► A novel Likert scale based on fuzzy sets theory is proposed. ► The new scale is proven to be more accurate using a consensus model. ► Information distortion/lost can be reduced significantly. ► The ...implementation feasibility is demonstrated via a low birth weight analysis.
The Likert method is commonly used as a standard psychometric scale to measure responses. This measurement scale has a procedure that facilitates survey construction and administration, and data coding and analysis. However, there are some drawbacks in the Likert scaling. This paper addresses the information distortion and information lost arising from the closed-form scaling and the ordinal nature of this measurement method. To overcome these problems, a novel fuzzy Likert scale developed based on the fuzzy sets theory has been proposed. The major contribution of the fuzzy Likert approach is that it permits partial agreement of a scale point. By incorporating this capability into the measurement process, the new scale can capture the lost information and regulate the distorted information. A quantitative analysis based on the concept Consensus has proven that the new scale can provide a more accurate measurement. The implementation feasibility and the improved measurement performance of the fuzzy Likert scale have been demonstrated via a simulation study on a low birth weight analysis.
The emergence of fuzzy sets makes job-shop scheduling problem (JSSP) become better aligned with the reality. This article addresses the JSSP with fuzzy execution time and fuzzy completion time ...(FJSSP). We choose the classic differential evolution (DE) algorithm as the basic optimization framework. The advantage of the DE algorithm is that it uses a special evolutionary strategy of difference vector sets to carry out mutation operation. However, DE is not very effective in solving some instances of FJSSP. Therefore, we propose a novel selection mechanism augmenting the generic DE algorithm (NSODE) to achieve better optimization results. The proposed selection operator adopted in this article aims at a temporary retention of all children generated by the parent generation, and then selecting N better solutions as the new individuals from N parents and N children. Various examples of fuzzy shop scheduling problems are experimented with to test the performance of the improved DE algorithm. The NSODE algorithm is compared with a variety of existing algorithms such as ant colony optimization, particle swarm optimization, and cuckoo search. Experimental results show that the NSODE can obtain superior feasible solutions compared with solutions produced by several algorithms reported in the literature.
► A new Multi-Criterion Decision Making (MCDM) methodology, using fuzzy sets theory (FST) and Dempster Shafer Theory of evidence (DST), is developed to deal with supplier selection problem. ► The ...Basic Probability Assignments (BPA) can be determined by the distance to the ideal solution and the distance to the negative ideal solution. The proposed method is more flexible due to the reason that the BPA can be determined without the transformation step in traditional fuzzy TOPSIS method. ► The numerical example about supplier selection is used to illustrate the efficiency of the proposed method.
Supplier selection is a multi-criterion decision making problem under uncertain environments. Hence, it is reasonable to hand the problem in
fuzzy sets theory (FST) and
Dempster Shafer theory of evidence (DST). In this paper, a new MCDM methodology, using FST and DST, based on the main idea of the technique for order preference by similarity to an ideal solution (TOPSIS), is developed to deal with supplier selection problem. The
basic probability assignments (BPA) can be determined by the distance to the ideal solution and the distance to the negative ideal solution. Dempster combination rule is used to combine all the criterion data to get the final scores of the alternatives in the systems. The final decision results can be drawn through the pignistic probability transformation. In traditional fuzzy TOPSIS method, the quantitative performance of criterion, such as crisp numbers, should be transformed into fuzzy numbers. The proposed method is more flexible due to the reason that the BPA can be determined without the transformation step in traditional fuzzy TOPSIS method. The performance of criterion can be represented as crisp number or fuzzy number according to the real situation in our proposed method. The numerical example about supplier selection is used to illustrate the efficiency of the proposed method.
•Proposing a novel integration of Z numbers and Best Worst Method.•The method results in lower inconsistency.•The uncertainty of the real word decisions is considered in the proposed method.
