Fuzzy Analytic Hierarchy Process Model Research Articles

Index design and safety evaluation of pesticides application based on a fuzzy AHP model for beverage crops: tea as a case study.

A fuzzy analytic hierarchy process (AHP) is shown to be an effective methodology for multiple criteria decision-making from various heterogeneous data. Despite application of AHP to some decision-making problems in agriculture, research on AHP utilization for screening the safe use of pesticides for tea plantations based upon multiple criteria has not been reported. The overall safety chain from tea plantation to tea manufacture to tea cup after pesticides had been sprayed on a tea plantation was considered and the AHP network was constructed at two levels with two categories, tea-related parameters and pesticide toxicity. Seven criteria were selected as safety indexes, half-lives of pesticides on the tea plant (T1/2 ), water solubility (Ws), vapor pressure (Vp), acceptable daily intake (ADI), acute oral lethal dose of pesticides to rat (LD50 ), and ecotoxicity of pesticides including LD50 to bees and LD50 to aquatic organisms. According to the AHP, water solubility was the most important factor in the evaluation pesticide safety for use on a tea plantation, followed by the half-lives of the pesticides on the tea plant and the acceptable daily intake. Combined with the scale of seven criteria and relative weight (W), 48 pesticides with an overall score (S) < 25 could be regarded as relatively safe compounds when applied in tea plantations. An AHP approach was suggested to evaluate the safe use of pesticides on tea plantations. This study provides a new idea for the evaluation of safety in beverage crops. © 2019 Society of Chemical Industry.

A fuzzy analytic hierarchy process model for customers’ bank selection decision in the Kingdom of Bahrain

Ranking the priorities of customers in selecting commercial banks is essential for the elaboration of bank development strategies. The purpose of this paper is to implement a fuzzy analytic hierarchy process (FAHP) multi-criteria decision model for commercial banks selection by customers. Six criteria and five Bahraini retail commercial banks are used to formulate a decision problem structured in three-level hierarchies. After structuring the hierarchies, the FAHP is applied to determine the relative weights of the evaluation criteria. The results show that most selected banks focus on pricing strategy more than bank facilities. Interest rates on credits and deposits as well as transaction costs are the main factors used to attract customers. The study provides several implications for decision makers to develop the appropriate strategies towards their customers’ preferences. An extensive numerical example for sensitivity analysis demonstrates the strength and plausibility of the FAHP approach.

Fault diagnosis and prioritisation in sugar industry: a fuzzy-AHP approach

The main aim of this study is to develop a fuzzy analytic hierarchy process (FAHP) model to prioritise the faults of the sugar industry. Although the concept of fault diagnosis has been discussed in previous studies, fault diagnosis of sugar industry is not investigated yet. To fill this gap, this study is carried out in three main phases as follows. Firstly, the general faults of industries are developed from the previous literature. Secondly, the developed faults are investigated with regard to their availability in sugar industry. Finally, a FAHP model is applied to prioritise the faults of sugar industry. According to the results, old technology, improper financing, poor research and development and lack of creativity and innovation are four main faults of sugar industry, respectively. Some managerial implications are suggested to deal with these faults and improve the performance of this industry.

Risk assessment of karst collapse using an integrated fuzzy analytic hierarchy process and grey relational analysis model

A karst collapse, as a natural hazard, is totally different to a normal collapse. In recent years, karst collapses have caused substantial economic losses and even threatened human safety. A risk assessment model for karst collapse was developed based on the fuzzy analytic hierarchy process (FAHP) and grey relational analysis (GRA), which is a simple and effective mathematical algorithm. An evaluation index played an important role in the process of completing the risk assessment model. In this study, the proposed model was applied to Jiaobai village in southwest China. First, the main controlling factors were summarized as an evaluation index of the model based on an investigation and statistical analysis of the natural formation law of karst collapse. Second, the FAHP was used to determine the relative weights and GRA was used to calculate the grey relational coefficient among the indices. Finally, the relational sequence of evaluation objects was established by calculating the grey weighted relational degree. According to the maximum relational rule, the greater the relational degree the better the relational degree with the hierarchy set. The results showed that the model accurately simulated the field condition. It is also demonstrated the contribution of various control factors to the process of karst collapse and the degree of collapse in the study area.

