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Keywords = multi-attribute decision making (MADM)

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24 pages, 2906 KiB  
Article
Spontaneous Symmetry Breaking in Group Decision-Making with Complex Polytopic Fuzzy System
by Muhammad Bilal
Symmetry 2025, 17(1), 34; https://doi.org/10.3390/sym17010034 - 27 Dec 2024
Viewed by 455
Abstract
Beginning with a symmetrical multiple-choice individual as the foundation, I develop a sociophysics model of decision-making. By simplifying the range of choices, the framework incorporates the complex Polytopic fuzzy model to capture nuanced dynamics. This approach enables a deeper analysis of decision-making processes [...] Read more.
Beginning with a symmetrical multiple-choice individual as the foundation, I develop a sociophysics model of decision-making. By simplifying the range of choices, the framework incorporates the complex Polytopic fuzzy model to capture nuanced dynamics. This approach enables a deeper analysis of decision-making processes within social systems. Decision-making problems commonly involve uncertainty and complexity, posing considerable challenges for organizations and individuals. Due to their structure and variable parameters, the Einstein t-norm (ETN) and t-conorm (ETCN) offer more elasticity than the algebraic t-norm (ATN) and t-conorm (ATCN). This flexibility makes them commonly effective and valuable in fuzzy multi-attribute decision-making (MADM) problems, where nuanced valuations are critical. Their application enhances the ability to model and analyze vagueness and uncertain information, eventually leading to more informed decision outcomes. The complex Polytopic fuzzy set (CPFS) improves the Polytopic fuzzy set (PFS) and complex fuzzy set (CPFS), allowing for a more precise valuation of attributes in complex (MADM) problems. This study aims to propose a MADM scheme using the ETN and ETCN within the framework of a complex Polytopic fuzzy environment. It begins by presenting the Einstein product and sum operations for complex Polytopic fuzzy numbers (CPFNs) and explores their necessary properties. This method enhances the accuracy and applicability of DM processes in ambiguous environments. Subsequently, three complex Polytopic fuzzy operators with known weighted vectors are developed: the complex Polytopic fuzzy Einstein weighted averaging (CPFEWA) operator, complex Polytopic fuzzy Einstein ordered weighted averaging (CPFEOWA) operator, complex Polytopic fuzzy Einstein hybrid averaging (CPFEHA) operator. Moreover, some substantial properties of the operators are studied. Finally, a method based on novel operators is planned, and a numerical example is provided to prove the practicality and effectiveness of the new proposed methods. Full article
(This article belongs to the Special Issue Recent Developments on Fuzzy Sets Extensions)
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24 pages, 569 KiB  
Article
Enhancing the Aczel–Alsina Model: Integrating Hesitant Fuzzy Logic with Chi-Square Distance for Complex Decision-Making
by Jianming Xie, Chunfang Chen, Jing Wan and Qiuxian Dong
Symmetry 2024, 16(12), 1702; https://doi.org/10.3390/sym16121702 - 22 Dec 2024
Viewed by 438
Abstract
The paper presents an innovative method for tackling multi-attribute decision-making (MADM) problems within a hesitant fuzzy (HF) framework. Initially, the paper generalizes the Chi-square distance measure to the hesitant fuzzy context, defining the HF generalized Chi-square distance. Following this, the paper introduces the [...] Read more.
