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The good development of health care is conducive to improve the value and prospects of society. However, health sectors of Ghana are facing a challenge in providing medical services with expected quality for an ever-increasing number of patients in response to competitive pressures. In such circumstances, the proper evaluation of hospital health-care delivery quality becomes critical. Thus, to achieve this goal, this paper proposes an integrated medical triangular fuzzy MULTIMOORA approach (IMTFMA). We firstly construct the appropriate evaluation criteria system based on the analysis of Ghana's medical services. Then, to properly evaluate the weight of the criteria in a comprehensive manner, we determine the weight of criteria from subjective and objective perspectives. Meantime, we handle the fuzzy evaluation of experts for the criterion importance with the enhanced alpha-level sets method. According to the triangular fuzzy rating for hospitals provided by respondents, we further develop a novel evaluation method based on MULTIMOORA with the axiomatic design for accurately evaluating health-care delivery quality. The research is conducted on 8 selected hospitals, including 4 public and 4 private hospitals in the Greater Accra Region of Ghana, with 24 criteria. 15 experts with rich experience in related fields and 480 respondents assessed the above 8 selected hospitals by questionnaires. According to the outcome of the empirical analysis, even though public hospitals benefit subsidy from the government, they perform abysmally low, whereas private hospitals which are self-sponsored rather perform extremely better than expectation. [ABSTRACT FROM AUTHOR]

[Display omitted] • A new fuzzy subsethood-based IT2F-AD is developed. • Proposed IT2F-AD is integrated with IT2F-BWM. • Blockchain deployment projects are evaluated. • A real-life case study is provided. This study is concerned with the development of the axiomatic design (AD) method under an interval type-2 fuzzy (IT2F) environment and its application in evaluating blockchain deployment projects in supply chains. Blockchain is a transformative technology that has received significant attention recently. Blockchain technology can process various business transactions by offering a reliable and decentralized infrastructure. Supply chain management is an important application area of blockchains due to its desirable properties, including data security, extended visibility, product traceability, digitalization, and disintermediation. Since blockchain technologies are in their infancy, adopting them to supply chains requires proper design methodologies. Fuzzy AD offers valuable computational mechanisms to evaluate design options in the presence of functional requirements. However, extending AD to different fuzzy extensions is not an easy task, and area-based calculations hinder its widespread applicability. In this study, an IT2F-AD method is developed based on the concept of fuzzy subsethood. The potential of the fuzzy subsethood measure as the main computation engine within type-1 and IT2F-AD is demonstrated. Finally, an integrated multiple criteria decision-making (MCDM) model is proposed by using IT2F Best-Worst Method (IT2F-BWM) and IT2F-AD. The proposed model is used to prioritize blockchain deployment projects in a real-life case study. [ABSTRACT FROM AUTHOR]

In the field of evidence theory, the processing of uncertain information is a very important research orientation, which has been receiving widespread attention in academic community. Recently, Yager and Alajlan proposed a method to evaluate the belief structure satisfaction to uncertain target values. However, this method ignored the effect of the overlapping degree between events. In this paper, a new method used to calculate the belief structure satisfaction is proposed. With different overlapping degrees between events considered, this new method effectively quantifies the evaluation interval of the belief structure satisfaction. The validity of the proposed belief structure satisfaction is verified in an illustrative application for multi-criteria decision-making through a combination of evidential axiomatic design process. [ABSTRACT FROM AUTHOR]