Difference Analysis of Ecological Security Assessment Based on FAHP

In this study, the important city of Guanzhong Plain-Weinan, was studied and its ecological security index changed from the year of 2000 to 2012. The stress-state-response (PSR) model was used to establish an ecological security assessment system based on agricultural development cities. The method of quantitative research including 12 indicators based on the fuzzy analytic hierarchy process (FAHP) model was constructed, and the main aspects such as the natural environment, economic society, and human activities were designed. The results showed that from 2000 to 2012, the area of ecological security and stability is gradually increasing, and the stability of the ecological environment is enhanced. The ecological security level in the central region of the country has developed well in the past 10 years, but the ecological security level in some areas has gradually increased in edge area.

Sustainable Supplier Selection Process in Edible Oil Production by a Hybrid Fuzzy Analytical Hierarchy Process and Green Data Envelopment Analysis for the SMEs Food Processing Industry

Today, business organizations are facing increasing pressure from a variety of sources to operate using sustainable processes. Thus, most companies need to focus on their supply chains to enhance sustainability to meet customer demands and comply with environmental legislation. To achieve these goals, companies must focus on criteria that include CO2 (carbon footprint) and toxic emissions, energy use and efficiency, wastage generations, and worker health and safety. As in other industries, the food processing industry requires large inputs of resources, which results in several negative environmental effects; thus, decision-makers have to evaluate qualitative and quantitative factors. This work identifies the best supplier for edible oil production in the small and medium enterprise (SME) food processing industry in Vietnam. This study also processes a hybrid multicriteria decision-making (MCDM) model using a fuzzy analytical hierarchy process (FAHP) and green data envelopment analysis (GDEA) model to identify the weight of all criteria of a supplier’s selection process based on opinions from company procurement experts. Subsequently, GDEA is applied to rank all potential supplier lists. The primary objective of this work is to present a novel approach which integrates FAHP and DEA for supplier selection and also consider the green issue in edible oil production in uncertain environments. The aim of this research is also to provide a useful guideline for supplier selection based on qualitative and quantitative factors to improve the efficiency of supplier selection in the food industry and other industries. The results reveal that Decision-Making Unit 1 (DMU 1), DMU 3, DMU 7, and DMU 9 are identified as extremely efficient for five DEA models, which are the optimal suppliers for edible oil production. The contributions of this research include a proposed MCDM model using a hybrid FAHP and GDEA model for supplier selection in the SME food processing industry under a fuzzy environment conditions in Vietnam. This research also is part of an evolution of a new hybrid model that is flexible and practical for decision-makers. In addition, the research also provides a useful guideline in supplier selection in the food processing industry and a guideline for supplier selection in other industries.

A Multi-Criteria Decision Making (MCDM) for Renewable Energy Plants Location Selection in Vietnam under a Fuzzy Environment

In the context of increasing energy demands in Vietnam, and as a result of the limited supply of domestic energy (oil/gas/coal reserves are exhausted), the potential for renewable energy sources in Vietnam is significant. Thus, building wind power plants in Vietnam is necessary. Access to this type of renewable energy not only contributes to society’s energy supply but also helps to save energy and reduce environmental pollution. Although some works have reviewed applications of the Multi-Criteria Decision Making (MCDM) model in wind power plant site selection, little research has focused on this problem in a fuzzy environment. This is the reason why a hybrid Fuzzy Analytic Hierarchy Process (FAHP) and The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) are developed for wind power plant site selection in Vietnam. In the first stages of this research, an FAHP model is proposed for determining the weight of each potential location for building a wind power plant, based on qualitative and quantitative factors. A TOPSIS is applied for ranking all potential alternatives in the final stage. The authors collected data from seven locations, which have good conditions for investment in a wind power plant. The results indicate that Binh Thuan (Binh Thuan Province is located on coast of South Central Vietnam) is the best place for building a wind power plant in Vietnam. The contributions of this work proposed an MCDM approach under fuzzy environments for wind power plant location selection in Vietnam. This paper also resides in the evolution of a new approach that is flexible and practical for a decision-maker. This work also provides a useful guideline for wind power plant location selection in others countries.

Evaluation of landslide susceptibility models: A comparative study on the part of Western Ghat Region, India

The present research focuses on evaluating the effectiveness of landslide susceptibility using fuzzy gamma operator (FGO) and analytical hierarchy process (AHP) model in part of Western Ghat, India. The landslide inventory data and various causative factors were used to generate the landslide susceptibility index (LSI) map using geospatial technology. The LSI map classified into five classes and finally validated by Area Under Curve (AUC) method for accuracy assessment. The AUC result of success and prediction rates depicts that FGO model has high accuracy value than AHP model. However, both models are highly correlated (r = 0.976). Among the all causative factors slope, lithology, land use land cover, geomorphology and lineament proximity are strongly correlated (r = >0.9) with the landslide susceptibility between the two models. The research outcome will be helpful for future spatial planning in the study region.