The paper presents an innovative method for tackling multi-attribute decision-making (MADM) problems within a hesitant fuzzy (HF) framework. Initially, the paper generalizes the Chi-square distance measure to the hesitant fuzzy context, defining the HF generalized Chi-square distance. Following this, the paper introduces the power average (P-A) operator and the power geometric (P-G) operator to refine the weights derived from Shannon entropy, taking into account the inter-attribute support. Leveraging the strengths of Aczel–Alsina operations and the power operation, the paper proposes the hesitant fuzzy Aczel–Alsina power weighted average (HFAAPWA) operator and the hesitant fuzzy Aczel–Alsina power weighted geometric (HFAAPWG) operator. Consequently, a hesitant fuzzy Aczel–Alsina power model is constructed. The applicability of this model is demonstrated through a case study examining the urban impacts of cyclonic storm Amphan, and the model’s superiority is highlighted through comparative analysis. Full article
(This article belongs to the Section Mathematics)
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27 pages, 680 KiB  
Article
A Hesitation-Associated Multi-Attribute Decision-Making Method Based on Generalized Interval-Valued Hesitation Fuzzy Weighted Heronian Averaging Operator
by Jiayou Shen, Nan Yang and Hejun Liang
Mathematics 2024, 12(23), 3857; https://doi.org/10.3390/math12233857 - 7 Dec 2024
Viewed by 664
Abstract
In multi-attribute decision making (MADM), complex situations often arise where decision attributes are interval-valued hesitant fuzzy numbers (IVHFNs) and the attributes are interrelated. Traditional decision-making methods may be ineffective in handling such cases, highlighting the practical importance of seeking more effective approaches. Therefore, [...] Read more.
In multi-attribute decision making (MADM), complex situations often arise where decision attributes are interval-valued hesitant fuzzy numbers (IVHFNs) and the attributes are interrelated. Traditional decision-making methods may be ineffective in handling such cases, highlighting the practical importance of seeking more effective approaches. Therefore, finding a more effective decision-making approach has important practical significance. By combining the theories of Archimedean S-norms and T-norms, we innovatively propose a multi-attribute decision-making method based on the generalized interval-valued hesitant fuzzy weighted Heronian mean (GIVHFWHM) operator to address the aforementioned issues. Initially, based on the operational laws of IVHFNs and the Heronian mean (HM) operator, we introduce the generalized interval-valued hesitant fuzzy Heronian mean (GIVHFHM) operator and the GIVHFWHM operator. We then examine properties of the GIVHFHM operator, including permutation invariance, idempotency, monotonicity, boundedness, and parameter symmetry. A multi-attribute decision-making model is constructed based on the GIVHFWHM operator. Finally, we validate the proposed model through numerical experiments in MADM. The results demonstrate that the new decision-making method, based on the GIVHFWHM operator, is feasible and effective in handling multi-attribute decision problems involving IVHFNs with interdependent attributes. This approach provides a novel perspective and method for solving MADM problems under interval-valued hesitant fuzzy conditions with interdependent attributes. It enriches the theoretical framework of multi-attribute hesitant decision models and expands the application of the Heronian mean operator within interval-valued hesitant fuzzy environments. This methodology assists decision makers in making more accurate decisions within complex decision-making contexts, enhancing both the scientific rigor and reliability of decision-making processes. Full article
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44 pages, 8746 KiB  
Article
Advanced Integration of ES-MADM II in HRM: A Balanced Approach to Appraisal and Promotion Decisions
by Sideris Kiratsoudis and Vassilis Tsiantos
Information 2024, 15(12), 767; https://doi.org/10.3390/info15120767 - 2 Dec 2024
Viewed by 487
Abstract
Personnel appraisal and promotion are fundamental processes in Human Resource Management (HRM), requiring advanced methodologies that adeptly combine objective data with subjective assessments. This paper introduces ES-MADM II, an enhanced iteration of the Entropy Synergy Multi-Attribute Decision-Making model, designed to strengthen decision-making robustness [...] Read more.
Personnel appraisal and promotion are fundamental processes in Human Resource Management (HRM), requiring advanced methodologies that adeptly combine objective data with subjective assessments. This paper introduces ES-MADM II, an enhanced iteration of the Entropy Synergy Multi-Attribute Decision-Making model, designed to strengthen decision-making robustness and stability. The model incorporates key entropy-based indices such as Normalized Mutual Information (NMI), Criteria Effectiveness Score (CES), Conditional Stability Factor (CSF), and the newly introduced Alternatives Distinction Index (ADI). Together, these indices offer a comprehensive framework for assessing not only decision accuracy but also the overall resilience and clarity of the evaluation process. The effectiveness of ES-MADM II is showcased through military HRM case studies, illustrating how the model enhances personnel performance appraisals and promotion decisions by harmonizing subjective judgments with objective metrics. A detailed sensitivity analysis further demonstrates the model’s adaptability to variations in input data while preserving decision integrity. ES-MADM II ultimately fosters a more transparent, balanced, and equitable decision-making process, making it an indispensable tool for HR decision makers in complex organizational settings. This refined approach underscores the model’s capacity to navigate the complexities of HR evaluations with rigor and fairness. Full article
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31 pages, 753 KiB  
Article
Divergence and Similarity Characteristics for Two Fuzzy Measures Based on Associated Probabilities
by Gia Sirbiladze, Bidzina Midodashvili and Teimuraz Manjafarashvili
Viewed by 803
Abstract
The article deals with the definitions of the distance, divergence, and similarity characteristics between two finite fuzzy measures, which are generalizations of the same definitions between two finite probability distributions. As is known, a fuzzy measure can be uniquely represented by the so-called [...] Read more.
