Fuzzy Analytic Network Process Method Research Articles

Enhancing Decision-Making Processes in the Complex Landscape of the Taiwanese Electronics Manufacturing Industry through a Fuzzy MCDM Approach

This research proposes a hybrid multi-criteria decision-making (MCDM) framework for workforce recruitment in Taiwan’s electronics manufacturing companies, an area with limited research. First, a comprehensive review of existing literature and interviews with industry experts were conducted to compile a list of decision-making criteria and sub-criteria relevant to workforce selection in Taiwan’s electronics industry. The Fuzzy Delphi Method (FDM) was then applied to identify and retain the most critical criteria while eliminating the less important ones. Next, Interpretive Structural Modelling (ISM) was used to calculate the interdependencies among the identified factors. Finally, based on these relationships, the Fuzzy Analytic Network Process (FANP) was employed to calculate the relative importance weights of the criteria and sub-criteria. These weights were then used to rank the criteria, identifying the most important ones and aiding in decision-making. The findings indicate that the proposed method provides a structured and assessable model for making informed decisions in workforce recruitment, particularly in the challenging environment of Taiwan’s electronics manufacturing industry, which faces a shortage of skilled labor. The research presents three primary contributions: the development of a systematic criteria selection technique using FDM, the establishment of consistent criteria relations for decision-makers using ISM, and the proposal of an application model employing the FANP method to identify and rank appropriate criteria for hiring new employees. The study highlights work attitude, adaptability to the environment, and work ability as major criteria. It also emphasizes the importance of discipline compliance, a positive attitude, and adherence to health and safety protocols as the top sub-criteria for workforce selection.

APPLICATION OF FUZZY ANALYTICAL NETWORK PROCESS IN DETERMINING THE CHOICE OF AREAS OF INTEREST

The Untan Statistics Study Program offers students a choice of areas of interest to develop competencies, attitudes, and skills. This study aims to analyze the decision to determine the choice of field of interest according to lecturers and students using the Fuzzy Analytical Network Process (FANP) method. A combination of ANP methods and Fuzzy logic, FANP is used to model and analyze complex networks of several factors determining the choice of areas of interest. The step in this study begins with the determination of the criteria and sub-criteria used for tissue formation. Then a comparison was carried out in pairs using the Fuzzy scale, so that the calculation of the global weight value of each criterion and sub-criteria was obtained. The resulting weight can be used for decision making. Data in research affects the opinions of lecturers and students. The decision obtained using the FANP method in this study is in the opinion of lecturers and students that the fields of business and finance are priority alternatives with the highest weight of 44.5%. The second priority with a weight of 37.5%, namely social and industrial interests, and the environmental and disaster sector occupies the last priority with a weight of 18%.

An Integrated Fuzzy Analytic Network Process and Fuzzy Regression Method for Bitcoin Price Prediction

Predicting the prices of cryptocurrencies is more complicated than that of classical financial assets because they do not seem to have reached the maturity stage of their life. In addition, many known and unknown factors may affect Bitcoin prices; these factors and their importance seem to be changing faster than other financial assets. Therefore, the data used to predict the prices of cryptocurrencies can be considered big data challenging to manage due to their volume, variety, and variability. This study presents an integrated approach to managing the data when predicting the Bitcoin price. We first prepare a list of factors affecting the Bitcoin price. We then use the Fuzzy Analytic Network Process (FANP) to screen these factors and select the most important ones based on the experts’ opinions. The selected factors are considered independent variables affecting the Bitcoin price. Next, we extract a fuzzy regression model using the historical data in which the Bitcoin price is considered the dependent variable. Finally, this model is validated with different confidence levels, and the appropriate level is selected to predict the Bitcoin price. The results show that Bitcoin prices fall within the forecasting intervals obtained from the fuzzy regression model for a 99% confidence level. Unlike crisp regression models, the fuzzy regression model used in this study does not predict the Bitcoin price as a crisp value; instead, it predicts the price as an interval value. The contributions of this study are fourfold: (1) identifying the factors affecting the Bitcoin price and investigating their mutual impacts on each other; (2) determining the most influential factors using the FANP method; (3) using fear and greed as essential sentimental independent variables in regression to predict the Bitcoin price; (4) and predicting the Bitcoin price as an interval instead of a crisp value.

