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With the constant changes in the decision-making environment, various limitations have emerged in traditional decision-making methods, such as the inability to simultaneously consider multiple factors such as randomness, hesitation, and ambiguity, thus limiting a comprehensive grasp of the decision-maker's cognitive inputs. To address the above problems, we propose a multi-criteria decision-making (MCDM) model based on a new fuzzy set (FS). Firstly, we define a new Z hesitant fuzzy linguistic term set (ZHFLTS) and propose a visualization metric for mapping ZHFLTS into T-spherical fuzzy (T-SF) space to simplify the computation. The relevant properties of ZHFLTS are further investigated. In order to accurately measure the uncertainty of FSs, we propose the probabilistic-hesitation-fuzzy (PHF) entropy and use it as a basis to derive the potential probability distribution using the fruit fly optimization algorithm (FOA). Subsequently, an MCDM model is established based on the proposed ZHFLTS, visualization metric, and PHF entropy. The model can better solve complex decision-making problems such as TCM through example studies and comparative analyses. The research in this paper aims to cope with today's increasingly complex decision-making environments, and the introduced ZHFLTS framework and the corresponding methodology provide new ways to solve complex decision problems. • ZHFLTS is defined and a mapping method to visualize ZHFLTS in T-SF space is studied. • PHF entropy is proposed based on FOA for obtaining potential probability distribution. • A Novel MCDM model based on ZHFLTS is presented. • It proves the effectiveness of the model through instances and comparative analysis. [ABSTRACT FROM AUTHOR]

Fifth-generation (5G) technology provides new possibilities for a variety of applications, but it also comes with challenges influenced by distinct aspects, such as the size of organizations that use such technology. Therefore, it is important to understand which architecture of 5G-radio access networks (RANs) is best for a given purpose; this requires an evaluation platform for assessment. This paper tackles this problem by presenting a novel multi-criteria decision-making (MCDM) solution based on a new integrated fuzzy set. The proposed integrated approach, which is based on a Type-2 neutrosophic fuzzy environment, is developed to address the application challenges of 5G-RANs architecture evaluation, as also to face the MCDM theoretical challenge represented by ambiguities and inconsistencies among decision makers within the decision making context of the presented case study. Many MCDM techniques for weighting and selection were presented from the literature, yet many of them still suffer from inconsistencies and uncertainty. Therefore, the chosen methods in this research are unique in a way that previous issues are addressed, making them suitable for integration with Type-2 neutrosophic fuzzy environment, and therefore creating a more robust decision platform for the presented challenge in this research, as a theoretical contribution. First, a new "Type-2 Neutrosophic Fuzzy-Weighted Zero-Inconsistency" (T2NN-FWZIC) technique is formulated for weighting the evaluation criteria of RAN architectures. Second, another new method, namely, "Type-2 Neutrosophic Fuzzy Decision by Opinion Score Method" (T2NN-FDOSM), was formulated to select the optimal RAN architecture using the obtained weights. The weighting results by T2NN-FWZIC for the (n = 25) evaluation criteria revealed that (C 21 latency and C 22 reliability) as the most important criteria, with 0.06 value for each as opposed to (C 15 Data Processing) as the lowest weighted criteria with 0.0186 value. As for T2NN-FDOSM, a total of four 5G-RAN architectures were evaluated, including "virtualized cloud RAN" coming as the optimal one, followed by "fog RAN," "cloud RAN," and finally "heterogeneous cloud RAN." The results were confirmed by carrying out a sensitivity analysis. The outcome of this study can be used to assist future 5G-RAN developments according to business needs and to establish an assessment platform for 5G technology in different domains and applications. [ABSTRACT FROM AUTHOR]

The strategic supplier-related activity of supplier segmentation focuses on the evaluation of suppliers, identifying different approaches, identifying the most suitable criteria and proper methods to segment the suppliers. The main aim of the evaluation of suppliers is to form different groups from the selected suppliers to create different supplier management strategies for segments involved. Supplier development is another strategic supplier-related activity designed to upgrade the performance level of suppliers in order to create and maintain a network of competent suppliers, which has a major influence on the competitive advantages of a buying company. To allocate scarce resources more efficiently, we should design different supplier development strategies for different supplier segments. This is where we actually use the evaluation for suppliers. This paper proposes an integrative approach that includes capabilities and willingness as two dimensions for evaluating and subsequently segmenting suppliers. The results of that segmentation are then used as the main basis for supplier development. The integrative approach proposed in this paper is of significant importance, as it helps companies apportion their managerial resources more efficiently. We use a new multi-criteria decision-making method called Best Worst Method (BWM) to segment suppliers. A supplier development conceptual model is proposed to develop the suppliers in the different segments. The proposed framework is further applied to a medium-sized high-tech company as input to validate the model. [ABSTRACT FROM AUTHOR]

