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Search Results (5)

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Keywords = ELECTRE-I

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33 pages, 412 KB  
Article
Multi-Attribute Decision-Making Based on m-Polar Fuzzy Hamacher Aggregation Operators
by Neha Waseem, Muhammad Akram and José Carlos R. Alcantud
Symmetry 2019, 11(12), 1498; https://doi.org/10.3390/sym11121498 - 10 Dec 2019
Cited by 58 | Viewed by 4726
Abstract
In this paper, we introduce certain aggregation operators, namely, the m-polar fuzzy (mF) Hamacher weighted average operator, mF Hamacher ordered weighted average (mFHOWA) operator, mF Hamacher hybrid average (mFHHA) operator, mF Hamacher weighted [...] Read more.
In this paper, we introduce certain aggregation operators, namely, the m-polar fuzzy (mF) Hamacher weighted average operator, mF Hamacher ordered weighted average (mFHOWA) operator, mF Hamacher hybrid average (mFHHA) operator, mF Hamacher weighted geometric (mFHWG) operator, mF Hamacher weighted ordered geometric operator, and mF Hamacher hybrid geometric (mFHHG) operator. We discuss some properties of these operators, inclusive of their ability to implement both symmetric and asymmetric treatments of the items. We develop an algorithmic model to solve multi-attribute decision-making (MADM) problems in mF environment using mF Hamacher weighted average operator (mFHWA) and mFHWG operators. They can compensate for the possible asymmetric roles of the attributes that describe the problem. In the end, to prove the validity and feasibility of the proposed work, we give applications for selecting the most affected country regarding human trafficking, selecting health care waste treatment methods and selecting the best company for investment. We also solve practical MADM problems by using ELECTRE-I method, and give a comparative analysis. Full article
(This article belongs to the Special Issue Multi-Criteria Decision Aid methods in fuzzy decision problems – part II)
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20 pages, 329 KB  
Article
Group Decision-Making Based on m-Polar Fuzzy Linguistic TOPSIS Method
by Arooj Adeel, Muhammad Akram and Ali N. A. Koam
Symmetry 2019, 11(6), 735; https://doi.org/10.3390/sym11060735 - 29 May 2019
Cited by 71 | Viewed by 3872
Abstract
The fuzzy linguistic approach provides favorable outputs in several areas, whose description is relatively qualitative. The encouragement for the utilization of sentences or words instead of numbers is that linguistic characterizations or classifications are usually less absolute than algebraic or arithmetical ones. In [...] Read more.
The fuzzy linguistic approach provides favorable outputs in several areas, whose description is relatively qualitative. The encouragement for the utilization of sentences or words instead of numbers is that linguistic characterizations or classifications are usually less absolute than algebraic or arithmetical ones. In this research article, we animate the m-polar fuzzy (mF) linguistic approach and elaborate it with real life examples and tabular representation to develop the affluence of linguistic variables based on mF approach. As an extension of the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method, we develop an m-polar fuzzy linguistic TOPSIS approach for multi-criteria group decision-making (MCGDM). It is used to evaluate the best alternative, to get more authentic and comparable results and to handle the real life problems of having multi-polar information in terms of linguistic variables and values. In this approach decision-makers contribute their estimations in the form of linguistic term sets. To show the efficiency and compatibility of the proposed approach, we compare it with the m-polar fuzzy linguistic ELECTRE-I (Elimination and Choice Translating Reality) approach. Finally, we draw a flow chart of our proposed approach as an algorithm and generate a computer programming code. Full article
(This article belongs to the Special Issue Multi-Criteria Decision Aid methods in fuzzy decision problems)
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30 pages, 403 KB  
Article
Multi-Criteria Decision-Making under mHF ELECTRE-I and HmF ELECTRE-I
by Arooj Adeel, Muhammad Akram and Ali N.A. Koam
Energies 2019, 12(9), 1661; https://doi.org/10.3390/en12091661 - 1 May 2019
Cited by 28 | Viewed by 3721
Abstract
In a few years, hesitant fuzzy sets (HFSs) have had an impact on several different areas of decision science. However, a number of researches have utilized the Elimination and choice translating reality (ELECTRE) methods to determine the multi-criteria decision-making (MCDM) problems with hesitant [...] Read more.