A product evaluation and innovation process based on the circular design degree and patents evolution

People have recently become aware of the need to protect the environment. The integration of the circular economy concept and product design has become an essential strategic consideration, and the world is bound to give more attention to circular design. It aims to consider restorability and renewability in stages of the life cycle while doing design, such as the pathway of recycling, disassembling, reusing, and so forth. The purpose is to let waste become resources endlessly and create value continuously. Moreover, facing the demand for constantly changing products, the capability of innovation is also crucial. Hence, a product development process with the notion of circular design and innovative methods with the patent trend is incredibly important, but as we know so far there are few such approaches available, which motivates our study.To begin with, this study identifies five circular design criteria and forty elements to develop a framework for establishing a product design evaluation system for the waste electrical and electronic equipment products from the perspective of the product life cycle and operation procedure. The performance index of circular design degree (CDD) is created for the evaluation system using the Fuzzy Analytic Network Process method. Then, the product design can be evaluated to identify the criteria and elements with a lower CDD score for improvement. In addition, this study uses the TRIZ tool inventive principle from the contradiction matrix to find suitable patents, meanwhile, we use product attributes to find their evolution trends. Finally, after combining product evolution trends and patents, product innovative ideas are generated for suggestions to product designers. A small household electric appliance is used as a case study for illustrating the usefulness of the proposed methodology and guiding the product designers on how to improve and innovate their products with circular design consideration.

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. To find critical factors, this study first reviewed the literature and established a three-layer hierarchical 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 adoption of a cloud computing service, replacing the subjective decision of the authors. The results of this study determined five critical factors, namely data access security, information transmission security, senior management support, fallback cloud management, and employee acceptance. Finally, the paper presents the findings and implications of the study.

Hospital disaster resilience: development of an assessment tool using expert panel and fuzzy analytical network process

PurposeResilient hospitals have the vital role in reducing mortality, severity of injuries by providing required emergency services during accidents and disasters. This study aims to identify and prioritize key indicators on hospital resilience.Design/methodology/approachThis cross-sectional study was conducted in 2019. The draft of the indicators obtained from the systematic review of the previous study was finalized, with three expert panel sessions and 14 experts in resilience fields. The outputs of these sessions were divided into three domains including constructive resilience, infrastructural resilience and administrative resilience, 17 sub-domains and 71 indicators. Then fuzzy analytic network process method was used to weight and prioritize the final indicators of hospital disaster resilience.FindingsAdministrative resilience, logistic and financial management and strategic outsourcing agreement allocated the highest weight as domain, sub-domains and indicators, respectively. The weight of each sub-domain and indicator was also determined.Originality/valueInvestigating the weight of domains, sub-domains and indicators shows the importance of managerial and operational issues in hospital resilience. By using the indicators and relative weights, a tool for measuring hospital disaster resilience can be created in further studies. The output of these assessments is effective in promoting safety and increasing awareness of hospital managers and health policymakers.

DECISION SUPPORT SYSTEM FOR SMARTPHONE RECOMMENDATION: THE COMPARISON OF FUZZY AHP AND FUZZY ANP IN MULTI-ATTRIBUTE DECISION MAKING

Previous researches outlined the advantages of the Analytical Hierarchy Process (AHP) and Analytic Network Process (ANP) methods in solving Multi-Attribute Decision Making (MADM) problems. The advancement of the above methods was continually developed as an effort to cover up various weaknesses. Mainly related to the consistency and linguistic variables in translating the expert opinions. Thus, it initialized the emergence of Fuzzy AHP (F-AHP) and Fuzzy ANP (F-ANP). Due to the restricted operation of these algorithms in smartphone selection, this research attempted to investigate the effectiveness of both methods in providing the analysis of criteria weight, the final recommendation weight, the product recommendation weight, and the execution time in DSS-SmartPhoneRec application development. A survey of one hundred respondents of University students identified the dominant criteria in selecting the smartphone, namely price, Random Access Memory (RAM), processor, internal memory, and camera. Hence, five alternative products were then chosen as the appropriate smartphones’ recommendations based on the respondent’s preferences. As an automatic tool, a DSS-SmartPhoneRec application was built to analyze and compare between F-AHP and F-ANP methods in resolving the smartphone selection cases. It revealed that the level of consistency of criteria weight, the final weight of recommendation, and the weight that the product-based F-ANP was 40% greater than F-AHP. In terms of execution time, F-AHP had a shorter time than F-ANP. Meanwhile, the comparison of products recommendation from DSS-SmartPhoneRec and a manual test showed that F-ANP was 16% more in line with the respondents’ predilection. In a nutshell, the DSS-SmartPhoneRec administered the devote smartphone recommendations based on the user’s expectation. The comparison analysis furnished a learning outcome for the users in determining the appropriate MADM method tailored to the type of cases.