Fuzzy Analytical Hierarchy Process Method to Determine the Quality of Gemstones

The selection of quality gemstones requires a special ability to select and assess the quality of gemstones to be traded. The diversity of types of gemstones and consumers becomes an obstacle in itself when the knowledge and ability of individuals to analyze the quality of gemstones is minimal. The decision-making method used is Fuzzy Analytical Hierarchy Process (F-AHP) method which is widely used in various sectors. F-AHP is easy to adapt to many decision issues; the research proposes a decision-making system using the F-AHP algorithm to analyze the quality of gemstones. The results obtained with the use of F-AHP model in the selection of quality gemstones show the highest quality of gemstones of all stones compared, Rubi 1, with a weight value of 0.152942.

The impacts on both family and personal factors for youth entrepreneurship

This paper used the fuzzy analytic hierarchy process (FAHP) model to investigate how family and individual affect the success of entrepreneurship. The results of statistical analysis show that individual competence is the most important factor affecting youngsters’ willingness to start a business. Collaboration ability, interpersonal social skills, and upbringing should also be considered as the important factors for the success of youth entrepreneurship.

Evaluating the key performance indicators for supply chain information system implementation using IPA model

PurposeTo enhance the transparency of the supply chain and ensure proper dissemination of information among the supply chain members in a timely manner, more and more companies are implementing supply chain information system (SCIS). Often the challenge among the organizations is how to go for a proper SCIS implementation and to identify the key performance indicators (KPIs) to evaluate the SCIS. The purpose of this paper is to provide a framework to evaluate the KPIs for SCIS of SCISs implementation from user’s perspectives.Design/methodology/approachIn this paper, 16 KPIs were identified based on extensive literature survey. A fuzzy analytic hierarchy process (AHP) model is constructed to measure the users’ perceived importance and satisfaction for the KPIs. Subsequently, based on these two measurements, an importance-performance analysis (IPA) model along with a customer satisfaction attitude (SA) index is developed to categorize and prioritize the KPIs. As an empirical study, SCIS users across five industries belonging to different sectors were investigated to validate the model.FindingsAn IPA model along with a customer SA index is developed based on a fuzzy AHP model to evaluate the KPIs and provide the priorities of their improvement. Based on this result, some management implications and suggestions are proposed.Research limitations/implicationsThe study was limited to five organizations. More representative samples which can be sector specific can ensure better confirmation of the empirical results.Originality/valueThe KPIs identified in the research indicate the nature and dynamics of a complex SCIS implementation. It can serve as a checklist of areas that require attention when implementing a SCIS. The KPIs are presented through grouping in a systemic way. The development of the SAs in IPA model using fuzzy AHP is a novel approach.

Solar Panel Supplier Selection for the Photovoltaic System Design by Using Fuzzy Multi-Criteria Decision Making (MCDM) Approaches

The period of industrialization and modernization has increased energy demands around the world. As with other countries, the Taiwanese government is trying to increase the proportion of renewable energy, especially solar energy resources. Thus, there are many solar power plants built in Taiwan. One of the most important components of a solar power plant is the solar panel. The solar panel supplier selection process is a complex and multi-faceted decision that can reduce the cost of purchasing equipment and supply this equipment on time. In this research, we propose fuzzy MCDM approach that includes fuzzy analytical hierarchy process model (FAHP) and data envelopment analysis (DEA) for evaluation and selection of solar panel supplier for a photovoltaic system design in Taiwan. The main objective of this work is to design a fuzzy MCDM approach for solar panel supplier selection based on qualitative and quantitative factors. In the first step of this research, FAHP is applied to define the priority of suppliers. The AHP combined with fuzzy logic (FAHP) can be used to rank suppliers; however, the disadvantages of the FAHP model is that input data, expressed in linguistic terms, depends on experience of experts and the number of suppliers is practically limited, because of the number of pairwise comparison matrices. Thus, we applied several DEA models for ranking potential suppliers in the final stages. As the result, decision making unit 1 (DMU 1) is the optimal solar panel supplier for photovoltaic system design in Taiwan. The contribution of this research is a new fuzzy MCDM for supplier selection under fuzzy environment conditions. This paper also lies in the evolution of a new approach that is flexible and practical to the decision maker. It provides a useful guideline for solar panel supplier selection in many countries as well as a guideline for supplier selection in other industries.