[Display omitted] • Main developments on sorting approaches. • The categorization of multiple-criteria decision-making sorting methods. • Applications of the multiple-criteria decision-making sorting methods. • Trends and future directions of MCDM Sorting. Multi-Criteria Decision Making (MCDM) is a complex process. It aims to support decision makers in making their decisions more effective and consistent. MCDM provides a useful and successful alternative for handling three main types of MCDM problems, namely, choosing, ranking and sorting. The first two are the most common problems studied but the third offers a way to deal with real world MCDM problems that require alternatives to be assigned to ordered categories. The practitioners are currently developing and applying sorting methods to solve problems from different application areas. In spite of its interest and applicability, there is only one previous review on Multiple-Criteria sorting, performed almost 20 years ago. Hence, because of its interest this paper presents a new and systematic review of MCDM sorting methods that includes 30 years of research in the field. This review has systematically analyzed the conventional and non-classical methods of MCDM sorting and then classified the papers published into 16 application areas. The analysis reveals that the methodological development is still in growth phase for MCDM sorting and discovers the applied methods' trends. It also shows the complete spectrum of the areas of the application addressed, the state of knowledge about methods, the type of contribution to the knowledge, and the application area for the four categories of the MCDM approaches. The systematic review scrutinizes each selected article in order to find out which approach from the multi-criteria sorting presents the most development based on its contribution and application of the methods. We also aim to discover which Multiple-Criteria sorting methods are the most studied in MCDM. The relevant finding is the relation between the most applied methods and the application areas together with future directions for further research. [ABSTRACT FROM AUTHOR]

In general, traditional decision-making models are based on methods that perform calculations on quantitative measures. These methods are usually applied to assess possible solutions to a problem, resulting in a ranking of alternatives. However, when it comes to making decisions about qualitative measures —such as service quality—, the quantitative assessment is a bit difficult to interpret. Therefore, taking into account the maturity of the linguistic assessment models, this paper puts forth a new solution proposal. It is a decision-making model that uses linguistic labels —represented with the 2-tuple notation— and a variable expressive richness when providing output results. This solution allows expressing results in a manner closer to the human cognitive system. To achieve this goal, a mechanism has been implemented for measuring the distance among the aggregate ratings, providing the decision-maker with a fast and intuitive answer. The proposal is illustrated with an application example based on the TOPSIS model, using linguistic labels throughout the entire process. [ABSTRACT FROM AUTHOR]

Transshipment hub selection becomes increasingly important to the global logistics community. From the perspectives of shippers and freight forwarders, a selection must align with cost control strategy and sustain service reliability across cooperative service providers. This paper assesses the selection with the options of both sea and air transports, and from the influence of country of origin of the company. Critical factors of transshipment hub selection, both qualitative and quantitative, are identified through focus group discussions. Relative importance of these factors is determined based on collective views of logistics stakeholders. The competitiveness of transshipment hubs is then assessed using an AHP approach. Our analysis is based on the historical implementation of direct transportation link policy between Mainland China and Taiwan. With this empirical work, the finding suggests that even the spawn of other nearby ports with shorter transport distance and closer proximity to cargo sources, there remain overriding factors such as customs regulations & government policies and connectivity that a transshipment hub is preferred. [ABSTRACT FROM AUTHOR]

Tender analysis processes are everyday processes in any company, but they become even more important when the financial resources are limited. Achieving optimal and transparent tender analysis processes requires hard work from everyone involved. This paper proposes a linguistic multi-criteria decision-making model which helps decision-makers in this task by automating it. To do that, the proposal requires diverse experts to assess different criteria and establish their corresponding weights. The processing of all these input data will determine a minimum value, called profile , to consider an alternative as valid. Additionally, assessments of a similar (probably external) process will be taken into account, becoming a reference valuation. Unlike other decision-making models, the use of this last value gives an idea of the goodness of the result depending on whether the solution obtained is close to the reference value. To the best of our knowledge, there is no expert or intelligent system specifically designed to fully meet the needs of tender analysis processes. For both input and output process stages carried out in our proposal, 2-tuple linguistic labels have been used. These linguistic labels were chosen to facilitate decision-making for the staff involved in the process, as well as for being the most suitable communication way used by human beings. To validate the model, we apply it to a case study in the ICT (Information and Communications Technology) sector. In addition, we include a literature review related to applications using the 2-tuple representation, as well as a comparison of our proposal with related methods, including the results obtained by these methods for the case study presented. [ABSTRACT FROM AUTHOR]