This paper aims to develop a new axiomatic design-based mathematical programming method for heterogeneous multi-criteria group decision making (HMCGDM) problems with linguistic fuzzy truth degrees (LFTDs). The main contributions of this paper are summarized in five aspects: (1) The information content definitions for six types of fuzzy numbers are initially provided according to axiomatic design. (2) Considering the authority of experts on different criteria and group consensus, a bi-objective programming model is constructed to derive experts' weights by maximizing individual deviation and minimizing group discordance. (3) Each alternative is assessed on the basis of its information content to a fuzzy positive ideal solution. Information content is firstly used to define the linguistic fuzzy consistency and inconsistency indices. (4) A bi-objective linguistic fuzzy mathematic programming model is built to determine the criteria weights, which considers consistency and inconsistency indices simultaneously. This model can be dexterously transformed into a crisp linear programming model for resolution by the linguistic scale function. (5) The group information content of each alternative to fuzzy positive ideal solution is calculated to determine the ranking order of alternatives. Finally, an example of blockchain service provider selection is given to validate the proposed method. [ABSTRACT FROM AUTHOR]

For decades practitioners have been using the center-based partitional clustering algorithms like Fuzzy C Means (FCM), which rely on minimizing an objective function, comprising of an appropriately weighted sum of distances of each data point from the cluster representatives. Numerous generalizations in terms of choice of the distance function have been introduced for FCM since its inception. In a stark contrast to this fact, to the best of our knowledge, there has not been any significant effort to address the issue of convergence of the algorithm under the structured generalization of the weighting function. Here, by generalization we mean replacing the conventional weighting function u ij m (where u ij indicates the membership of data x i to cluster C j and m is the real-valued fuzzifier with 1≤ m < ∞) with a more general function g ( u ij ) which can assume a wide variety of forms under some mild assumptions. In this article, for the first time, we present a novel axiomatic development of the general weighting function based on the membership degrees. We formulate the fuzzy clustering problem along with the intuitive justification of the technicalities behind the axiomatic approach. We develop an Alternative Optimization (AO) procedure to solve the main clustering problem by solving the partial optimization problems in an iterative way. The novelty of the article lies in the development of an axiomatic generalization of the weighting function of FCM, formulation of an AO algorithm for the fuzzy clustering problem with the extension to this general class of weighting functions, and a detailed convergence analysis of the proposed algorithm. [ABSTRACT FROM AUTHOR]

The advancement of knowledge service has enabled the demanders and suppliers to find satisfied cooperation results. An optimal match between demanders and suppliers can facilitate continuous improvement and efficiency in knowledge services. While selecting suitable matching knowledge demander and supplier pairs is of significance for effective knowledge services, an area that has been generally neglected in previous studies. This paper reports on a method for effectively matching suitable knowledge service demanders and suppliers in which the expectation levels of attributes given by demanders and suppliers are considered. Linguistic information is used to describe the demanders and suppliers’ expectation levels and their actual levels. A new matching degree calculation method is proposed which takes account of the fuzzy linguistic information. First, the matching relationship between the demanders and suppliers is defined. Then, from the principle of axiomatic design (AD), a method based on fuzzy axiomatic design (FAD) is developed to identify the matching degree between the knowledge demanders and suppliers. Further, a multi-objective optimization model is formulated to maximize the overall matching degree of the pairs and to select the optimal matching pairs. Finally, an example illustrates the potential applications of the proposed method. The obtained computational process and results clearly demonstrate how optimal matching pairs can be identified for knowledge services’ demanders and suppliers. [ABSTRACT FROM AUTHOR]

Abstract: It is commonsense that people do express, think, reason, and make decision directly using linguistic terms in natural language rather than using numerical quantification. How to establish the formalized approach imitating the common way of human being’s to manipulate directly linguistic terms without numerical approximation to provide the rational decision is still an open research area. Investigations on the algebraic structure of linguistic term set for varied decision making applications (especially in social science) still lack a formalism for development of strict linguistic valued logic system as a theoretical foundation and its approximate reasoning scheme in practice. To attain this goal we characterize and construct a typical structure of commonly used linguistic term sets in natural language by a lattice-ordered algebra structure – lattice implication algebra (LIA), where Łukasiewicz implication algebra, as a special case of LIA, plays a substantial role. By using Łukasiewicz logic’s axiomatizability in terms of Pavelka type fuzzy logic, we propose a new axiomatizable lattice ordered qualitative linguistic truth-valued logic system based on LIA to place an important foundation for further establishing formal linguistic truth-valued logic based approximate reasoning and decision making with applications. This proposed logic system has a distinct feature of handling comparable or incomparable linguistic terms directly without numerical quantification, will be especially beneficial for perception-based decision making processes. It attempts to enhance the quantitative theory of decision science with qualitative, algebraic and logic-oriented approaches to achieve reasoning with words. [Copyright &y& Elsevier]

