Fuzzy Analytic Hierarchy Process Model Research Articles

Analysis and Evaluation of Enterprise Performance Appraisal Index Based on Fuzzy AHP Model

The decisive and decision-making challenges of business investment are for the good development of enterprises. In order to have a better market advantage of chemical granules for enterprises, the analytic hierarchy process (AHP) is constructed to analyze the company's performance. Under the environment of state-owned enterprises and foreign enterprises competing for market resources together, building a performance evaluation system suitable for the development stage of the company can adjust the planning strategy and analyze its own disadvantages in time. When analyzing the effective combination of performance appraisal and enterprise development, as well as the effective communication between employees and enterprise managers, feedback information is obtained through the experimental results. Under this analysis condition, this paper describes the feasibility and soundness of the AHP model system for enterprises, and what favorable decision-making methods can be provided for later development. Based on the selection of performance evaluation indicators, AHP analysis can clearly get the weight of each indicator and the correlation between them, in order to improve and build a new system of evaluation indicators. This paper concludes the following: (1) based on the analysis of enterprise performance appraisal indicators, using the AHP model evaluation method to calculate the indicators, the optimized indicators for the performance appraisal of the comprehensive and efficient significantly improved. (2) Comparing the traditional AHP calculation with the optimized model calculation, the results show that under the optimized calculation, the index is more concise and the fluctuation is reduced, which reduces the burden on administrators. (3) In the membership degree of index evaluation grade, the membership degree with an excellent grade is 0.9, which shows that the index plays a very important role in evaluation. (4) According to the development indicators of enterprises in recent years, it is found that the growth rate of resources is growing slowly, the demand for the talent market is still in a stable state as always, and its financial resources have increased by 120% in 2016.

Designing a MCDM Model for Selection of an Optimal ERP Software in Organization

Among the growth of the Industrial Revolution 4.0 and moving towards 5.0, the application of science and technology is a decisive factor in catching up with new business trends. In particular, the application of the enterprise resources planning (ERP) towards enterprise management is extremely important. ERP systems help businesses save time and effort in managing projects and utilizing resources. Instead of manual handling, the processes are carried out automatically. At the same time, the system operates correctly and efficiently which avoids errors. In this work, the author explored the application of a fuzzy multicriteria decision making (FMCDM) method including Fuzzy Analytic Hierarchy Process model (FAHP) and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) model for the evaluation of various ERP software (mainly warehouse and inventory management module). First, the fuzzy AHP model is applied to calculate the weights of criteria, and then, the obtained weights are used in the TOPSIS method for ranking of the alternatives. This study would assist decision makers in an ERP implementation environment in deciding a suitable ERP software for various industries.

A spherical fuzzy AHP model for contractor assessment during project life cycle

Abstract Measurement of construction performance is essential to a clear image of the present situation. This monitoring by the management team is necessary to identify locations where performance is exceptionally excellent or poor and to identify the primary reasons so that the lessons gained may be exported to the firm and its progress strengthened. This research attempts to construct an integrated mathematical model utilizing one of the recent methodologies for dealing with the fuzzy representation of experts’ knowledge and judgment considering hesitancy called spherical fuzzy analytic hierarchy process (SFAHP) method to assess the contractor’s performance per the project performance parameters (cost, schedule, quality, leadership, and change management). At the same time, most project control systems are currently applied through software like Primavera P6 or MS Project. These look at a project’s cost and schedule status by following the earned value analysis for finding the performance. Based on decision makers’ preferences, the analytic hierarchy process (AHP) may be used to arrive at the optimum conclusion. AHP approaches are discussed, including AHP, grey-AHP, fuzzy-AHP, and SFAHP weights comparison. Calculation results showed that the spherical fuzzy approach differs significantly from the other approaches where it considers the decision maker’s hesitation when making linguistic multicriteria decisions and then, as a result, recommends applying periodically for performance measurement. This model can be viewed as a valuable way to help the decision-making stakeholders in the construction sector do the best job about critical issues at a suitable time.

