS: THE FUZZY FULL CONSISTENCY METHOD – FUCOM-F

2020 ◽  
Vol 18 (3) ◽  
pp. 419
Author(s):  
Dragan Pamucar ◽  
Fatih Ecer
Keyword(s):  
Fuzzy Ahp ◽  
Evaluation Criteria ◽  
Real Life ◽  
Fuzzy Model ◽  
Complete Information ◽  
Sources Of Information ◽  
Weighting Method ◽  
Life Problems ◽  
Criteria Weights ◽  
Consistency Method

Values, opinions, perceptions, and experiences are the forces that drive almost each and every kind of decision-making. Evaluation criteria are considered as sources of information used to compare alternatives and, as a result, make selection easier. Seeing their direct effect on the solution, weighting methods that most accurately determine criteria weights are needed. Unfortunately, the crisp values are insufficient to model real life problems due to the lack of complete information and the vagueness arising from linguistic assessments of decision-makers. Therefore, this paper proposes a novel subjective weighting method called the Fuzzy Full Consistency Method (FUCOM-F) for determining weights as accurately as possible under fuzziness. The most prominent feature of the proposed method is obtaining the most accurate weight values with very few pairwise comparisons. Consequently, thanks to this model, consistency and reliability of the results increase while the processing time and effort decrease. Moreover, an illustrative example related to the green supplier evaluation problem is performed. Finally, the robustness and effectiveness of the proposed fuzzy model is demonstrated by comparing it with fuzzy best-worst method (F-BWM) and fuzzy AHP (F-AHP) models.

scholarly journals AN INTEGRATED FUZZY MULTI CRITERIA GROUP DECISION MAKING MODEL FOR HANDLING EQUIPMENT SELECTION

2014 ◽  
Vol 20 (5) ◽  
pp. 660-673 ◽  
Author(s):  
Abdolreza Yazdani-Chamzini
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Fuzzy Ahp ◽  
Evaluation Model ◽  
Evaluation Criteria ◽  
Fuzzy Topsis ◽  
Equipment Selection ◽  
Order Preference ◽  
Criteria Weights

The problem of handling equipment selection plays a significant role in the total cost of a mining project; so that it can affect the activity and continuity of the project and is a strategic problem. In this study, an integrated model based on two fuzzy multi-criteria decision making techniques for handling equipment selection is proposed. The proposed evaluation model is derived from group decision making, fuzzy set theory, analytical hierarchy process (AHP), and Technique to Order Preference by Similarity to Ideal Solution (TOPSIS) methods. The fuzzy AHP (FAHP) method is utilized to calculate the relative importance of the evaluation criteria, then, fuzzy TOPSIS (FTOPSIS) is applied for evaluating the feasible handling equipment in order to select the best handling system among a pool of the possible alternatives. The model is applied for a real world case study to demonstrate the capability and effectiveness of the proposed model. To investigate the result sensitiveness to the changes of the criteria weights, a sensitivity analysis is finally conducted.

scholarly journals A Hybrid MCDM Technique for Risk Management in Construction Projects

2017 ◽  
Author(s):  
Kajal Chatterjee ◽  
Edmundas Kazimieras Zavadskas ◽  
Jolanta Tamošaitienė ◽  
Krishnendu Adhikary ◽  
Samarjit Kar
Keyword(s):  
Construction Projects ◽  
Risk Mitigation ◽  
Preference Relation ◽  
Real Life ◽  
Mitigation Strategies ◽  
Response Strategy ◽  
Decision Matrix ◽  
Life Problems ◽  
Criteria Weights ◽  
Project Risks