QUALIFLEX (QUALItative FLEXible multiple criteria method) is a very useful outranking method to deal simultaneously with the cardinal and ordinal information in decision making process. The purpose of this paper is to develop a hesitant fuzzy QUALIFLEX with a signed distance-based comparison method for handling multi-criteria decision-making problems in which both the assessments of alternatives on criteria and the weights of criteria are expressed by hesitant fuzzy elements (HFEs). We propose a novel concept of hesitancy index for the HFE to measure the degree of hesitancy of the decision-maker or the decision organization. By taking their hesitancy indices into account, we present a signed distance-based method to compare the magnitude of HFEs. Using the signed distance-based comparison approach, we define the concordance/discordance index, the weighted concordance/discordance index and the comprehensive concordance/discordance index. By investigating all possible permutations of alternatives with respect to the level of concordance/discordance of the complete preference order, the optimal ranking orders of alternatives can be obtained. An application study of the proposed method on green supplier selection is conducted. The study indicates that the proposed method does not require the complicated computation procedures but still yields a reasonable and credible solution. [ABSTRACT FROM AUTHOR]

• A new form of the ranking based on optimal points MCDM method is developed. • A new weighting method is developed called Win, Loss, Draw method. • RBOP imitates the decision maker's behavioral pattern to find the best alternative. Supplier evaluation is a complex multi-criteria decision-making (MCDM) problem that deals with assessment of suppliers as the potential alternatives against various types of criteria. We consider the context where decision makers (DMs) have complete information about the suppliers and criteria. To address the needs of decision makers, a multi-criteria evaluation method named Ranking based on optimal points (RBOP) is developed in this paper. By imitating and simulating human decision-making behavioural patterns, the developed MCDM method selects the best alternative that is closer to what the DM desires. Furthermore, a novel subjective MCDM weighting method s called win-loss-draw (WLD) method is also developed, which is also based on human behavioural pattern. A real case study of domestic cheese brands is considered to apply the developed methods to select the best cheese supplier for an Iranian hypermarket. Compared to other MCDM methods, outputs of the RBOP method show some differences due to the impact of WLD method, which intensified divergence and optimal points during the decision-making process. [ABSTRACT FROM AUTHOR]

• Define Choquet integral based intuitionistic fuzzy arithmetic aggregation operator. • Combine the defined operator with ordered weighted aggregation operator. • Propose a decision-making method based on the combined operator. Intuitionistic fuzzy set (IFS), a classical extension of fuzzy set, is a powerful tool to describe fuzzy information in multi-criteria decision-making (MCDM) because of its membership and non-membership functions. Intuitionistic fuzzy aggregation operators are the standard mathematical tools for the combination of several inputs with respect to criteria into one unique output. The traditional intuitionistic fuzzy aggregation operator-based methods have been criticized because of reasons that include disregard for comprehensive correlative relationships of criteria and ignorance for combination of fuzzy measures of criteria and weights of positions. In this paper, the effectiveness of traditional aggregation operator-based MCDM techniques is improved by a novel method to select the best alternative(s) under the intuitionistic fuzzy environment. We begin by defining the Choquet integral-based intuitionistic fuzzy arithmetic aggregation (CIIFAA) operator, the remarkable properties of which are proved in details. Further, the Choquet integral based intuitionistic fuzzy hybrid arithmetic aggregation (CIIFHAA) operator is defined as well as the proofs of its properties. The CIIFHAA operator can not only capture the comprehensive correlative relationships of criteria in a simpler manner, but also combine the weights of positions. Then, we put forward a MCDM method based on CIIFHAA operator with intuitionistic fuzzy evaluations. An illustrative example is solved, the best alternative and the ranking of alternatives are obtained, which can verify the feasibility of the proposed method. Finally, two comparisons are conducted to illustrate the stability and advantages of the proposed method. [ABSTRACT FROM AUTHOR]