Application of fuzzy TOPSIS in assessing performance of agro-processed organic crops: A case of Sustainable Agriculture Tanzania (SAT) in Morogoro

It is a common practice for organisation to carry out assessment exercises regarding performance of their organisational activities and processes. This paper assesses the market performance of five agro-processed crops at Sustainable Agriculture Tanzania (SAT) against some criteria. Experts at SAT supplied useful information by responding through a questionnaire. The fuzzy TOPSIS model was applied in the methodology to rank the processed products. For the sake of comparing results, the fuzzy analytical hierarchy process (AHP) model was also applied to rank the products. It was found that three products maintained their positions in the two models while the other two products (alternatives) exchanged their positions. It was further suggested that more efforts have to go for lower market performing products by looking upon means to improve on their corresponding low weight criteria/sub-criteria.

Assessment of agricultural land suitability using GIS and fuzzy analytical hierarchy process approach in Ranchi District, India

The land is a vital source of agriculture. Agricultural land is utilized for the purpose of cropping. Delineation of potential agricultural land is pertinent when population pressure incrementally increases and a competitive trade-off between different land uses. The present study is conducted to evaluate the agrarian land suitability in the Ranchi district (Plateau region in India) using fuzzy analytical hierarchy process (FAHP). A land suitability evaluation technique is designed, combining nineteen thematic layers from five categories: climatic parameters, topographic features, soil characteristics, euclidean distance, and land elements. All thematic layers were combined into a single layer using the FAHP model to create agricultural land suitability map in a GIS environment. Our analysis demonstrates that 11.17% of the total area (509700 ha) is highly suitable, while about 20.73% and 13.81% of the study area is moderately suitable and marginally suitable for agricultural activities. The study also reveals that approximately 54.29% of the lands are not suitable for agriculture. Our findings provide additional information, and local governments can use the land suitability map to manage and develop agricultural resources. The study contributes to the studies on agricultural suitability by bringing in multiple variables centring on the FAHP method, which can be replicated in studies on plateau regions across the globe.

A Fuzzy Analytic Hierarchy Process Model to Evaluate Logistics Service Expectations and Delivery Methods in Last-Mile Delivery in Brazil

Nowadays, postal services and third-party logistics services (3PL) have been pressured by the increasing demand for delivery services. Therefore, they need to improve their last-mile delivery strategies to meet customers’ expectations. This paper aims to investigate how logistics service expectations affect the delivery process in urban areas using a multiple-criteria decision support system based on the Fuzzy Analytic Hierarchy Process (FAHP). We developed a decision-making model employing six criteria and five delivery methods indicated in the literature and collected information from 27 experts working in academia and local and multinational third-party logistics providers in Brazil to validate this model. The results indicate that cost (21.4%) and tracking and tracing (19.3%) are the most important two criteria in the decision model, and the best delivery methods are smart lockers (21.8%) followed by small trucks (21.3%). Our results suggest that service expectations regarding last-mile delivery are aligned with extensive use of road transport and the increase in e-commerce sales can raise greenhouse gas emissions and compromise the environment in urban areas.

Optimization of Cold Chain Logistics with Fuzzy MCDM Model

Vaccines are biological products containing a weakened, inactivated part of bacteria or viruses that are not harmful to the human body. Vaccine manufacturers and distributors should always store vaccines at the right temperature. To do this task, manufacturers and distributors need to manage cold supply chains to the required standards. Cold chain management helps manufacturers control and keep vaccines at the right temperature while ensuring quality and extending their expiration date. That will help businesses in the medical industry reduce economic losses, avoid waste, and bring more significant benefits to patients. The selection and evaluation process for logistics suppliers, especially those who deal with low-temperature storage, considers many factors to reduce the potential waste of products from poor storage strategies. The author introduces an integrated approach to solve such a fuzzy multiple criteria decision-making (MCDM) problem based on the Fuzzy Analytical Hierarchy Process (FAHP) model and an Interactive and Multi-criteria Decision-Making in Portuguese Model (TODIM) model methods under the fuzzy linguistic environment. In this work, the SF-AHP method derives criteria weights in the first stage, and then a TODIM method is presented to identify the ranking of logistics providers. Finally, the authors present a case study on the evaluation and selection of cold chain logistics suppliers to demonstrate the applicability of the proposed fuzzy MCDM model.