The article deals with the definitions of the distance, divergence, and similarity characteristics between two finite fuzzy measures, which are generalizations of the same definitions between two finite probability distributions. As is known, a fuzzy measure can be uniquely represented by the so-called its associated probability class (APC). The idea of generalization is that new definitions of distance, divergence, and similarity between fuzzy measures are reduced to the definitions of distance, divergence, and similarity between the APCs of fuzzy measures. These definitions are based on the concept of distance generator. The proof of the correctness of generalizations is provided. Constructed distance, similarity, and divergence relations can be used in such applied problems as: determining the difference between Dempster-Shafer belief structures; Constructions of collaborative filtering similarity relations; non-additive and interactive parameters of machine learning in phase space metrics definition, object clustering, classification and other tasks. In this work, a new concept is used in the fuzzy measure identification problem for a certain multi-attribute decision-making (MADM) environment. For this, a conditional optimization problem with one objective function representing the distance, divergence or similarity index is formulated. Numerical examples are discussed and a comparative analysis of the obtained results is presented. Full article
(This article belongs to the Special Issue New Perspectives in Fuzzy Sets and Their Applications)
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15 pages, 343 KiB  
Article
Intuitionistic Fuzzy Ordinal Priority Approach with Grey Relational Analysis
by Priyanka Majumder and Valerio Antonio Pamplona Salomon
Mathematics 2024, 12(19), 3156; https://doi.org/10.3390/math12193156 - 9 Oct 2024
Cited by 2 | Viewed by 1090
Abstract
Multi-attribute decision-making (MADM) is a methodology for solving decision problems with a finite set of alternatives. The several methods of MADM require weights for the criteria and the alternatives to provide a solution. The Ordinal Priority Approach (OPA) is a recently proposed method [...] Read more.
Multi-attribute decision-making (MADM) is a methodology for solving decision problems with a finite set of alternatives. The several methods of MADM require weights for the criteria and the alternatives to provide a solution. The Ordinal Priority Approach (OPA) is a recently proposed method for MADM that innovates; it does not require these inputs, just the rankings of criteria and alternatives. This article introduces a new hybrid method for MADM: the Intuitionistic Fuzzy Ordinal Priority Approach with Grey Relational Analysis (OPA-IF-GRA). OPA-IF-GRA combines GRA with OPA-IF, a newer extension of OPA that includes intuitionistic fuzzy sets to incorporate uncertainty into the decision-making process. The article presents an OPA-IF-GRA application for solving an electronics engineering problem, considering four criteria and six alternatives. The solution of OPA-IF-GRA is compared with the solutions obtained with three other MADM methods. Full article
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19 pages, 321 KiB  
Article
Multi-Attribute Three-Way Decision Approach Based on Ideal Solutions under Interval-Valued Fuzzy Soft Environment
by Hongwu Qin, Yanyan Han and Xiuqin Ma
Symmetry 2024, 16(10), 1327; https://doi.org/10.3390/sym16101327 - 8 Oct 2024
Viewed by 711
Abstract
The interval-valued fuzzy soft set (IVFSS) model, which combines the benefits of the soft set model with the interval-valued fuzzy set (IVFS) model, is a growing and effective mathematical tool for processing hazy data. In detail, this model is characterized by symmetry, which [...] Read more.