Best ...Worst Method (BWM) has recently been proposed as a method for Multi Criteria Decision Making (MCDM). Studies show that BWM compared with other methods such as Analytic Hierarchy Process (AHP), leads to lower inconsistency of the results while reducing the number of required pairwise comparisons. MCDM methods such as BWM require accurate information. However, it often happens in practice that a level of uncertainty accompanies the information. The main aim of this paper is to address this problem and provide an integration of BWM and Z-numbers, namely ZBWM. Providing BWM with Z-numbers enables the BWM method to handle the uncertainty of information of a multi-criteria decision. Additionally, the capabilities of the proposed method in the process of utilizing the linguistic information dealing with big data are highlighted. The proposed method is examined to address a supplier development problem. By experimental results, we show that ZBWM results lower inconsistency when compared with BWM. A Z-number contains subjectivity in its fuzzy part, which can be addressed in future applications of ZBWM.
The job-shop scheduling problem (JSP) is NP hard, which has very important practical significance. Because of many uncontrollable factors, such as machine delay or human factors, it is difficult to ...use a single real-number to express the processing and completion time of the jobs. JSP with fuzzy processing time and completion time (FJSP) can model the scheduling more comprehensively, which benefits from the developments of fuzzy sets. Fuzzy relative entropy leads to a method that can evaluate the quality of a feasible solution following the comparison between the actual value and the ideal value (the due date). Therefore, the multiobjective FJSP can be transformed into a single-objective optimization problem and solved by a hybrid adaptive differential evolution (HADE) algorithm. The maximum completion time, the total delay time, and the total energy consumption of jobs will be considered. HADE adopts a mutation strategy based on DE-current-to-best. Its parameters (CR and F ) are all made adaptive and normally distributed. The new individuals are selected according to the fitness value (FRE) obtained from a population consisting of N parents and N children in HADE. The algorithm is analyzed from different viewpoints. As the experimental results demonstrate, the performance of the HADE algorithm is better than those of some other state-of-the-art algorithms (namely, ant colony optimization, artificial bee colony, and particle swarm optimization).
In this paper a new approach was proposed so as to comparatively evaluate the quality of service alternatives. In particular, a fuzzy extension of the ServPerf service conceptual model was considered ...to estimate quality scores of fundamental service criteria, whereas the non-compensative multi-criteria decision-making ELECTRE III method was employed to point out the quality ranking of service alternatives on the basis of which the comparative service quality analysis was performed. In order to show the effectiveness of the proposed approach, an empirical study concerning service quality evaluation of the three international airports in Sicily (Italy) was conducted with detailed proposals for passenger service improvement. The results showed that only few key service aspects played a focal role in quality airport service. Moreover, the effects on the evaluation of service quality, arising from customers' uncertainties, were computed, thus demonstrating the effectiveness of the proposed approach.
•A methodology capable of handling uncertainty in service performance analysis is developed.•The ELECTRE III procedure is adopted to point out the quality ranking of service alternatives.•A strategic analysis concerning service quality evaluation of the three international airports in Sicily is performed.
This study proposes a framework based on the concept of fuzzy sets theory and the VIKOR method to provide a rational, scientific and systematic process for evaluating the hospital service quality ...under a fuzzy environment where the uncertainty, subjectivity and vagueness are addressed with linguistic variables parameterized by triangular fuzzy numbers. This study applies the fuzzy multi-criteria decision making approach to determine the importance weights of evaluation criteria and the VIKOR method is taken to consolidate the service quality performance ratings of the feasible alternatives. An empirical case involving 33 evaluation criteria, 2 public and 3 private medical centres in Taiwan assessed by 18 evaluators from various fields of medical industry is solicited to demonstrate the proposed approach. The analysis result reveals that the service quality of private hospitals is better than public hospitals because the private hospitals are rarely subsidized by governmental agencies. These private hospitals have to fend themselves to retain existing patients or attract new patients to ensue sustainable survival.