Abstract: Molodtsov initiated the concept of soft set theory, which can be used as a generic mathematical tool for dealing with uncertainty. However, it has been pointed out that classical soft sets are not appropriate to deal with imprecise and fuzzy parameters. In order to handle these types of problem parameters, some fuzzy (or intuitionistic fuzzy, interval-valued fuzzy) extensions of soft set theory are presented, yielding fuzzy (or intuitionistic fuzzy, interval-valued fuzzy) soft set theory. In this paper, we define the distance measures between intuitionistic fuzzy soft sets and give an axiom definition of intuitionistic entropy for an intuitionistic fuzzy soft set and a theorem which characterizes it. Furthermore, we discuss the relationship between intuitionistic fuzzy soft sets and interval-valued fuzzy soft sets and transform the structure of entropy for intuitionistic fuzzy soft sets to the interval-valued fuzzy soft sets. [Copyright &y& Elsevier]

Abstract: The measurement of the degree of agreement in a group has recently attracted considerable attention by researchers from various fields. In this paper we consider situations where each member of a population classifies a list of options as either “acceptable” or “non-acceptable” (as in job committees or elections by approval voting); either “agree” or “disagree” (as in polls or surveys); either “guilty” or “not guilty” (as in jury courts), etc. In order to measure the cohesiveness that the expression of such dichotomous opinions conveys, we propose the novel concept of approval consensus measure (ACM), which does not refer to any priors of the agents like preferences or other decision-making processes. Then we give axiomatic characterizations of two generic classes of ACMs. Finally, we focus on the 2012 presidential elections in USA as a real scenario to put in practice these two proposals. [Copyright &y& Elsevier]

Abstract: Managing the verification of primary design projects for ship machinery systems is one of the crucial stages in ship building processes. In particular, the design of operator–system interfaces such as remote controls, displays, alarms, workstations, and labels requires a high level of technical expertise and systematic control. This paper focuses on structuring a ship design project approval mechanism (SDPAM) based on fuzzy axiomatic design (FAD) methodology which is concerned with the system design of relevant interfaces on an engine room control console. Design characteristics such as accessibility and operational requirements are treated as “hard” constraints being encountered in this complex problem. Hence, the proposed methodology requires performance assessment using fuzzy values. This study provides original contributions to the existing approval procedures of classification societies, which are non-governmental construction and classification organizations in the shipping industry. Furthermore, the study proposes a new approach to handle uncertainty and vagueness by an axiomatic design extension to ship project execution problems. [Copyright &y& Elsevier]

The basic concept in axiomatic design (AD) is the existence of design axioms. First of these axioms is the independence axiom and the second one is the information axiom. Information axiom proposes the selection of the best alternative that has minimum information. Analytic hierarchy process (AHP) is another multi-attribute method which is a decision-making method for selecting the best among a set of alternatives, given some criteria. The method has been extensively applied, especially in large-scale problems where many criteria must be considered and where the evaluation of alternatives is mostly subjective. Multi-attribute transportation company selection is a very important activity for effective supply chain. Selection of the best company under determined criteria (such as cost, time, damage/loss, flexibility and documentation ability) using both multi-attribute AD and AHP will be realized in this study. The fuzzy multi- attribute AD approach is also developed and it is compared by one of fuzzy AHP methods in the literature. The selection process has been accomplished by aiding a software that includes crisp AD and fuzzy AD. [ABSTRACT FROM AUTHOR]