The interval-valued fuzzy soft set (IVFSS) model, which combines the benefits of the soft set model with the interval-valued fuzzy set (IVFS) model, is a growing and effective mathematical tool for processing hazy data. In detail, this model is characterized by symmetry, which has the lower and upper membership degree. The study of decision-making based on IVFSS has picked up more steam recently. However, existing multi-attribute decision-making (MADM) methods can only sort alternative schemes, but are not able to classify them, which is detrimental to decision-makers’ efficient decision-making. In this paper, we propose a multi-attribute three-way decision-making (MATWDM) algorithm based on ideal solutions for IVFSS. MATWDM is extended to the IVFSS environment by incorporating the concept of the ideal solution, offering a more adaptable and comprehensive approach for addressing uncertain MADM issues. The method not only obtains the ranking results of the alternatives, but also divides them into acceptance domain, rejection domain, and delayed-decision domain, which makes the decision results more reasonable and effective, facilitating decision-makers to make better decisions. We apply the proposed three-way decision algorithm to two practical cases as diverse as mine emergency decision and Homestay selection decision. Additionally, the effectiveness and viability of the suggested method are confirmed by experimental findings. Full article
(This article belongs to the Section Computer)
20 pages, 5549 KiB  
Article
Optimal Configuration of Modular Strongrooms Using Multi-Attribute Decision Making
by Violeta Đorđević, Vladan Grković, Milan Kolarević, Branko Radičević and Mišo Bjelić
Appl. Sci. 2024, 14(19), 8961; https://doi.org/10.3390/app14198961 - 5 Oct 2024
Viewed by 687
Abstract
In this paper, we show that it is possible to obtain an optimal configuration variant of Modular Strongrooms (MSR) that satisfies the individual requirements of customers and is most economically advantageous for manufacturers. A model of the automatic configuration system for configuring MSR [...] Read more.
In this paper, we show that it is possible to obtain an optimal configuration variant of Modular Strongrooms (MSR) that satisfies the individual requirements of customers and is most economically advantageous for manufacturers. A model of the automatic configuration system for configuring MSR type MODULPRIM was developed, integrating the procedures for generating product variants, choosing the optimal configuration, and designing detailed products and technological processes. The developed model’s importance lies in its ability to automatically select the optimal configuration from a set of possible configurations on a multidisciplinary basis. The problem of choosing was solved by integrating the Analytic Hierarchy Process (AHP) and Simple Additive Weighting (SAW) methods from the group of Multi-Attribute Decision Making (MADM). Validation of the proposed model was performed on eight examples of Modular Strongrooms type MODULPRIM 5 and showed great opportunities to improve efficiency and effectiveness in the process of innovative product development, as well as to obtain a product configuration with significantly improved quality. The proposed model has a high degree of flexibility and universality; thus, it can be further upgraded and integrated into a company’s business system. Full article
(This article belongs to the Section Applied Industrial Technologies)
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16 pages, 1294 KiB  
Article
A Generalized Method for Deriving Steady-State Behavior of Consistent Fuzzy Priority for Interdependent Criteria
by Jih-Jeng Huang and Chin-Yi Chen
Mathematics 2024, 12(18), 2863; https://doi.org/10.3390/math12182863 - 14 Sep 2024
Viewed by 609
Abstract
Interdependent criteria play a crucial role in complex decision-making across various domains. Traditional methods often struggle to evaluate and prioritize criteria with intricate dependencies. This paper introduces a generalized method integrating the analytic network process (ANP), the decision-making trial and evaluation laboratory (DEMATEL), [...] Read more.
