Multi-criteria linguistic interval group decision-making approach

For group decision-making problems with linguistic assessment information, a new method based on two-tuple and WC-OWA operator is proposed, in which the criteria＇s weights and the decision-makers＇ preference information might take the form of linguistic grade, or might be between two continuous linguistic grades, or might be linguistic interval, or might be default. In this method, all linguistic values are transformed into two-tuple, and an aggregative decision-making matrix is obtained by using interval operation. The group aggregative values of each criterion on alternatives are computed by using a WC-OWA operator, the aggregative values on alternatives are worked out, and transformed into two-tuple. And the rank of the alternatives is obtained by using the order property of two-tuple. An example shows the feasibility and effectiveness of the proposed method.

Cubic q-Rung Orthopair Fuzzy Linguistic Set and Their Application to Multiattribute Decision-making with Muirhead Mean Operator

The objective of this paper is to present a new concept,named cubic q-rung orthopair fuzzy linguistic set(Cq-ROFLS),to quantify the uncertainty in the information.The proposed Cq-ROFLS is a qualitative form of cubic q-rung orthopair fuzzy set,where membership degrees and nonmembership degrees are represented in terms of linguistic variables.The basic notions of Cq-ROFLS have been introduced and study their basic operations and properties.Furthermore,to aggregate the different pairs of preferences,we introduce the Cq-ROFL Muirhead mean-(MM),weighted MM-,dual MM-based operators.The major advantage of considering the MM is that it considers the interrelationship between more than two arguments at a time.On the other hand,the Cq-ROFLS has the ability to describe the qualitative information in terms of linguistic variables.Several properties and relation of the derived operators are argued.In addition,we also investigate multiattribute decision-making problems under the Cq-ROFLS environment and illustrate with a numerical example.Finally,the effectiveness and advantages of the work are established by comparing with other methods.

Dynamic hesitant fuzzy linguistic group decision-making from a reliability perspective

A dynamic hesitant fuzzy linguistic group decisionmaking(DHFLGDM) problem is studied from the perspective of information reliability based on the theory of hesitant fuzzy linguistic term sets(HFLTSs). First, an approach is applied to transform the dynamic HFLTSs(DHFLTSs) into a set of proportional linguistic terms to eliminate the time dimension. Second, expert reliability is measured by considering both group similarity and degree of certainty, and an optimization method is employed to quantify the linguistic terms by maximizing the group similarity. Third, through computing the attribute stability as well as its reliability, a combination rule which considers both reliability and weight is proposed to aggregate the information, and then the aggregated grade values and degree of stability are used to make a selection. Finally,the application and feasibility of the proposed method are verified through a case study and method comparison.

The Spherical q-Linear Diophantine Fuzzy Multiple-Criteria Group Decision-Making Based on Differential Measure

Spherical q-linearDiophantine fuzzy sets(Sq-LDFSs)provedmore effective for handling uncertainty and vagueness in multi-criteria decision-making(MADM).It does not only cover the data in two variable parameters but is also beneficial for three parametric data.By Pythagorean fuzzy sets,the difference is calculated only between two parameters(membership and non-membership).According to human thoughts,fuzzy data can be found in three parameters(membership uncertainty,and non-membership).So,to make a compromise decision,comparing Sq-LDFSs is essential.Existing measures of different fuzzy sets do,however,can have several flaws that can lead to counterintuitive results.For instance,they treat any increase or decrease in the membership degree as the same as the non-membership degree because the uncertainty does not change,even though each parameter has a different implication.In the Sq-LDFSs comparison,this research develops the differentialmeasure(DFM).Themain goal of the DFM is to cover the unfair arguments that come from treating different types of FSs opposing criteria equally.Due to their relative positions in the attribute space and the similarity of their membership and non-membership degrees,two Sq-LDFSs formthis preference connectionwhen the uncertainty remains same in both sets.According to the degree of superiority or inferiority,two Sq-LDFSs are shown as identical,equivalent,superior,or inferior over one another.The suggested DFM’s fundamental characteristics are provided.Based on the newly developed DFM,a unique approach tomultiple criterion group decision-making is offered.Our suggestedmethod verifies the novel way of calculating the expert weights for Sq-LDFSS as in PFSs.Our proposed technique in three parameters is applied to evaluate solid-state drives and choose the optimum photovoltaic cell in two applications by taking uncertainty parameter zero.The method’s applicability and validity shown by the findings are contrasted with those obtained using various other existing approaches.To assess its stability and usefulness,a sensitivity analysis is done.

