Development and validation of fuzzy multicriteria decision making models

A fuzzy multi-criteria decision-making model by associating technique for order preference by similarity to ideal solution with relative preference relation

To accommodate the criterion-referenced student group project assessment approach, this paper proposes a fuzzy group Multi-Criteria Decision Making (MCDM) model. The proposed model can be used to solve student group project assessment problem in particular and generic MCDM problems in general, where the criteria used are often different and can be scored with multiple preference formats. The proposed fuzzy group MCDM model supports seven different preference formats, including preference ordering, utility vector, linguistic term vector, selected subset, fuzzy selected subset, fuzzy preference relation, and normal preference relation. It has been firstly used in the context of Information Systems (IS) student group project assessment.

The role of container logistics centre as home bases for merchandise transportation has become increasingly important. The container carriers need to select a suitable centre location of transshipment port to meet the requirements of container shipping logistics. In the light of this, the main purpose of this paper is to develop a fuzzy multi-criteria decision-making (MCDM) model to evaluate the best selection of transshipment ports for container carriers. At first, some concepts and methods used to develop the proposed model are briefly introduced. The performance values of quantitative and qualitative subcriteria are discussed to evaluate the fuzzy ratings. Then, the ideal and anti-ideal concepts and the modified distance measure method are used in the proposed model. Finally, a step-by-step example is illustrated to study the computational process of the quantitative and qualitative fuzzy MCDM model. The proposed approach has successfully accomplished our goal. In addition, the proposed fuzzy MCDM model can be empirically employed to select the best location of transshipment port for container carriers in the future study.

With the increasing environmental awareness, apparel manufacturers have begun to consider environmental issues in supplier evaluation and selection. It is crucial to assess suppliers based on their environmental performance along with other criteria for supplier selection. This paper addresses the green supplier evaluation and selection problem in global apparel manufacturing by developing a methodological framework for green supplier evaluation and selection based on the triple bottom line principle and a fuzzy multi-criteria decision-making (MCDM) model. First, a green supplier evaluation criteria hierarchy based on the triple bottom line principle is established based on comprehensive literature review, on-site investigation and policy analysis. Then, a fuzzy MCDM model is presented to evaluate and select the best material supplier. Finally, a sensitivity analysis is conducted to verify the effectiveness of the proposed framework. Results show that the proposed framework can handle green supplier evaluation and selection in apparel manufacturing effectively.

A criteria weighting approach by combining fuzzy quality function deployment with relative preference relation

In modern business conditions, where competitiveness is evident across all operational segments, it is necessary to adopt a proactive management approach, i.e., to actively manage business performance. To keep pace with evolving trends and technologies, a daily presence on social networks and an adequate level of product promotion are necessary. This paper proposes a Fuzzy MCDM (Multi-Criteria Decision-Making) model to define the future direction of a perfumery regarding the application of digital marketing, using a two-phase group decision-making process. A total of ten digital advertising variants were considered, combining five social networks: Facebook, Instagram, TikTok, YouTube, and Threads. The results obtained through the application of the original Fuzzy MCDM model indicate that companies should focus their efforts on promoting designer and oriental perfumes via Facebook, Instagram, and TikTok in order to enhance growth and potentially expand their business operations.

The main purpose of this study is to present a systematic methodology based on fuzzy Multi-Criteria Decision-Making (FMCDM) models to help users evaluate computer algebra systems (CAS). CAS is a software package for the manipulation of mathematical formulas. The suggested methodology is user-centred which involves users' subjective evaluation judgments. User judgments are represented by means of fuzzy linguistic modelling techniques. An evaluation criteria framework based on the concept of the usefulness of CAS is developed. Next, two FMCDM models – fuzzy Analytical Hierarchy Process (FAHP) and fuzzy Technique for Order Preference by Similarity to Ideal Solution (FTOPSIS) are proposed for the evaluation procedure. The FAHP is applied to determine the relative importance weights of qualitative evaluation criteria; the FTOPSIS is applied to rank the CAS alternatives. The illustrated case study demonstrates the applicability and effectiveness of the proposed methodology.

Analysis of the benefit generated by using fuzzy numbers in a TOPSIS model developed for machine tool selection problems

Stakeholders in hospitality and tourism industries are involved in many decision-making scenarios. Multi-criteria decision-making (MCDM) methods have been widely used in hospitality and tourism industries. Although some articles summarised the applications of MCDM models in hospitality and tourism industries, they ignored the fuzziness of individual cognition in an uncertain environment. In addition, these surveys lacked a comprehensive overview from the perspective of bibliometrics analysis and content analysis regarding the whole hospitality and tourism industries. To analyse the applications of fuzzy MCDM methods in hospitality and tourism industries and further explore future research directions, this article reviews 85 selected papers published from 1997 to 2022 regarding fuzzy MCDM models applied in hospitality and tourism industries. Through analysing the results of bibliometric analysis, methodologies and applications, we found that analytic hierarchy process (AHP) and TOPSIS methods are the most widely used MCDM methods, and tourism evaluation, hotel evaluation and selection, tourism destination evaluation and selection are the most attractive research issues in hospitality and tourism industries. Finally, future research directions are proposed from three aspects. This article provides insights for researchers and practitioners who have interest in fuzzy MCDM models in hospitality and tourism industries.

Evaluating selection of logistic centre location is basically determined by decision makers' subjective perceptions and feelings towards each of the evaluated criterion, so it is more reasonable to deal this problem with fuzzy decision model. Fuzzy AHP (Analytic Hierarchy Process) is proposed to determine the rank in logistic centre location scheme evaluation. In order to include the domain expertise into the decision process and improve evaluation performance, we develop a fuzzy MCDM (multicriteria decision making) model to modify the fuzzy AHP weights based on the entropy technique, by making use of the decision matrix information through Delphi method. We apply fuzzy comprehensive evaluation algorithm to optimize selection location for logistic centre. The rank result indicates this model is a feasible and practical decision support model which analyses both the qualitative and quantitative factors.