Interdependent criteria play a crucial role in complex decision-making across various domains. Traditional methods often struggle to evaluate and prioritize criteria with intricate dependencies. This paper introduces a generalized method integrating the analytic network process (ANP), the decision-making trial and evaluation laboratory (DEMATEL), and the consistent fuzzy analytic hierarchy process (CFAHP) in a fuzzy environment. The Drazin inverse technique is applied to derive a fuzzy total priority matrix, and we normalize the row sum to achieve the steady-state fuzzy priorities. A numerical example in the information systems (IS) industry demonstrates the approach’s real-world applications. The proposed method derives narrower fuzzy spreads compared to the past fuzzy analytic network process (FANP) approaches, minimizing objective uncertainty. Total priority interdependent maps provide insights into complex technical and usability criteria relationships. Comparative analysis highlights innovations, including non-iterative convergence of the total priority matrix and the ability to understand interdependencies between criteria. The integration of the FANP’s network structure with the fuzzy DEMATEL’s influence analysis transcends the capabilities of either method in isolation, marking a significant methodological advancement. By addressing challenges such as parameter selection and mathematical complexity, this research offers new perspectives for future research and application in multi-attribute decision-making (MADM). Full article
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20 pages, 866 KiB  
Article
Multi-Attribute Decision-Making Based on Consistent Bidirectional Projection Measures of Triangular Dual Hesitant Fuzzy Set
by Juan Wang, Baoyu Cui and Zhiliang Ren
Viewed by 543
Abstract
To solve complex multi-attribute decision-making (MADM) problems within a triangular dual hesitant fuzzy (TDHF) environment where the attribute weights (Aws) are either fully or partially known, a novel bidirectional projection method is proposed, named multi-attribute decision-making and based on the consistent bidirectional projection [...] Read more.
To solve complex multi-attribute decision-making (MADM) problems within a triangular dual hesitant fuzzy (TDHF) environment where the attribute weights (Aws) are either fully or partially known, a novel bidirectional projection method is proposed, named multi-attribute decision-making and based on the consistent bidirectional projection measures of triangular dual hesitant fuzzy sets (TDHFSs). First, some notions are developed, such as the operation laws, score and accuracy functions, negative ideal points (NIPs), and positive ideal points (PIPs) of TDHFSs. The correlation coefficients and the cosine of the angle between the vectors of each alternative and the triangular dual hesitant fuzzy (TDHF) points are introduced. Then, the consistent bidirectional projection decision-making method based on the TDHFSs’ correlation coefficients is proposed. Additionally, an optimization model is established via maximizing the consistent coefficient to determine the Aws. Furthermore, some approaches are investigated based on the proposed approaches concerning the MADM issues with attribute values represented by triangular dual hesitant fuzzy elements (TDHFEs). Finally, a supply chain management (SCM) problem is illustrated, and comparative analyses are implemented to demonstrate the presented approach’s feasibility and efficiency. Full article
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38 pages, 2282 KiB  
Article
Fermatean Probabilistic Hesitant Fuzzy Power Bonferroni Aggregation Operators with Dual Probabilistic Information and Their Application in Green Supplier Selection
by Chuanyang Ruan and Lin Yan
Viewed by 741
Abstract
In the realm of management decision-making, the selection of green suppliers has long been a complex issue. Companies must take a holistic approach, evaluating potential suppliers based on their capabilities, economic viability, and environmental impact. The decision-making process, fraught with intricacies and uncertainties, [...] Read more.