Solar Energy Deployment for the Sustainable Future of Vietnam: Hybrid SWOC-FAHP-WASPAS Analysis

In recent years, solar power has developed significantly in Vietnam, making an important contribution to ensuring energy conservation and decreasing greenhouse gas exposure. Recently, Vietnam has experienced impressive growth in the solar and wind energy sectors, showing the high potential of using renewable electricity in addressing energy needs. The target of this study was to construct a fuzzy multicriteria decision-making, model including strengths-weaknesses-opportunities-challenges (SWOC) analysis, the fuzzy analytic hierarchy process (F-AHP) model, and the weighted aggregates sum product assessment (WASPAS) model, to select the location of a solar power plant in south Vietnam. The proposed fuzzy multicriteria decision-making model (MCDM) model is the first solar power plant location selection in southern Vietnam that utilizes literature reviews and expert interviews. Moreover, this is the first study to provide a case study on evaluating locations during solar power plant location selection that utilizes a combination of the SWOC, FAHP, and WASPAS models. The findings of this study provide valuable knowledge for the assessment and selection of suitable locations for renewable energy projects, including both solar power energy projects and other renewable energy projects.

National-scale flood risk assessment using GIS and remote sensing-based hybridized deep neural network and fuzzy analytic hierarchy process models: a case of Bangladesh

Assessing flood risk is challenging due to complex interactions among flood susceptibility, hazard, exposure, and vulnerability parameters. This study presents a novel flood risk assessment framework by utilizing a hybridized deep neural network (DNN) and fuzzy analytic hierarchy process (AHP) models. Bangladesh was selected as a case study region, where limited studies examined flood risk at a national scale. The results exhibited that hybridized DNN and fuzzy AHP models can produce the most accurate flood risk map while comparing among 15 different models. About 20.45% of Bangladesh are at flood risk zones of moderate, high, and very high severity. The northeastern region, as well as areas adjacent to the Ganges–Brahmaputra–Meghna rivers, have high flood damage potential, where a significant number of people were affected during the 2020 flood event. The risk assessment framework developed in this study would help policymakers formulate a comprehensive flood risk management system.

Comparative analysis of groundwater potentiality zone using fuzzy AHP, frequency ratio and Bayesian weights of evidence methods

Groundwater resource management in the urban area is one of the important aspects because of growing population demand and having inadequate water supply. So, proper information is needed to manage the future urban planning for such kinds of areas. This study emphasizes groundwater potentiality zone (GPZ) assessment in the Asansol urban agglomeration (AUA) region, West Bengal, India. For this purpose, we have incorporated eight conditioning factors namely LULC, lithology, slope, elevation, rainfall, drainage density, lineaments density, and soil map using conventional and remote sensing data in GIS software. All these conditioning factors have been reclassified in ArcGIS and processed by the fuzzy analytical hierarchy process (FAHP), frequency ratio (FR), and Bayesian weights of evidence (BWOE) statistical methods. Then, the groundwater potential index has been formulated, and finally, GPZ maps are generated based on of selected three models. The result shows that very high area of GPZ, e.g. 9.13%, 11.62% and 7.43% are under BWOE, FR and FAHP models, respectively. The receiver operating characteristic validation curves show that FR method (AUC = 96.4%) is well obtained for GPZ in comparison with both BWOE (AUC = 83.8%) and FAHP methods (AUC = 82.9%). Therefore, this statistical method is highly recommended for the study of groundwater potential assessment and this outcome is very suitable for the groundwater resources management in future land use planning. Precautionary works in low potential areas should be given priority for long-term planning. Thus, this study can be considered as a good document for decision support in water exploitation planning and sustainable groundwater management in AUA region.

An Integrated Fuzzy Analytic Hierarchy Process (AHP) Model for Studying Significant Factors Associated with Frequent Lane Changing.