Multi-stakeholder based construction projects are subject to various risk factors due to dynamic business environments. These risks affect project activities which indirectly impact construction costs, resulting in delays and poor building quality. So, managing these project risks requires suitable risk mitigation strategies to evaluate and analyse their severity. Hence, risk evaluation and assessment of construction projects is a multi-criteria decision making (MCDM) problem. In present real-life problems, evaluation of project risks is often uncertain and even incomplete, and the prevailing methodologies fail to handle such situations. To address the problem, this paper extends the analytical network process (ANP) methodology in the D number domain to handle three types of ambiguous evaluations, viz. complete, uncertain, and incomplete, and assesses the weight of risk criteria. The D number based approach overcomes the deficiencies of the exclusiveness hypothesis and completeness constraint of Dempster-Shafer (D-S) theory. Here, preference ratings of the decision matrix for each decision-maker are determined using a D number extended consistent fuzzy preference relation (D-CFPR). An extended multi-attributive border approximation area comparison (MABAC) method in D number is then developed to rank and select the best alternative risk response strategy. Finally, an illustrative example from construction sector is presented to check the feasibility of the proposed approach. For checking the reliability of alternative ranking, a comparative analysis is performed with different MCDM approaches (D-COPRAS, D-ARAS, D-MABAC, and D-TOPSIS). Based on different criteria weights, a sensitivity analysis of obtained ranking of the hybrid D-ANP-MABAC model is performed for verify the robustness of the proposed method.

scholarly journals Model for Selection of the Best Location Based on Fuzzy AHP and Hurwitz Methods

2017 ◽  
Vol 2017 ◽  
pp. 1-12 ◽  
Author(s):  
Slavko Arsovski ◽  
Gordana Todorovic ◽  
Zorica Lazić ◽  
Zora Arsovski ◽  
Nikolina Ljepava ◽  
...  
Keyword(s):  
Urban Areas ◽  
Fuzzy Ahp ◽  
Evaluation Criteria ◽  
Real Life ◽  
Time Period ◽  
Real Life Data ◽  
Proposed Model ◽  
Long Time ◽  
Selection Of

The problem of evaluation and selection of parking lots is a part of significant issues of public transport management in cities. As population expands as well as urban areas, solving the mentioned issues affects employees, security and safety of citizens, and quality of life in long-time period. The aim of this paper is to propose a multicriteria decision model which includes both quantitative and qualitative criteria, which may be of either benefit or cost type, to evaluate locations. The criteria values and the importance of criteria are either precise or linguistic expressions defined by trapezoidal fuzzy numbers. The human judgments of the relative importance of evaluation criteria and uncertain criteria values are often vague and cannot be expressed by exact precise values. The ranking of locations with respect to all criteria and their weights is performed for various degrees of pessimistic-optimistic index. The proposed model is tested through an illustrative example with real life data, where it shows the practical implications in public communal enterprises.

scholarly journals A NEW MULTIMODAL MULTI-CRITERIA ROUTE PLANNING MODEL BY INTEGRATING A FUZZY-AHP WEIGHTING METHOD AND A SIMULATED ANNEALING ALGORITHM

2015 ◽  
Vol XL-1-W5 ◽  
pp. 203-209 ◽  
Author(s):  
F. Ghaderi ◽  
P. Pahlavani
Keyword(s):  
Simulated Annealing Algorithm ◽  
High Efficiency ◽  
Fuzzy Ahp ◽  
Route Planning ◽  
Pairwise Comparison ◽  
Weighting Method ◽  
Public And Private ◽  
Transportation Modes ◽  
Criteria Weights ◽  
Matlab Programming

A multimodal multi-criteria route planning (MMRP) system provides an optimal multimodal route from an origin point to a destination point considering two or more criteria in a way this route can be a combination of public and private transportation modes. In this paper, the simulate annealing (SA) and the fuzzy analytical hierarchy process (fuzzy AHP) were combined in order to find this route. In this regard, firstly, the effective criteria that are significant for users in their trip were determined. Then the weight of each criterion was calculated using the fuzzy AHP weighting method. The most important characteristic of this weighting method is the use of fuzzy numbers that aids the users to consider their uncertainty in pairwise comparison of criteria. After determining the criteria weights, the proposed SA algorithm were used for determining an optimal route from an origin to a destination. One of the most important problems in a meta-heuristic algorithm is trapping in local minima. In this study, five transportation modes, including subway, bus rapid transit (BRT), taxi, walking, and bus were considered for moving between nodes. Also, the fare, the time, the user’s bother, and the length of the path were considered as effective criteria for solving the problem. The proposed model was implemented in an area in centre of Tehran in a GUI MATLAB programming language. The results showed a high efficiency and speed of the proposed algorithm that support our analyses.