Fuzzy multi-criteria decision-making approach with incomplete information based on evidential reasoning

The weights of criteria are incompletely known and the criteria values are incomplete and uncertain or even default in some fuzzy multi-criteria decision-making problems.For those problems,an approach based on evidential reasoning is proposed,in which the criteria values are integrated on the basis of analytical algorithm of evidential reasoning,and then nonlinear programming models of each alternative are developed with the incomplete information on weights.The genetic algorithm is employed to solve the models,producing the weights and the utility interval of each alternative,and the ranking of the whole set of alternatives can be attained.Finally,an example shows the effectiveness of the method.

Studies on Multi-Criteria Decision-Making-Based Healthcare Systems Using the Machine Learning

There is a lot of information in healthcare and medical records.However,it is challenging for humans to turn data into information and spot hidden patterns in today’s digitally based culture.Effective decision support technologies can help medical professionals find critical information concealed in voluminous data and support their clinical judgments and in different healthcare management activities.This paper presented an extensive literature survey for healthcare systems using machine learning based on multi-criteria decision-making.Various existing studies are considered for review,and a critical analysis is being done through the reviews study,which can help the researchers to explore other research areas to cater for the need of the field.

Business Blockchain Suitability Determinants: Decision-Making through an Intuitionistic Fuzzy Method

Blockchain is one of the innovative and disruptive technologies that has a wide range of applications in multiple industries beyond cryptocurrency.The widespread adoption of blockchain technology in various industries has shown its potential to solve challenging business problems,as well as the possibility to create new business models which can increase a firm’s competitiveness.Due to the novelty of the technology,whereby many companies are still exploring potential use cases,and considering the complexity of blockchain technology,which may require huge changes to a company’s existing systems and processes,it is important for companies to carefully evaluate suitable use cases and determine if blockchain technology is the best solution for their specific needs.This research aims to provide an evaluation framework that determines the important dimensions of blockchain suitability assessment by identifying the key determinants of suitable use cases in a business context.In this paper,a novel approach that utilizes both qualitative(Delphi method)and quantitative(fuzzy set theory)methods has been proposed to objectively account for the uncertainty associated with data collection and the vagueness of subjective judgments.This work started by scanning available literature to identify major suitability dimensions and collected a range of criteria,indicators,and factors that had been previously identified for related purposes.Expert opinions were then gathered using a questionnaire to rank the importance and relevance of these elements to suitability decisions.Subsequently,the data were analyzed and we proceeded to integrate multi-criteria group decision-making(MCGDM)and intuitionistic fuzzy set(IFS)theory.The findings demonstrated a high level of agreement among experts,with the model being extremely sensitive to variances in expert assessments.Furthermore,the results helped to refine and select the most relevant suitability determinants under three important dimensions:functional suitability of the use case,organizational applicability,and ecosystem readiness.

Information Security Evaluation of Industrial Control Systems Using Probabilistic Linguistic MCDM Method

Industrial control systems(ICSs)are widely used in various fields,and the information security problems of ICSs are increasingly serious.The existing evaluation methods fail to describe the uncertain evaluation information and group evaluation information of experts.Thus,this paper introduces the probabilistic linguistic term sets(PLTSs)to model the evaluation information of experts.Meanwhile,we propose a probabilistic linguistic multi-criteria decision-making(PL-MCDM)method to solve the information security assessment problem of ICSs.Firstly,we propose a novel subscript equivalence distance measure of PLTSs to improve the existing methods.Secondly,we use the Best Worst Method(BWM)method and Criteria Importance Through Inter-criteria Correlation(CRITIC)method to obtain the subjective weights and objective weights,which are used to derive the combined weights.Thirdly,we use the subscript equivalence distance measure method and the combined weight method to improve the probabilistic linguistic Visekriterijumska Optimizacija I Kompromisno Resenje(PL-VIKOR)method.Finally,we apply the proposed method to solve the information security assessment problem of ICSs.When comparing with the existing methods such as the probabilistic linguistic Tomada deDecisão Iterativa Multicritério(PL-TODIM)method and probabilistic linguistic Technique for Order Preference by Similarity to Ideal Solution(PL-TOPSIS)method,the case example shows that the proposed method can provide more reasonable ranking results.By evaluating and ranking the information security level of different ICSs,managers can identify problems in time and guide their work better.