Frequent lane changes cause serious traffic safety concerns, which involve fatalities and serious injuries. This phenomenon is affected by several significant factors related to road safety. The detection and classification of significant factors affecting lane changing could help reduce frequent lane changing risk. The principal objective of this research is to estimate and prioritize the nominated crucial criteria and sub-criteria based on participants’ answers on a designated questionnaire survey. In doing so, this paper constructs a hierarchical lane-change model based on the concept of the analytic hierarchy process (AHP) with two levels of the most concerning attributes. Accordingly, the fuzzy analytic hierarchy process (FAHP) procedure was applied utilizing fuzzy scale to evaluate precisely the most influential factors affecting lane changing, which will decrease uncertainty in the evaluation process. Based on the final measured weights for level 1, FAHP model estimation results revealed that the most influential variable affecting lane-changing is ‘traffic characteristics’. In contrast, compared to other specified factors, ‘light conditions’ was found to be the least critical factor related to driver lane-change maneuvers. For level 2, the FAHP model results showed ‘traffic volume’ as the most critical factor influencing the lane changes operations, followed by ‘speed’. The objectivity of the model was supported by sensitivity analyses that examined a range for weights’ values and those corresponding to alternative values. Based on the evaluated results, stakeholders can determine strategic policy by considering and placing more emphasis on the highlighted risk factors associated with lane changing to improve road safety. In conclusion, the finding provides the usefulness of the fuzzy analytic hierarchy process to review lane-changing risks for road safety.

Applying the fuzzy analytical hierarchy process for classifying and prioritizing healthcare quality attributes

Abstract In any country, the healthcare system is an important sector whose major goal is to provide high-quality medical services and goods to maximize patient satisfaction. The purpose of this research is to introduce an analytical approach for presenting and classifying healthcare quality aspects which might have an impact on patient satisfaction. Therefore, this perspective is achieved by implementing an integrated Kano and fuzzy analytical hierarchy process (FAHP) Model which will grant the support for creating better and improved business strategies, as well as an efficient resource allocation. Our contribution to the literature focuses on the advantage of using an integrated Kano Model and a fuzzy analytical hierarchy process in classifying patients’ needs based on healthcare quality attributes regarding the healthcare staff and clinic’s facility design. Furthermore, this contribution represents a base for further research and completes with the efficiency and sustainability of the fuzzy analytical hierarchy process applied to the healthcare system. The results suggest that healthcare providers should focus more on performance attributes, to increase patient satisfaction.

On the Factors of Successful e-Commerce Platform Design during and after COVID-19 Pandemic Using Extended Fuzzy AHP Method

The ongoing COVID-19 pandemic has caused a paradigm shift in all aspects of contemporary human life. Everyday activities such as shopping have shifted from traditional methods to the ever-more growing online variants, allowing for an increase in electronic commerce (e-commerce) industry. As more services become available online, consumers often rely on trusted services, which are often reflected on the web and mobile platforms they are presented on. In this paper, we study the factors for successful e-commerce platform design in the Western Balkans region using Fuzzy Analytical Hierarchy Process (FAHP) with triangular fuzzy numbers. After an extensive literature overview, interviews with representatives of top-ranking e-commerce companies in the region, and the analysis of experts’ opinions, we select a number of factors and sub-factors for prioritization, taking into account pre-pandemic factors, as well as the ones of the pandemic itself. We extend the FAHP model, which now consists of five (instead of three) points of view. Finally, we present and discuss the results in the form of tables and graphs, as well as an overall recommendation of what should be taken into account when designing an e-commerce platform. Our results rank service quality and security factors first and criteria such as multilingual support last.

Two-Stage Fuzzy MCDM for Green Supplier Selection in Steel Industry

Steel is one of the most powerful industries globally, and the associated products have a tremendous impact on nurturing a sustainable society. Considering environmental concerns within this industry's supply chain is highly successful in saving both energy and natural resources and lowering greenhouse gas emissions. In light of this, sustainable suppliers are considered input partners who play a specific role in the chain of business operations of every enterprise, maintaining them to achieve higher levels of customer satisfaction and thus gain more market share. Supplier selection can be characterized as a multi-criteria decision-making (MCDM) problem under a vague and uncertain environment. In this paper, a hybrid model of fuzzy analytic hierarchy process (FAHP) and fuzzy technique for order of preference by similarity to ideal solution (FTOPSIS) is suggested to determine the most potent green supplier of steel manufacturing in Vietnam based on a complete set of five main criteria (price, quality, delivery, service, environment) through literature review and experts’ responses. The significance of each criterion is measured by experts’ judgments in linguistic terms, which can be expressed in triangular fuzzy numbers using the FAHP model. Then, the FTOPIS model is deployed to rank alternatives. A case study of Vietnam's top 10 steel manufacturers is implemented to exhibit the model's effectiveness. From FAHP findings, “lead time”, “warranty”, “defect rate”, “supply capacity”, and “product price” were recognized as the most impactful criteria. As for the ranking of sustainable suppliers, “Hoa Phat Group Joint-stock company”, “Hoa Sen Group”, and “Pomina Steel Corporation” are the top three optimal suppliers. In dealing with qualitative data and input uncertainties in the supplier evaluation and selection problem, this paper can suggest more possible solutions and provide significant materials in similar outsourcing selection problems and applications of relevant industries.