The Psychologist in the Medical School: An Example of Solving Real-Life Problems

1970 ◽  
Author(s):  
Matisyohu Weisenberg ◽  
Carl Eisdorfer ◽  
C. Richard Fletcher ◽  
Murray Wexler
Keyword(s):  
Medical School ◽  
Real Life ◽  
Life Problems

scholarly journals AnANN Model Trained on Regional Data in the Prediction of Particular Weather Conditions

2021 ◽  
Vol 11 (11) ◽  
pp. 4757
Author(s):  
Aleksandra Bączkiewicz ◽  
Jarosław Wątróbski ◽  
Wojciech Sałabun ◽  
Joanna Kołodziejczyk
Keyword(s):  
Atmospheric Pressure ◽  
Real Life ◽  
Real Data ◽  
Weather Conditions ◽  
Maximum Temperature ◽  
Air Masses ◽  
Weather Forecasts ◽  
Life Problems ◽  
The World ◽  
The City

Artificial Neural Networks (ANNs) have proven to be a powerful tool for solving a wide variety of real-life problems. The possibility of using them for forecasting phenomena occurring in nature, especially weather indicators, has been widely discussed. However, the various areas of the world differ in terms of their difficulty and ability in preparing accurate weather forecasts. Poland lies in a zone with a moderate transition climate, which is characterized by seasonality and the inflow of many types of air masses from different directions, which, combined with the compound terrain, causes climate variability and makes it difficult to accurately predict the weather. For this reason, it is necessary to adapt the model to the prediction of weather conditions and verify its effectiveness on real data. The principal aim of this study is to present the use of a regressive model based on a unidirectional multilayer neural network, also called a Multilayer Perceptron (MLP), to predict selected weather indicators for the city of Szczecin in Poland. The forecast of the model we implemented was effective in determining the daily parameters at 96% compliance with the actual measurements for the prediction of the minimum and maximum temperature for the next day and 83.27% for the prediction of atmospheric pressure.

scholarly journals Formulating Modes of Cooperative Leaning for Education for Sustainable Development

2021 ◽  
Vol 13 (6) ◽  
pp. 3465
Author(s):  
Jordi Colomer ◽  
Dolors Cañabate ◽  
Brigita Stanikūnienė ◽  
Remigijus Bubnys
Keyword(s):  
Sustainable Development ◽  
Real Life ◽  
Education For Sustainable Development ◽  
Professional Life ◽  
Global Challenges ◽  
Life Problems ◽  
The Face ◽  
Contemporary Education ◽  
The Impact

In the face of today’s global challenges, the practice and theory of contemporary education inevitably focuses on developing the competences that help individuals to find meaningfulness in their societal and professional life, to understand the impact of local actions on global processes and to enable them to solve real-life problems [...]

scholarly journals Derivative-Free King’s Scheme for Multiple Zeros of Nonlinear Functions

Mathematics ◽  
2021 ◽  
Vol 9 (11) ◽  
pp. 1242
Author(s):  
Ramandeep Behl ◽  
Sonia Bhalla ◽  
Eulalia Martínez ◽  
Majed Aali Alsulami
Keyword(s):  
Iterative Methods ◽  
Fourth Order ◽  
Order Of Convergence ◽  
Real Life ◽  
Multiple Roots ◽  
Computational Results ◽  
Nonlinear Functions ◽  
First Order ◽  
Life Problems ◽  
Derivative Free

There is no doubt that the fourth-order King’s family is one of the important ones among its counterparts. However, it has two major problems: the first one is the calculation of the first-order derivative; secondly, it has a linear order of convergence in the case of multiple roots. In order to improve these complications, we suggested a new King’s family of iterative methods. The main features of our scheme are the optimal convergence order, being free from derivatives, and working for multiple roots (m≥2). In addition, we proposed a main theorem that illustrated the fourth order of convergence. It also satisfied the optimal Kung–Traub conjecture of iterative methods without memory. We compared our scheme with the latest iterative methods of the same order of convergence on several real-life problems. In accordance with the computational results, we concluded that our method showed superior behavior compared to the existing methods.

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