A Choquet integral-based TODIM method for q-rung trapezoidal fuzzy numbers and its application in group decision-making

Purpose–The purpose of this paper is to develop a multi-attribute group decision-making(MAGDM)method under the q-rung orthopair trapezoidal fuzzy environment,which calculates the interaction between the criteria depending on the proposed q-rung orthopair trapezoidal fuzzy aggregation Choquet integral(q-ROTrFACI)and employ TODIM(an acronym in Portuguese of Interactive and Multi-criteria Decision Making)to consider the risk psychology of decision-makers,to determine the optimal ranking of alternatives.Design/methodology/approach–In MAGDM,q-rung orthopair trapezoidal fuzzy numbers(q-ROTrFNs)are efficient to indicate the quantitative vagueness of decision-makers.The q-ROTrFACI operator is defined and some properties are proved.Then,a novel similarity measure is developed by fusing the area and coordinates of the q-rung orthopair trapezoidal fuzzy function.Based on the above,a Choquet integral-based TODIM(CI-TODIM)method to consider the risk psychology of decision-makers is proposed and two cases are provided to prove superiority of the method.Findings–The paper investigates q-ROTrFACI operator to productively solve problems with interdependent criteria.Then,an approach is proposed to determine the center point of q–ROTrFNs and a q-rung orthopair trapezoidal fuzzy similarity is constructed.Furthermore,CI-TODIM method is devised based on the proposed q-ROTrFACI operator and similarity in q-rung orthopair trapezoidal fuzzy context.The illustration example of business models’solutions and hypertension health management are given to demonstrate the effectiveness and superiority of proposed method.Originality/value–Thepaperdevelops a novelCI-TODIMmethodthat effectivelysolves the MAGDM problems under the premise of fully considering the priority of criteria and the risk preference of decision-makers,which provides guiding advantages for practical decision-making and enriches the application of decision-making theory.

MULTI-CRITERIA UNIVERSITY SELECTION:FORMULATION AND IMPLEMENTATION USING A FUZZY AHP

Collaboration with universities as ＇knowledge factories＇ is increasingly perceived to be an effective and viable solution for firms to gain competitive advantage. One of the main challenges firms face in this area is how to select the best university for collaboration. This selection undoubtedly affects some other strategic activities of firms, such as managing and governing the relationship with the selected university and, most importantly, firm performance. As such, the selection becomes an important strategic decision that deserves a great deal of attention. Thus far, no systematic attempt has been made to investigate this significant area of research. The main purpose of this study is to formulate a decision-making model for university selection. Reviewing existing literature of university-industry relationship yields a list of relevant criteria for this problem. The problem is then formulated as a multi-criteria decision-making （MCDM） model, and a fuzzy AHP is used to provide the solution. To illustrate the model, three Dutch universities are ranked based on the importance of the selected criteria.

The Evaluation and Selection of Outsourcing Suppliers in Mass Customization (MC)

Many MC companies find it necessary to cooperate with a large number of outsourcing suppliers to provide MC products according to customers’ diversified orders.To this end,how to select competitve suppliers for the outsourcing manufacturing of non-core processes is the key to establish strong supply chain ally of MC company as well as make the company more efficient in its core manufacturing processes.A procedure of selecting outsourcing suppliers was presented to identify and find competitive suppliers.The continuous improvement of this procedure was proposed to ensure the optimal supply chain of MC company in the long run.Besides,a multi-criteria evaluation model in the procedure was set up according to MC’s characteristic with fuzzy multi-criteria methods combined to solve the fuzzy problems of criteria weight and qualitative attribute value.A case study of MC manufacturing company was provided to show that the procedure,model and methods are effective to select outsourcing suppliers.

Optimal Route Selection Method Based on Vague Sets

Optimal route selection is an important function of vehicle trac flow guidance system. Its core is to determine the index weight for measuring the route merits and to determine the evaluation method for selecting route. In this paper, subjective weighting method which relies on driver preference is used to determine the weight and the paper proposes the multi-criteria weighted decision method based on vague sets for selecting the optimal route. Examples show that, the usage of vague sets to describe route index value can provide more decision-making information for route selection.