Software Architectural Quality Assessment Model for Security Analysis Using Fuzzy Analytical Hierarchy Process (FAHP) Method

In the last decade, the greater need for quality software led to the development of quality assessment especially at the software architecture (SA) level. Since software security is an important quality attribute, several models have been evolved to validate the security related issues at the SA level. This paper proposes a Fuzzy Analytical Hierarchy Process (FAHP) with Buckley method for security assessment at the SA level for object-oriented design. FAHP is a Multi-Criteria Decision Making approach which employs linguistic variables as a pair-wise comparison matrix to derive priorities of various selection attributes and sub-attributes. In addition, the proposed work uses genetic algorithm to fill the missing values in the comparison matrix of FAHP. The validation of FAHP model takes place by the use of four versions of apache Tomcat series namely TC 7.0.6, TC 7.0.22, TC 7.0.39 and TC 7.0.47. The obtained results ensure that the proposed FAHP model with Buckley method performs well than existing methods in terms of security index to measure the performance at the SA level and defect density ratio to validate the results.

Supplier Selection Model of the Lithium-ion Battery using Fuzzy AHP and Analysis of BOCR

Although the demand for the lithium-ion battery for electronic consumers and electric vehicles in Indonesia is high, there is no supplier coming from the local manufacturer. The proper selection of suppliers is required by some lithium-ion battery manufacturers (cells, modules, and packs), and Research and Development (R&amp;D) center of the lithium-ion battery with the consideration not only in benefits and cost but also in opportunities and risks. It is important that experts assist the manufacturers and R&amp;D to procure the lithium-ion (materials and cells), through transparent methods that seek a quantitative model to select the right supplier. The main objective of this study is to propose an analytical approach to select suppliers which incorporate Benefits, Opportunities, Costs and Risks (BOCR) concept that comply with the characteristics of the lithium-ion battery industries. A fuzzy Analytical Hierarchy Process (AHP) model is developed by accommodating the vagueness and inaccuracies of expert elections. The result of this research is development of the model obtained from 2 questionnaires given to the expert. Questionnaire 1 was made for the determination of criteria and sub-criteria, while Questionnaire 2 aims to perform pairwise comparisons of existing criteria and sub-criteria. In the selection of the lithium-ion battery suppliers, there are 11 criteria and 40 sub-criteria which are considered. Those criteria are divided into 4 merits and known for their respective global priorities.

Key criteria influencing the choice of Arctic shipping: a fuzzy analytic hierarchy process model

ABSTRACTAs Arctic sea ice shrinks due to global warming, the Northern Sea Route (NSR) and the Northwest Passage (NWP) offer a substantial reduction in shipping distance between Asia and the European and North American continents, respectively, when compared to conventional routes through the Suez and Panama Canals. However, Arctic shipping routes have many problems associated with their use. The main objective of this paper is to identify the key criteria that influence the decisions of shipping operators with respect to using Arctic shipping routes. A multi-criteria decision-making methodology, the Fuzzy Analytic Hierarchy Process, is applied to rank four potential categories of criteria (‘economic’, ‘technical’, ‘political’ and ‘safety’ factors) and their sub-criteria.The results of the analysis suggest that, on aggregate, ‘economic’ is the most important category of influential factors, followed by ‘safety’, ‘technical’ and ‘political’ factors. The paper concludes, however, that the most influential specific sub-criteria relate to risks that lie mainly within the ‘safety’ and ‘political’ domains and that, especially in combination, these overwhelm the importance which is attached to ‘economic’ factors such as reduced fuel use. Finally, the implications of these findings for the future development of Arctic shipping are addressed at a strategic level.

Calculation and Analysis of Ecological Environment Impacts along High-speed Railway

Construction and operation of high-speed railway have significant impacts on the ecological environment within certain range. It is difficult to quantify and analyze effects of different factors. This paper conducts analysis of high-speed railway’s impacts on the ecological environment along the railway comprehensively and systematically. Factors of the ecological environmental impacts are divided into natural ecology, landscape environment, social ecology. Then it proposes specific measurement and calculation method of the secondary factors. Based on the ecological environmental impacts analysis system of high-speed railway, the fuzzy analytic hierarchy process model is built and specific effects of high-speed railway on ecological environment are analyzed.Analysis shows that the main influence of high-speed railway on the ecological environment are natural ecology and social ecological impacts. Consequently, it needs to focus on strengthening the protection of the natural ecological and handling the public interest demands properly during the construction and operation stages of high-speed railway.