In the realm of management decision-making, the selection of green suppliers has long been a complex issue. Companies must take a holistic approach, evaluating potential suppliers based on their capabilities, economic viability, and environmental impact. The decision-making process, fraught with intricacies and uncertainties, urgently demands the development of a scientifically sound and efficient method for guidance. Since the concept of Fermatean fuzzy sets (FFSs) was proposed, it has been proved to be an effective tool for solving multi-attribute decision-making (MADM) problems in complicated realistic situations. And the Power Bonferroni mean (PBM) operator, combining the strengths of the power average (PA) and Bonferroni mean (BM), excels in considering attribute interactions for a thorough evaluation. To ensure a comprehensive and sufficient evaluation framework for supplier selection, this paper introduces innovative aggregation operators that extend the PBM and integrate probabilistic information into Fermatean hesitant fuzzy sets (FHFSs) and Fermatean probabilistic hesitant fuzzy sets (FPHFSs). It successively proposes the Fermatean hesitant fuzzy power Bonferroni mean (FHFPBM), Fermatean hesitant fuzzy weighted power Bonferroni mean (FHFWPBM), and Fermatean hesitant fuzzy probabilistic weighted power Bonferroni mean (FHFPWPBM) operators, examining their key properties like idempotency, boundedness, and permutation invariance. By further integrating PBM with probabilistic information into FPHFSs, three new Fermatean probabilistic hesitant fuzzy power Bonferroni aggregation operators are developed: the Fermatean probabilistic hesitant fuzzy power Bonferroni mean (FPHFPBM), Fermatean probabilistic hesitant fuzzy weighted power Bonferroni mean (FPHFWPBM), and Fermatean probabilistic hesitant fuzzy probabilistic weighted power Bonferroni mean (FPHFPWPBM). Subsequently, a MADM method based on these operators is constructed. Finally, a numerical example concerning the selection of green suppliers is presented to demonstrate the applicability and effectiveness of this method using the FPHFPWPBM operator. Full article
(This article belongs to the Special Issue Fuzzy Systems, Fuzzy Decision Making, and Fuzzy Mathematics)
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28 pages, 4561 KiB  
Article
Selection of AI Architecture for Autonomous Vehicles Using Complex Intuitionistic Fuzzy Rough Decision Making
by Tahir Mahmood, Ahmad Idrees, Khizar Hayat, Muhammad Ashiq and Ubaid ur Rehman
World Electr. Veh. J. 2024, 15(9), 402; https://doi.org/10.3390/wevj15090402 - 3 Sep 2024
Cited by 2 | Viewed by 971
Abstract
The advancement of artificial intelligence (AI) has become a crucial element in autonomous cars. A well-designed AI architecture will be necessary to attain the full potential of autonomous vehicles and will significantly accelerate the development and deployment of autonomous cars in the transportation [...] Read more.
The advancement of artificial intelligence (AI) has become a crucial element in autonomous cars. A well-designed AI architecture will be necessary to attain the full potential of autonomous vehicles and will significantly accelerate the development and deployment of autonomous cars in the transportation sector. Promising autonomous cars for innovating modern transportation systems are anticipated to address many long-standing transporting challenges related to congestion, safety, parking, and energy conservation. Choosing the optimal AI architecture for autonomous vehicles is a multi-attribute decision-making (MADM) dilemma, as it requires making a complicated decision while considering a number of attributes, and these attributes can have two-dimensional uncertainty as well as indiscernibility. Thus, in this framework, we developed a novel mathematical framework “complex intuitionistic fuzzy rough set” for tackling both two-dimensional uncertainties and indiscernibility. We also developed the elementary operations of the deduced complex intuitionistic fuzzy rough set. Moreover, we developed complex intuitionistic fuzzy rough (weighted averaging, ordered weighted averaging, weighted geometric, and ordered weighted geometric) aggregation operators. Afterward, we developed a method of MADM by employing the devised operators and investigated the case study “Selection of optimal AI architecture for autonomous vehicles” to reveal the practicability of the devised method of MADM. Finally, to reveal the dominance and supremacy of our proposed work, a benchmark dilemma was used for comparison with various prevailing techniques. Full article
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32 pages, 1059 KiB  
Article
Categorization of Attributes and Features for the Location of Electric Vehicle Charging Stations
by Andrea Mazza, Angela Russo, Gianfranco Chicco, Andrea Di Martino, Cristian Giovanni Colombo, Michela Longo, Paolo Ciliento, Marco De Donno, Francesca Mapelli and Francesco Lamberti
Energies 2024, 17(16), 3920; https://doi.org/10.3390/en17163920 - 8 Aug 2024
Cited by 3 | Viewed by 1479
Abstract
The location of Electric Vehicle Charging Stations (EVCSs) is gaining significant importance as part of the conversion to a full-electric vehicle fleet. Positive or negative impacts can be generated mainly based on the quality of service offered to customers and operational efficiency, also [...] Read more.