In a few years, hesitant fuzzy sets (HFSs) have had an impact on several different areas of decision science. However, a number of researches have utilized the Elimination and choice translating reality (ELECTRE) methods to determine the multi-criteria decision-making (MCDM) problems with hesitant information. The aim of this research article is to develop new multi-criteria group decision-making (MCGDM) methods, such as the m-polar hesitant fuzzy ELECTRE-I (mHF ELECTRE-I) method and hesitant m-polar fuzzy ELECTRE-I (HmF ELECTRE-I) method. Proposed MCGDM techniques based on the hybrid models, m-polar hesitant fuzzy sets (mHFS-sets) and hesitant m-polar fuzzy sets (HmF-sets), which are the natural generalizations of HFSs and m-polar fuzzy sets (mF sets). These models enable us to deal with multipolar information under hesitancy. We use the proposed methods to deal the complex problems in which the membership degree of an element of given set uses the m different numeric and fuzzy values, to rank all the alternatives and to determine the best alternative. We present two practical examples that illustrate the procedure of the proposed methods. We also discuss the differences and comparative analysis of the proposed methods. Finally, we develop an algorithm that implements our decision-making procedures by using computer programming. Full article
(This article belongs to the Special Issue Adaptive Fuzzy Control)
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26 pages, 390 KB  
Article
Novel m—Polar Fuzzy Linguistic ELECTRE-I Method for Group Decision-Making
by Arooj Adeel, Muhammad Akram, Imran Ahmed and Kashif Nazar
Symmetry 2019, 11(4), 471; https://doi.org/10.3390/sym11040471 - 2 Apr 2019
Cited by 38 | Viewed by 4453
Abstract
Linguistic variables play a vital role in several qualitative decision environments, in which decision-makers assume several feasible linguistic values or criteria instead of a single term for an alternative or variable. The motivation for the use of words or sentences instead of numbers [...] Read more.
Linguistic variables play a vital role in several qualitative decision environments, in which decision-makers assume several feasible linguistic values or criteria instead of a single term for an alternative or variable. The motivation for the use of words or sentences instead of numbers is that linguistic classification and characterizations are generally less precise than numerical ones. In this research article, we encourage the fuzzy linguistic approach and introduce the novel concept known as m-polar fuzzy linguistic variable (mFLV) to increase the affluence of linguistic variables based on m-polar fuzzy (mF) approach. An mF set is an effective concept for interpreting uncertainty and fuzziness. The concept of mFLV is more versatile and sensible for dealing with real-life problems, when data comes from qualitative and multipolar information. We also introduce an mF linguistic ELECTRE-I approach to solve multiple-criteria decision-making (MCDM) and multiple-criteria group decision-making (MCGDM) problems, where the evaluation of the alternatives under suitable linguistic values are determined by the decision-makers. Furthermore, we validate the efficiency of our proposed technique by applying it to real-life examples, such as the salary analysis of companies and by selecting a corrupt country. Finally, we develop an algorithm of our proposed approach, present its flow chart, and generate computer programming code. Full article
(This article belongs to the Special Issue Multi-Criteria Decision Aid methods in fuzzy decision problems)
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17 pages, 407 KB  
Article
Decision-Making with Bipolar Neutrosophic TOPSIS and Bipolar Neutrosophic ELECTRE-I
by Muhammad Akram, Shumaiza and Florentin Smarandache
Axioms 2018, 7(2), 33; https://doi.org/10.3390/axioms7020033 - 15 May 2018
Cited by 69 | Viewed by 5711
Abstract
Technique for the order of preference by similarity to ideal solution (TOPSIS) and elimination and choice translating reality (ELECTRE) are widely used methods to solve multi-criteria decision making problems. In this research article, we present bipolar neutrosophic TOPSIS method and bipolar neutrosophic ELECTRE-I [...] Read more.
Technique for the order of preference by similarity to ideal solution (TOPSIS) and elimination and choice translating reality (ELECTRE) are widely used methods to solve multi-criteria decision making problems. In this research article, we present bipolar neutrosophic TOPSIS method and bipolar neutrosophic ELECTRE-I method to solve such problems. We use the revised closeness degree to rank the alternatives in our bipolar neutrosophic TOPSIS method. We describe bipolar neutrosophic TOPSIS method and bipolar neutrosophic ELECTRE-I method by flow charts. We solve numerical examples by proposed methods. We also give a comparison of these methods. Full article
(This article belongs to the Special Issue Neutrosophic Multi-Criteria Decision Making)
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