Developing and evaluating a proposed health security framework in IoT using fuzzy analytic network process method

Internet of Things (IoT) played a significant role in Healthcare. One of the major challenges in IoT health is security. For this reason, regarding the past studies, there is a lack of a comprehensive security framework that encompasses all layers of IoT. This article offers a security framework with four layers of sensor, network, service, and application. These layers help to develop security mechanisms within the proposed framework by providing security solutions. Also, security improvement has been influenced by the Multi Criteria Decision Making (MCDM) technique. To evaluate this framework, a conceptual model was defined with six critical criteria including security, network, services, interoperability, privacy, and reliability. The validity and reliability of this conceptual model were analyzed using SPSS 24 and AMOS 18. After proving the important criteria in the proposed model, we used the MCDM process of fuzzy analytic network process to prioritize the important criteria. The evaluation results of the conceptual model in the proposed framework, after analyzing the routes, show the validity of the proposed criteria. Therefore, in this model, 8 out of 12 communication routes between the criteria have a positive and significant relationship and 4 routes do not. The results of prioritizing important criteria in the research model, using analytic network process method, show that the network criterion, and authentication and validation sub-criteria have the highest priority among the proposed criteria. Thus, it can be decided that security solutions in the network layer and authentication and validation sub-criteria help to develop the proposed security framework.

Investor sentiment index based on intuitionistic fuzzy analytic network process method and empirical analysis1

This paper presents a network index system for assessing investor sentiment. The proposed comprehensive investor sentiment index is based on intuitionistic fuzzy analytic network process (IFANP) and regression model, and is compared with a sentiment

PENERAPAN FUZZY ANALYTIC NETWORK PROCESS (FANP) UNTUK PENENTUAN PRIORITAS KRITERIA PADA PEMILIHAN MAHASISWA BERPRESTASI DI UNESA

The selection of outstanding students needs to be done at each university, so that the potential possessed by students in the form of hard skills and soft skills can be increased and the achievements obtained are better. Hard skills and soft skills can be developed by the students participate in various activities that have been made by the department, faculty, and campus. Outstanding students mentioned in this regard should have a good performance in academic and non academic. In the Achievement Student Selection (Pilmapres) there are several criteria that must be met. To determine the priority criteria that influence in this Pilmapres it is necessary to calculate the weight of each criterion. In this study the Fuzzy Analytic Network Process (FANP) method is used. Fuzzy Analytic Network Process (FANP) method is a combination of fuzzy method and Analytic Network Process (ANP) method. By using the FANP method it can be seen that the criteria which are very influential are the criteria for the achievement of field competition where the weight is 22%, the award rate criteria is 17,9%, the weighting criteria for the superior performance results is 14,1%, the weighting criteria for the superior performance award is 11,9%, the weighting of the role criteria in the superior achievements was 11,6%, the weighting of the registrant identity criteria was 10,9%, and the weighting of the career criteria in the organization was 7,6%. For the sub-criteria that influence in the Pilmapres, among others, are innovative findings which have a weight of 27,6%, a work subcriteria 26,9% and a product subcriteria 25,6%.

Allocation of Maltodextrin Raw Material Orders by Fuzzy Analytic Network Process (FANP) and Goal Programming Methods (Study Case: PT. Neopangan Selaras Indonesia)

PT. Neopangan Selaras Indonesia is a food company that produces seasoning. One of the raw materials with the most frequent problems with delays and wrong allocation is maltodextrin, which is 72%. To determine the need for evaluation for each maltodextrin supplier using the Fuzzy Analytical Network Process (FANP) and Goal Programming methods. The existence of a method of merging these two studies. Determination of the proportion of the criteria and sub-criteria in the company by minimizing changes in each assessment. The FANP method in this study produced criteria and assessments of each supplier that could be considered in the allocation of the purchase of raw materials. The best supplier of weights was obtained by PT. Indo Asia Tirta Manunggal (0.4421). The Goal Programming method provides a solution by minimizing total costs by considering the price of each supplier, maximizing the purchase value by considering the weight generated. This method produces a solution that produces a total cost of 0.134%, increasing the purchase value of 1.143%.