The location of Electric Vehicle Charging Stations (EVCSs) is gaining significant importance as part of the conversion to a full-electric vehicle fleet. Positive or negative impacts can be generated mainly based on the quality of service offered to customers and operational efficiency, also potentially involving the electrical grid to which the EVCSs are connected. The EVCS location problem requires an in-depth and comprehensive analysis of geographical, market, urban planning, and operational aspects that can lead to several potential alternatives to be evaluated with respect to a defined number of features. This paper discusses the possible use of a multi-criteria decision-making approach, considering the differences between multi-objective decision making (MODM) and multi-attribute decision-making (MADM), to address the EVCS location problem. The conceptual evaluation leads to the conclusion that the MADM approach is more suitable than MODM for the specific problem. The identification of suitable attributes and related features is then carried out based on a systematic literature review. For each attribute, the relative importance of the features is obtained by considering the occurrence and the dedicated weights. The results provide the identification of the most used attributes and the categorization of the selected features to shape the proposed MADM framework for the location of the electric vehicle charging infrastructure. Full article
(This article belongs to the Special Issue Smart Electric Vehicle Charging Approaches for Demand Response)
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22 pages, 4368 KiB  
Article
Implementing a Multi-Attribute Decision-Making-Based Approach to Evaluate Small Electric Vertical Takeoff and Landing Fixed-Wing Drones with Mission Efficiency
by Zhuo Bai, Bangchu Zhang, Zhong Tian, Shangnan Zou and Weiyu Zhu
Aerospace 2024, 11(7), 568; https://doi.org/10.3390/aerospace11070568 - 11 Jul 2024
Cited by 1 | Viewed by 965
Abstract
Evaluating the mission efficiency of various drone configurations under complex, multi-source, and multi-dimensional requirements remains a significant challenge. This study aimed to develop a comprehensive decision support system (DSS) that employs mission efficiency evaluation, probabilistic hesitant fuzzy sets (PHFs), and multi-attribute decision-making (MADM) [...] Read more.
Evaluating the mission efficiency of various drone configurations under complex, multi-source, and multi-dimensional requirements remains a significant challenge. This study aimed to develop a comprehensive decision support system (DSS) that employs mission efficiency evaluation, probabilistic hesitant fuzzy sets (PHFs), and multi-attribute decision-making (MADM) methods to assess and optimize drone design. In the proposed method, mission efficiency is defined as a composite measure of the flight performance, adaptability, and economic viability required to complete a mission. By designing a “demand–capability–design” mapping approach, this system effectively resolves multi-attribute conflicts in the decision-making process. To demonstrate the proposed approach, a set of small electric vertical takeoff and landing fixed-wing (e-VTOLFW) drones are compared and ranked based on their mission efficiency. The impacts of different mission requirements on drone evaluation are also discussed. The results demonstrate that this model resolves the traditional issue of unclear information flow in drone design. By improving the evaluation criteria, it enhances informed decision making and the robustness of evaluation results in drone design assessments. Additionally, the model is generalizable and can be widely applied to similar fields such as “demand–product design”, improving the understanding and optimization of product performance. Full article
(This article belongs to the Section Aeronautics)
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28 pages, 2296 KiB  
Article
Decision-Making Approach to Design a Sustainable Photovoltaic Closed-Loop Supply Chain Considering Market Share for Electric Vehicle Energy
by Hadi Shenabi and Rashed Sahraeian
Sustainability 2024, 16(13), 5763; https://doi.org/10.3390/su16135763 - 5 Jul 2024
Cited by 1 | Viewed by 1138
Abstract
This study aims to develop a model for the closed-loop supply chain of photovoltaic (PV) systems. The primary objective addresses strategic and tactical decision-making using a two-stage approach. To pinpoint suitable locations for solar power plants, the PROMETHEE II method is utilized, which [...] Read more.
This study aims to develop a model for the closed-loop supply chain of photovoltaic (PV) systems. The primary objective addresses strategic and tactical decision-making using a two-stage approach. To pinpoint suitable locations for solar power plants, the PROMETHEE II method is utilized, which is a component of multi-attribute decision making (MADM) approaches. Next, a multi-objective modeling of the closed-loop PV supply chain is conducted. This model aims to minimize total supply chain costs, reduce environmental impacts, mitigate adverse social effects, maximize the on-time delivery (OTD) of manufactured products, and maximize market share. Additionally, a robust fuzzy mathematical model is introduced to examine the model’s sustainability under various uncertainties. An evaluation of the effectiveness and utility of this model is conducted in Tehran city. Furthermore, a comprehensive analysis of various supply chain costs indicates that production centers have the highest costs, while separation centers have the lowest costs. Full article
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