Due to urbanization and industrialization pollution level increases. Air pollution directly affects to human health. Air Quality Indices (AQI) method is related to measuring the concentration of different pollutants PM10, NO2, SO2 and other pollutants. The fuzzy Logic air quality index calculates in single value of AQI defines limits 0 to 1. In this study, a comparison of air quality data of three cities was conducted with the help of fuzzy logic algorithm. It used to evaluating Indices through fuzzy multi criteria decision making (MCDM) framework in which linguistic terms of experts opinion and perception, accordingly computing matrix is constructed for sub criteria. There are five linguistic terms used in this framework to create membership functions such as high significant, significant, average significant, low significant and not significant. The three cities, Bangalore, Mysore, and Hubli-Dharwad air quality datas was taken for analysis and evaluating indices during pre-COVID years (2017, 2018, and 2019). The AQI value shows that Bangalore has the highest pollution level while Mysore has the lowest. Using the fuzzy theory, results show that Bangalore and Hubli-Dharwad decrease in pollution level by -0.074921% and -0.04797%. Negative sign shows the decrease pollution level while Mysore increase pollution level by 0.011792%. Overall the results show that AQI of Mysore city is low compared to Bangalore and Hubli-Dharwad. Also, this study reveals air quality disseminated through industrial processes and automobile emissions in India cities during pre-COVID pandemic years.Graphical abstract

Supplier selection is a crucial task in supply chain management, and good supply chain management is essential to a company's ability to develop sustainably and gain the trust and satisfaction of its customers. In modern supply chain management, supplier selection often takes the form of a multi-criteria decision-making (MCDM) problem. Thus, to solve this problem, this study formulated a novel fuzzy MCDM model, which is based on the fuzzy data envelopment analysis model. This novel approach can transform the linguistic variables of assessment criteria into well-founded quantitative data for calculation. Moreover, our approach can effectively discriminate between decision-making units (both efficient and inefficient) to aid managers in identifying the most suitable suppliers. We hope that our model can provide scholars and managers with new insights into solving the MCDM problem in supplier selection.

For airlines, service is regarded as an essential item in their enterprises, and thus they emphasize service performance on management. Due to varied messages’ imprecision and vagueness, the assessment of airline service performance is a fuzzy multi-criteria decision-making (FMCDM) problem for management. In FMCDM problems, classical multi-criteria decision-making (MCDM) methods, including simple additive weighting (SAW), have been extended into FMCDM methods to encompass imprecise and vague messages. The generalizations were first used in FMCDM with independent evaluation criteria, and then FMCDM could be further associated with quality function deployment (QFD) to resolve the tie of the dependent evaluation criteria. Alternative ratings and criteria weights of FMCDM were commonly presented by general (i.e., triangular or trapezoidal) fuzzy numbers. Recently, FMCDM with independent evaluation criteria under an interval-valued fuzzy environment was proposed; however, FMCDM with dependent evaluation criteria under the environment has scarcely been mentioned for high computation difficulty. Moreover, QFD has been generalized under a general fuzzy environment but not an interval-valued fuzzy environment. However, interval-valued fuzzy numbers can present more messages than triangular or trapezoidal fuzzy numbers. Additionally, the assessment of airline service performance using several criteria is not only an FMCDM problem but also a problem with dependent evaluation criteria. In this paper, we generalize QFD and SAW under an interval-valued fuzzy environment for the assessment of airline service performance with dependent evaluation criteria for obtaining more messages. By the association of QFD and SAW, the computation tie of the dependent evaluation criteria corresponding to the interval-valued fuzzy numbers is resolved and more messages are gained for FMCDM.

Prioritization of renewable energy alternatives by using an integrated fuzzy MCDM model: A real case application for Turkey

IT/IS represents a substantial financial investment for many organizations. Making IT project portfolio decision is difficult, because long lead times of IT project and market and technology dynamics lead to unavailable and unreliable collected data for portfolio management. This uncertainty has been modeled using fuzzy concepts. We need a collective model that will help decision-makers evaluate potential new investment projects in an easy, cost-effective, and collective manner. Hence, we propose a new approach based on the fuzzy multi-criteria decision model (FMCDM) and a fuzzy binary multi-objective linear programming model, featuring a 2-stage evaluation and selection process with 19 criteria for IT/IS investment. At the first stage, evaluation, all stakeholders in a corporation can decide the relative weights they give to the criteria when they evaluate a new IT/IS project by using linguistic values. Experts can also use linguistic values to evaluate all candidates easily. Only an Excel worksheet is needed to obtain an evaluation result. The results of FMCDM of the aforementioned are treated as input of a fuzzy binary mathematical programming model as coefficients of objective functions, which is the second stage of the proposed model. In the second stage, selection, we have developed a fuzzy binary mathematical programming model in order to find an optimum combination of investment portfolio considering a multi-objective measurement function in three ways: to maximize the benefit, to maximize the confidence level and to minimize the cost of projects in a complete ambiguous condition, when their initial investment costs, profits, confidence levels, resource requirements and total available budgets are assumed to be uncertain. We solve it in Lingo 10.0 through a Branch and Bound algorithm. In this paper, for the first time we have developed a model for IT/IS project portfolio selection in presence of uncertainty that is combination of fuzzy multi-criteria decision making and fuzzy mathematical programming with 19 criteria that is compatible with the nature of IT projects. We conduct a case study to show how this model can be used and discuss the results.