A Hybrid Fuzzy Decision-Making Approach to Select the Best online-taxis business

In the recent decade, significant growth of internet-based platforms and changes in people’s moving preferences has led to an increase in the electronic taxis businesses. Hence, investigating the factors affected by such businesses can help increase their profits and, at the same, time their customers’ satisfaction level. In this study, a hybrid fuzzy decision-making approach is proposed to examine the best online-taxis business selection problem. The proposed framework firstly determines the interrelationships between criteria and sub-criteria, by applying the Fuzzy Decision making trial and evaluation laboratory (FDEMATEL) method. Then, the weights of the criteria and sub-criteria are calculated using an integrated Fuzzy Best-Worst Method (FBWM) and the Fuzzy Analytic network process (FANP). In this regard, at first, the local weights of indicators are calculated using the FBWM regardless of interrelationships between them. Then, the final (i.e. global) weights of indicators, considering their interrelationships, are measured employing the FANP method. Afterwards, the feasible alternatives are prioritized by employing the Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (FTOPSIS) method. For each step of the proposed framework, a questionnaire is designed and distributed between experts. The results show that the most important criteria and sub-criteria for passengers are cost and reasonable price, respectively. Finally, some managerial insights are provided.

Quantitative Analysis of Requirement Elicitation Techniques through FANP: Security Perspective

The last few decades have shown an incredible rise in the production of different types of software according to the user’s needs. Requirement Elicitation techniques for security requirements are one of the most crucial stage of software development life cycle. Based on the Analytical Network Process (ANP) process, this paper analyzes the weighting of elicitation techniques for security requirements in the production of software applications. In other words, the elicitation strategies of security requirements play an important role in the development of secure software. It also analyzes the relationship between security requirement elicitation techniques and their objectives through the use of ANP method and also demonstrates the application of fuzzy ANP method to achieve higher accuracy. When developing a secure software framework, the results provide a better platform. With these facts in mind, the proposed study will also clarify the priority weights of security requirement elicitation techniques that can be used to analyze trade-offs between competing software security requirement elicitation techniques and provide a new way for developers when constructing the secure software.

A Fuzzy ANP-Based GRA Approach to Evaluate ERP Packages

One of the major problems that most companies face with during the implementation of an ERP system is to determine the best satisfying ERP software based on their needs and expectations. Because an improperly selected ERP software might lead to time loss and increased costs, and in the long run, a loss of market share. Therefore, the ERP evaluation process for companies becomes to a vital point. On the other hand, evaluating ERP software alternatives under a set of criteria leads us to a multiple-criteria decision making (MCDM) problem, and needs to use proper MCDM methods. In the current literature, a number of the MCDM methods have been proposed to solve these kinds of problems, both of which are the analytic network process (ANP) of Saaty, and grey relational analysis (GRA) which has been widely used in solving MCDM selection problems in various fields. Moreover, in this article, the authors used the fuzzy extension of the ANP method to reflect the uncertainty and ambiguity of decision maker(s) into problem in order to reach more reliable solution. As the fuzzy ANP method was used to calculate the priority weights of the evaluation criteria, the GRA method with fuzzy interval-values was employed to rank a set of the possible ERP software alternatives. The proposed approach was also validated in a case study to show its applicability to potential readers and practitioners.

HHI-based evaluation of the European banking sector using an integrated fuzzy approach

PurposeThis paper aims to evaluate the market concentration and competition in the European Banking Sector using an integrated multi-criteria decision-making approach under the fuzzy environment.Design/methodology/approachThe hybrid model combining fuzzy decision-making trial and evaluation laboratory (DEMATEL), fuzzy analytic network process (ANP) and fuzzy VIKOR methods is applied to measure the market competition and concentration in the European Banking Sector. For this purpose, two academicians and one expert from banking sector with at least five-year experiences are selected to evaluate the dimensions, criteria and alternatives. The academicians are also appointed to define the decision-making problem and determine the dimensions and the criteria on the basis of related literature. The implementation of the model has been constructed in three main phases. The first phase consists of the fuzzy DEMATEL technique for understanding the impact-relation map among the dimensions. The second phase includes the fuzzy ANP method for measuring the relative importance of the criteria. The last phase comprises the fuzzy VIKOR approach to rank the alternatives with the values of the Herfindahl–Hirschman Index (HHI).FindingsTurkey, France, England and Germany are placed in the competitive market structure of the European Banking Sector respectively. Additionally, the comparative results of the study confirm the market shares and the competitive policies of the European and Turkish Banking Sector.Originality/valueThe novelty of the paper is to construct a hybrid multi-criteria decision-making model with the proposed HHI scales under the fuzzy environment and defined competition dimensions and criteria based on the literature for the European Banking Industry.