► We proposed a method to deal with MCDM problem under the framework of Demspter-Shafer evidence theory. ► A new fuzzy evidential MCDM method under uncertain environments is proposed. ► The ...linguistic variables can be transformed into basic probability assignments. ► Data from different criteria can be combined based on the Demspter rule.
Multiple-criteria decision-making (MCDM) is concerned with the ranking of decision alternatives based on preference judgements made on decision alternatives over a number of criteria. First, taking advantage of data fusion technology to comprehensively consider each criterion data is a reasonable idea to solve the MCDM problem. Second, in order to efficiently handle uncertain information in the process of decision making, some well developed mathematical tools, such as fuzzy sets theory and Dempster Shafer theory of evidence, are used to deal with MCDM. Based on the two main reasons above, a new fuzzy evidential MCDM method under uncertain environments is proposed. The rating of the criteria and the importance weight of the criteria are given by experts’ judgments, represented by triangular fuzzy numbers. Then, the weights are transformed into discounting coefficients and the ratings are transformed into basic probability assignments. The final results can be obtained through the Dempster rule of combination in a simple and straight way. A numerical example to select plant location is used to illustrate the efficiency of the proposed method.
Vlsekriterijumska optimizacija i kompromisno resenje (VIKOR) method is one of the most popular multiple criteria decision making (MCDM) techniques in which, the optimal alternative is determined ...based on an agreement between maximum group utility and minimum individual regret. Despite VIKOR presents important advantages regarding other techniques for decision situations, it may result in a situation where an alternative with high measures for most criteria and low value for one criterion is not chosen as the optimal alternative. Thus, VIKOR may lead to unreasonable and inconsistent results and cannot present true situation of alternatives in indices’ list. The goal of this paper is to present an improved extended version of interval type-2 fuzzy VIKOR (IT2FVIKOR) method for relieving the drawbacks of usual IT2FVIKOR. The proposed indices present more continuous and logical values than prior one such that better ranking results obtain for the MCDM problems. In order to demonstrate effectuality of the suggested method, a case study and an illustrative example are performed. Eventually, the extracted ranking upshots are analyzed with the others.
To achieve sustainability, businesses are adopting Cleaner Production (CP) and Circular Economy (CE) practices for producing better quality products at the lowest cost while decreasing the negative ...environmental impact of their operations. The implementation of these practices is highly influenced by Industry 4.0 technology’s enablers, particularly within the context of ethical and sustainable business development. In this paper, a novel framework is proposed to assess the importance of Industry 4.0 enablers for implementing CP practices embedded in CE in the context of ethical societies and assess an industry’s readiness. Firstly, the most effective context-related Industry 4.0 enablers are extracted from previous studies and validated through a Fuzzy Delphi method. Secondly, the Interval-Valued Fuzzy Sets (IVFS) based Analytical Hierarchy Process (AHP) method is applied to evaluate the enablers’ weight. Due to existing ambiguities in the enablers, IVFS was applied to model the uncertainty in an interval 0,1. The final results indicate that the most important enablers are “Technical Capability”, “Security and Safety”, Policy and Regulation”, “System Flexibility”, “Education and Participation” and “Support and Maintenance” respectively. Thirdly, the Fuzzy Evaluation Method (FEM) was followed to evaluate the readiness score of Industry 4.0 enablers for implementing CP practices embedded in CE and evolving ethical principles of corporate social responsibility. This paper contributes to the CP, CE and ethics body of knowledge by proposing a framework for assessing the dimensions of Industry 4.0 enablers during the implementation of CP and CE practices and to provide ethical and sustainable business development.
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•Conducted an extensive literature review to extract a broad range of Industry 4.0 enablers and validated.•Determining the preference and importance of enablers and sub-enablers by applying IVFS-AHPD.•Fuzzy Evaluation Method was used to obtain the readiness score of Industry 4.0 enablers.•Proposed a novel framework for assessing Industry 4.0 enablers in the context of ethical business development.
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