Analysis of Critical Factors in Manufacturing by Adopting a Cloud Computing Service

The advantages of a cloud computing service are cost advantages,availability,scalability,flexibility,reduced time to market,and dynamic access to computing resources.Enterprises can improve the successful adoption rate of cloud computing services if they understand the critical factors.Tofind critical factors,this studyfirst reviewed the literature and established a three-layer hierarch-ical factor table for adopting a cloud computing service based on the Technology-Organization-Environment framework.Then,a hybrid method that combines two multi-criteria decision-making tools—called the Fuzzy Analytic Network Process method and the concept of VlseKriterijumska Optimizacija I Kompromisno Resenje acceptable advantage—was used to objectively identify critical factors for the adop-tion of a cloud computing service,replacing the subjective decision of the authors.The results of this study determinedfive critical factors,namely data access secur-ity,information transmission security,senior management support,fallback cloud management,and employee acceptance.Finally,the paper presents thefindings and implications of the study.

Sustainable food waste management using modified fuzzy improved analytic hierarchy process:a study of Malaysia

Food waste generation is a pressing issue that requires urgent attention and concerted efforts worldwide.The staggering amount of food wasted each year not only wastes valuable resources but also exacerbates environmental,economic,and social challenges.Food Waste Management(FWM)consists of a complex array of criteria and sub-criteria,and treatments which seems interdependent.There is a need to evaluate the FWM with the help of important criteria and sub-criteria and treatments to address this challenge.In this study,we identified four important criteria,21 sub-criteria,and four alternatives of FWM for the case of Malaysia using the integrated approach of literature review and expert opinions.Further,we employed the approach of Modified Fuzzy Improved Analytical Hierarchy Process(IAHP)to corroborate the interrelationships among the identified criteria and sub-criteria,and their associated treatments.This study undertakes linear normalization methods to transform data into comparable numerical values and the Geometric Mean method to handle uncertainty in human judgments.Moreover,the Centroid method is employed to convert fuzzy weights into crisp sets for ease of interpretation.The results indicate that environmental is the most essential criterion,followed by social,economic,and technical.In addition,air and water pollution is identified as the most critical sub-criteria.Black Soldier Fly is discovered as the most sustainable FWM treatment,since it performs the best while meeting all the criteria and sub-criteria assessed.Sensitivity analysis demonstrates that the outputs from the proposed method are robust and reliable.The finding suggests a proper and robust approach to help decision-makers select suitable FWM treatments to tackle various criteria and alternatives especially when handling inconsistent and uncertain judgments during evaluation.

TODIM and TOPSIS with Z-numbers

In this paper, we present an approach that can handle Z-numbers in the context of multi-criteria decision-making problems. The concept of Z-number as an ordered pair Z=(A, B) of fuzzy numbers A and B is used, where A is a linguistic value of a variable of interest and B is a linguistic value of the probability measure of A. As human beings, we communicate with each other by means of natural language using sentences like "the journey from home to university most likely takes about half an hour." The Z-numbers are converted to fuzzy numbers. Then the Z-TODIM and Z-TOPSIS are presented as a direct extension of the fuzzy TODIM and fuzzy TOPSIS, respectively. The proposed methods are applied to two case studies and compared with the standard approach using crisp values. The results obtained show the feasibility of the approach.

PLATFORM SELECTION FOR COMPLEX SYSTEMS:BUILDING AUTOMATION SYSTEMS

Automation systems for buildings interconnect components and technologies from the information technology industry and the telecommunications industry.In these industries,existing platforms and new platforms（that are designed to make building automation systems work） compete for market acceptance and consequently several platform battles among suppliers for building automation networking are being waged.It is unclear what the outcome of these battles will be and also which factors are important in achieving platform dominance.Taking the fuzziness of decision makers＇ judgments into account,a fuzzy multi-criteria decision-making methodology called the Fuzzy Analytic Hierarchy Process is applied to investigate the importance of such factors in platform battles for building automation networking.We present the relative importance of the factors for three types of platforms（subsystem platforms,system platforms,and evolved subsystem platforms）.The results provide a first indication that the set of important factors differs per type of platform.For example,when focusing on other stakeholders,for subsystem platforms,the previous installed base is of importance;for system platforms,the diversity of the network of stakeholders is essential;and for evolved subsystem platforms,the judiciary is an important factor.