Determination of Media Attributes Through Fuzzy Analytical Hierarchy Process and Artificial Neural Network Model

Determination of Media Attributes Through Fuzzy Analytical Hierarchy Process and Artificial Neural Network Model

Comparative Analysis of AHP-TOPSIS and Fuzzy AHP Models in Selecting Appropriate Nanocomposites for Environmental Noise Barrier Applications

Choosing the right material in the design of environmental noise barriers has always been a challenging issue in acoustics. In less-developed countries, the material selection is affected by many factors from various aspects, which makes the decision-making very complicated. This study attempts to compare and assign weights to the most important indices affecting the choice of appropriate noise barrier material. These criteria include absorption coefficient, transparency, tensile modulus, strength at yield, elongation at break, impact strength, flexural modulus, hardness, and cost. For this purpose, experts' opinions was gathered through a total of 13 questionnaires and used for assigning weights by Analytic Hierarchy Process (AHP) and Fuzzy Analytic Hierarchy process (FAHP) techniques. According to the AHP results, impact strength, with only a minor difference of 0.093 compared to the AHP, was recognized as the most important criterion. Finally, the optimal composite material was selected using two different methods; first by Technique for Order-Preference by Similarity to Ideal Solution (TOPSIS) based on the weights obtained from AHP, and next by directly applying the obtained weights from FAHP to the true measured values of parameters. As the results show, in both abovementioned methods, Polycarbonate-SiO2 0.3% with roughened surface (PCSI3-R) received the highest score and was selected as the preferred composite material. Given the close similarity of the results, to determine the superiority of one method over the other, some noise was added to the original data set from the mechanical and acoustic tests and then the variance of the changes in the final orders of preferences was calculated. This indicates the robustness of the method against the measurement errors and noise. The results shows that under the same circumstances, the overall order shift variance in the classic TOPSIS is six times higher than that of the fuzzy AHP method.

A Fuzzy AHP Approach to Comparison of Grant Aid for ODA in Japan

Today, many companies contribute to Official Development Assistance (ODA). The details of ODA are publicised for each project, with contributions and companies listed on the company’s website. The objective of this paper is to evaluate these companies in terms of the best practices that characterise ODA donations in four fields: infrastructure, medical service, education and security. Analytic hierarchy process (AHP) is proposed by T. L. Saaty to evaluate uncertainty in decision problems. Using comparison matrices, the AHP can evaluate the extent of data fit to practical data. In fuzzy analytic hierarchy process (Fuzzy AHP), interval weights play a pivotal role and can be solved by linear programming. An approach to fuzzy AHPs is to estimate interval priorities on the items discussed. These interval weights are based on the concept of possibility and express the range of the possibility. The method employed by H. Tanaka is to minimise the range including the given data. The range of the possibility can be illustrated as the interval or width of calculated values. Similar to a conventional AHP model, the fuzzy AHP model has a hierarchical structure that is used to decide the priority of each alternative with the minimal evaluation width of each alternative. Saaty proposed that an AHP matrix should have a Consistency Index (C.I.) of less than 0.1, since theory suggests that C.I. should be satisfied. The fuzzy AHP Model can minimise such vagueness and uncertainty in the hierarchical structure used to evaluate alternatives.

Effective factors on not using the N95 respirators among health care workers: Application of Fuzzy Delphi and Fuzzy Analytic Hierarchy Process (FAHP).

Using respiratory protective equipment (RPE) including N95 respirators is one of the most important ways to protect health care workers (HCWs) against respiratory hazards. The aim of this study was to identify and prioritize the problems and obstacles in using N95 respirators among HCWs in Iran. In this cross-sectional study, problems and obstacles in using N95 respirators were identified and ranked by experts, using Fuzzy Delphi and Fuzzy Analytic Hierarchy Process (FAHP). Additionally, HCWs were asked to give their opinions about obstacles in using N95 respirators in order to form an opinion. Of 15 important obstacles in using N95 respirators identified by Fuzzy Delphi method, 6 factors were entered into the FAHP model: heat around the face, inaccessibility to respirator, difficulty breathing, pressure on the nose, trouble communicating with patients and colleagues, and no one does it. Identified problems and obstacles in using N95 respirators could be controlled during the selection of respirators, as well as by training and administrative measures.