Selection of optimal renewable energy investment project via fuzzy ANP

Purpose - This study aims to determine the optimal renewable energy investment project providing a guideline to the investors in decision making process. Methodology - This study presents a comprehensive and solid mathematical approach considering the assessment of the ambiguities in the preferences of the decision maker for selection of the optimal renewable energy investment project via fuzzy analytic network process (FANP). FANP captures vagueness along with uncertainties in the evaluation. Findings - After FANP method had been implemented for the considered problem, Hydropower with 31% of importance is selected as optimum renewable energy investment project for the firm. Conclusion- This study provides a realistic assessment of energy resources and the consideration of the ambiguities presented in the preferences of the decision maker

Model Multi Criteria Decision Making with Fuzzy ANP Method for Performance Measurement Small Medium Enterprise (SME)

SMEs have a very important role in the development of the economy in Indonesia. SMEs assist the government in terms of creating new jobs and can support household income. The number of SMEs in Madura and the number of measurement indicators in the SME mapping so that it requires a method.This research uses Fuzzy Analytic Network Process (FANP) method for performance measurement SME. The FANP method can handle data that contains uncertainty. There is consistency index in determining decisions. Performance measurement in this study is based on a perspective of the Balanced Scorecard. This research approach integrated internal business perspective, learning, and growth perspective and fuzzy Analytic Network Process (FANP). The results of this research areframework a priority weighting of assessment indicators SME.

An integrated ANP-VIKOR methodology for sustainable supplier selection with interval type-2 fuzzy sets

Recently, sustainable supplier chain management (SSCM) has gained increasing attentions both from corporate and academic. A large number of multiple criteria group decision-making (MCGDM) methods for sustainable supplier selection have been developed. In this paper, considering that the interval type-2 fuzzy sets (IT2FSs) exhibit some interesting properties for handling uncertain information and high order imprecision, we integrate the ANP (analytical network process) method and the VIKOR (ViseKriterijumska Optimizacija I Kompromisno Resenje) method under interval type-2 fuzzy environment to solve supplier selection problem in SSCM. The proposed method consists of two steps. First, we obtain the weights of criteria via the ANP method. Then, based on the weights of criteria presented in step 1, a compromise solution will be proposed with the aid of VIKOR method. A numerical example is presented to show the decision process in detail. In addition, a comparative analysis with interval type-2 fuzzy ANP method and TOPSIS method is also presented to verify the validity of the proposed method.

Optimal maintenance strategy selection based on a fuzzy analytical network process

Maintenance is one of the most crucial issues in today’s competitive manufacturing environment. Nowadays, productive methods are used in manufacturing plants to improve operations capabilities, which alternatively change business environmental factors leading to a competitive market. Consequently, selection and illustration of an optimal maintenance strategy play a significant role in achieving these goals. Also, lack of an integrated model is felt, one that consists of available criteria and options, a systematic approach in setting maintenance instructions and robust maintenance decision-making. So, based on the fuzzy analytical network process (FANP) method, which composes criteria and options, a new approach to selecting optimal maintenance strategy is proposed in this article. Here, using multi-attribute decision-making in conjunction with application of fuzzy numbers structure has been regarded as an efficacious method for determining the significance of each criterion and option. The criteria that are considered in the FANP method are organization, safety, administration, staff, and technical requirements. The options (strategies) that are taken into consideration in this study are time-based preventive maintenance, corrective maintenance, condition-based maintenance, reliability-centered maintenance, and predictive maintenance. After implementing the method proposed for a 5-MW powerhouse (a case study undertaken for the purpose of this study), the predictive maintenance strategy was selected. According to expert opinions, it is the administrative and staff requirements that must be highlighted for selecting the best strategies.

An integrated weighted fuzzy multi-objective model for supplier selection and order scheduling in a supply chain

This paper presents a new weighted fuzzy multi-objective model to integrated supplier selection, order quantity allocation and customer order scheduling problem to prepare a responsive and order-oriented supply chain in a make-to-order manufacturing system. Total cost and quality of purchased parts as well as the reliability of on-time delivery of customer orders are regarded as the objectives of the model. On the other hand, flexible suppliers can contribute to the responsiveness and flexibility of entire supply chain in the face of uncertain customer orders. Therefore, a mathematical measure is developed for evaluating the volume flexibility of suppliers and is considered as the other objective of the model. Furthermore, by considering the effect of interdependencies between the selection criteria and to handle inconsistent and uncertain judgments, a fuzzy analytic network process method is used to identify top suppliers and consider as the last objective. In order to optimise these objectives, the decision-maker needs to decide from which supplier to purchase parts needed to assemble the customer orders, how to allocate the demand for parts between the selected suppliers, and how to schedule the customer orders for assembled products over the planning time horizon. Numerical examples are presented and computational analysis is reported.