Optimization Model for Selecting Temporary Hospital Locations During COVID-19 Pandemic

The two main approaches that countries are using to ease the strain on healthcare infrastructure is building temporary hospitals that are specialized in treating COVID-19 patients and promoting preventive measures. As such, the selection of the optimal location for a temporary hospital and the calculation of the prioritization of preventive measures are two of the most critical decisions during the pandemic, especially in densely populated areas where the risk of transmission of the virus is highest. If the location selection process or the prioritization of measures is poor, healthcare workers and patients can be harmed, and unnecessary costs may come into play. In this study, a decision support framework using a fuzzy analytic hierarchy process (FAHP) and a weighted aggregated sum product assessment model are proposed for selecting the location of a temporary hospital, and a FAHP model is proposed for calculating the prioritization of preventive measures against COVID-19. A case study is performed for Ho Chi Minh City using the proposed decision-making framework. The contribution of this work is to propose a multiple criteria decision-making model in a fuzzy environment for ranking potential locations for building temporary hospitals during the COVID-19 pandemic. The results of the study can be used to assist decision-makers, such as government authorities and infectious disease experts, in dealing with the current pandemic as well as other diseases in the future. With the entire world facing the global pandemic of COVID-19, many scientists have applied research achievements in practice to help decision-makers make accurate decisions to prevent the pandemic. As the number of cases increases exponentially, it is crucial that government authorities and infectious disease experts make optimal decisions while considering multiple quantitative and qualitative criteria. As such, the proposed approach can also be applied to support complex decision-making processes in a fuzzy environment in different countries.

Optimization Agricultural Supply Chain: A Case Study of Fertilizer Supplier Selection

The 21st century is associated with the Industrial Revolution 4.0 and the organic agriculture trend, making the utilization of high-quality fertilizers, abundant nutritional content, economical, and no affect to environment pollution. According to the new concept, clean agricultural production and organic agricultural products are not allowed to excessively use synthetic chemicals such as chemical fertilizers, and plant protection drugs, but priority is to use manure, organic fertilizers, and natural mineral fertilizers. Fertilizer must meet the balanced nutritional requirements of crops, maintain, and improve the fertility of the ground, protect the surrounding ecosystem, and leave harmful effects in agricultural products, products with high quality, safe for users and high economic efficiency for producers. To achieve the above goal, the selection of a fertilizer supplier is an important decision, supporting the supply chain's sustainable development, fertilizer supplier selection is a multicriteria decision making model, the decision maker must assess all qualitative and quantitative factors. In this paper, the author proposed an integer decision making model including Fuzzy Analytic Hierarchy Process (FAHP) and Complex Proportional Assessment of Alternatives (COPRAS) for fertilizer supplier selection. The weightings of the criteria are calculated by using FAHP, COPRAS is then applied for ranking some potential fertilizer suppliers. The efficiency of the proposed models is proved by a case study conducted in a farm located in the south of Vietnam. This research is the first fertilizer supplier evaluation and se-lection model in Vietnam by interviewing experts and reviewing the literature. Re-search result is to provide a case study on evaluating supplier in agricultural supply chain utilizing the model proposed by the combination of FAHP and COPRAS models.

Fuzzy Decision Model: Evaluating and Selecting Open Banking Business Partners

The finance supply chain has always been a different supply chain compared to product supply chain being a service supply chain. Open Banking (OB) is one of the most important milestones since the beginning of financial technology innovation and service supply chain. As these are activities provided by traditional banks, non-bank financial institutions also provide financial service with access to consumer banking, transactional and other financial data to develop financial applications and services tailored to their customers. The development of financial technology, “Open banking”, promotes financial services to begin this transformation. However, evaluating and selecting open banking business partners from multiple perspectives for banks are underexplored. Thus, the authors in this research proposed a hybrid multi-criteria decision-making model which includes a Spherical Fuzzy Analytical Hierarchy Process (SF-AHP) model and a Multi-Attributive Ideal-Real Comparative Analysis (MAIRCA) model with supports from seasoned domain experts. The contribution of this research is a proposition of a fuzzy decision model for evaluating and selecting open banking business partners. The model successfully determined a suitable open bank provider in order to assist decision makers decide objectively.

Sustainable Supplier Selection Model in Supply Chains During the COVID-19 Pandemic

As global supply chains become more developed and complicated, supplier quality has become increasingly influential on the competitiveness of businesses during the Covid-19 pandemic. Consequently, supplier selection is an increasingly important process for any business around the globe. Choosing a supplier is a complex decision that can result in lower procurement costs and increased profits without increasing the cost or lowering the quality of the product. However, these decision-making problems can be complicated in cases with multiple potential suppliers. Vietnam's textile and garment industry, for example, has made rapid progress in recent years but is still facing great difficulties as the supply of raw materials and machinery depends heavily on foreign countries. Therefore, it is extremely important for textile and garment manufacturing companies in Vietnam to implement an effective supplier evaluation and selection process. While multicriteria decision-making models are frequently employed to assist with supplier evaluation and selection problems, few of these models consider the problem under the condition of a fuzzy decision-making environment. The aim of this paper is to create a hybrid MCDM model using the Fuzzy Analytical Hierarchy Process (FAHP) model and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to assist the supplier selection process in the garment industry in a fuzzy decision-making environment. In this study, the FAHP method is used to evaluate the performance and the weight of each criterion. TOPSIS is then used to rank all potential suppliers. The proposed model is then applied to a real-world case study to demonstrate both the process of calculation as well as its real-world applicability. The results from the case study provide empirical evidence that the model is feasible. The proposed approach can also be used in combination with other MCDM models to better support decision makers and can be modified to be applied in similar supplier selection processes for different industries.

Creating a common priority vector in intuitionistic fuzzy AHP: a comparison of entropy-based and distance-based models

In the case of conflicting individuals or evaluator groups, finding the common preferences of the participants is a challenging task. This statement also refers to Intuitionistic Fuzzy Analytic Hierarchy Process models, in which uncertainty of the scoring of individuals is well-handled, however, the aggregation of the modified scores is generally conducted by the conventional way of multi-criteria decision-making. This paper offers two options for this aggregation: the relatively well-known entropy-based, and the lately emerged distance-based aggregations. The manuscript can be considered as a pioneer work by analyzing the nature of distance-based aggregation under a fuzzy environment. In the proposed model, three clearly separable conflicting groups are examined, and the objective is to find their common priority vector, which can be satisfactory to all participant clusters. We have tested the model results on a real-world case study, on a public transport development decision-making problem by conducting a large-scale survey involving three different stakeholder groups of transportation. The comparison of the different approaches has shown that both entropy-based and distance-based techniques can provide a feasible solution based on their high similarity in the final ordinal and cardinal outcomes.

An optimal selection method for debris flow scene symbols considering public cognition differences

Disaster scene symbols can reduce memory and cognitive burdens and improve the transmission efficiency of debris flow information. There is no unified standard for disaster scene symbols, although many academic institutions and emergency departments have thoroughly studied debris flow disasters. Instead, many disaster scene symbols of different styles interfere with the public's understanding of disaster information. Here, an optimal selection method for debris flow scene symbols considering public cognition differences is proposed. First, public knowledge is incorporated into the fuzzy analytic hierarchy process (FAHP) model for debris flow scene symbols selection. Second, debris flows are visualized in 3D with a virtual geographic environment (VGE). Finally, a real debris flow is selected for experimental analysis. The proposed method can support the optimal selection of debris flow scene symbols considering public cognition differences, and a 3D scene constructed with the selected scene symbols can improve the transmission efficiency of disaster information and provide support for public-oriented debris flow information services.