Analytic Hierarchy Process Model Research Articles

Land Suitability for Biological Wastewater Treatment in Lebanon and the Litani River Basin Using Fuzzy Logic and Analytical Hierarchy Process

Biological wastewater treatment (BWWT) has been demonstrated to be a suitable procedure to degrade organic pollutants by utilizing natural processes. This paper presents a validated model to map land suitability for BWWT systems under the climatic conditions of Lebanon and the Litani River basin, using the Geographic Information System (GIS) and a machine learning approach for the Litani River Basin and Lebanon. The model was validated using fuzzy theory and the analytic hierarchy process (AHP) modeling theory, and a final suitability map was created in Lebanon that combined potential areas for Biological Wastewater Treatment (BWWT) based on particular criteria. Results show that spatial distribution of the suitable areas for BWWT sites differs for each of the criteria and the total extent of these potential areas is 162.94 km2 all over Lebanon and 42.62 km2 in the Litani basin areas. This area covers around 1.55% of the Lebanese areas and can help more than 30 regions while the total number of beneficiaries can reach a minimum of 60,000 and a maximum of 180,000 which represents between 1.5% and 3.75% of the total population. These potential areas are identified through land suitability classes to sustain the remaining BWWT areas and can contribute to the riparian forest ecosystem and mitigate the impact of climate change.

A modified cyanobacteria prediction model based on cellular automata model using N and P concentration reverse data: a case study in Taihu Lake

The problem of algal bloom caused by eutrophication has attracted global attention. Many scholars have studied the problem associated with algae bloom, but few have carried out dynamic monitoring, instead focusing on the formation mechanism of cyanobacteria. For our study of the Taihu Lake in China, we used Moderate-Resolution Imaging Spectroradiometer (MODIS) and Landsat remote sensing image data from 2017 to establish a prediction model. First, we used MODIS data to retrieve the concentration of N, P, and chlorophyll a in water. Then, we applied the analytic hierarchy process (AHP) model to the inversion results to construct the diffusion potential index. Finally, we used C# to compile the cellular automata (CA) model. We found that the distribution of cyanobacteria predicted by our method was consistent with the algal bloom situation of Taihu Lake in 2017. The results showed that the method effectively predicts the dynamic transfer of cyanobacteria from outbreak to diffusion in a short period of time, which can help decision-makers monitor lake health.

Sustainability assessment model for Brazilian hydroelectric projects using multicriteria analysis

The Analytic Hierarchy Process (AHP) has not previously been applied to the sustainable implementation of hydroelectric plants in Brazil. Despite attempts to conduct environmental analyses in a less subjective way, the Brazilian method is still in an early stage of development. Therefore, this study presents a new approach to the AHP methodology, which is used worldwide to analyze the feasibility of hydroelectric plant projects. Specifically, we develop a model for assessing the sustainability of hydroelectric projects that considers environmental, social, and economic criteria. To prove the effectiveness of this model, we conduct a survey of the main criteria and sub-criteria adopted around the world and discuss their respective prioritization processes. Subsequently, we present case studies of three Brazilian hydroelectric plants. Our analysis suggests that the AHP model is satisfactory. We recommend using the proposed model as a basis to encourage and incite discussion regarding the multiple perspectives involved in a hydroelectric project. The AHP model combined with a sensitivity analysis is capable of describing the potential conflicts and impacts resulting from the implementation of a hydroelectric project.

Marble waste site suitability assessment using the GIS-based AHP model

Site suitability with regards to environmental protection, public concerns, and the legitimate prerequisite is a basic issue that has been tended to in this study. By and large, marble waste is being unloaded on accessible open spaces or released in water to the close by waterways in the territory, Mohmand marble zone (Shabqadar), Khyber Pakhtunkhwa, Pakistan. Suitability assessment for marble waste collection and disposal was carried out through the integrated approach of analytical hierarchy process (AHP) and geographic information system (GIS) to limit the ecological dangers, public, and government concerns related to marble waste. The available land use was ordered into three main land use classes followed by six sub-classes including water bodies and agriculture (environmental), settlement and social site (social), and marble units and roads (economic). These sub-classes in the investigation region were organized through pairwise correlation and weighted sum analysis, AHP procedure. The AHP results were interpreted through GIS tools of digitization, buffering, and overlay in ArcMap, ArcGIS. The integrated AHP and GIS outcomes were consolidated to get the optimum results of the study, marble waste collection, and disposal options. It was concluded that priority should be given to water bodies followed by agricultural land while protecting the available land use classes from marble waste hazards. The percent priority values calculated are 32.33%, 30.50%, 12.16%, 10.66%, 8.50%, and 6% for water bodies, agricultural land, settlements, marble processing units, roads, and cultural sites respectively. The sequence of priority of the land use values are waterbodies > agriculture > settlement > marble industries > road > cultural site. The proposed integrated model is helpful in site suitability for waste management by the authorities and decision-makers associated with waste management.

Multicriteria Evaluation of Portable Energy Storage Technologies for Electric Vehicles

The conventional vehicles are a major cause of the greenhouse gases emissions in the global environment. Electric vehicles are a sustainable alternative to the conventional vehicles due to the negligible emissions and the possibility of the renewable energy integration. However, the electric vehicles require the separate storage systems and the selection of the proper storage system is a major concern in the electric vehicles markets. The storage system should be selected in a systematic and rational way. Hence, this paper evaluates the existing storage technologies for electric vehicles based on a multi-criteria decision making model. For this purpose, this paper performs a comprehensive literature review of the existing storage technologies for electric vehicles. Then, this paper evaluates the key storage technologies for electric vehicles based on the five criteria including cost, technical features, compatibility, technological maturity, and environment, health, and safety. These criteria and their sub-criteria were used in the development of an analytic hierarchy process (AHP) model. The proposed AHP model was solved using Super Decisions software. Results offer the various insights for the selection of a proper storage system for electric vehicles. In most of the cases, AHP model suggested the utilization of hybrid sodium-nickel chloride battery (SNCB) and supercapacitors (SC) for electric vehicles. Besides, the higher capital cost has been identified as the key barrier in the adoption several storage technologies such as lithium ion battery (LIB) and hydrogen fuel cells (HFC) storage.

Disaster Risk Evaluation of Superlong Highways Tunnel Based on the Cloud and AHP Model

Comprehensive evaluation of the geological disaster risk of super long tunnels is significant for safety construction. In this paper, we establish a comprehensive evaluation system based on the cloud model and analytic hierarchy process (AHP) theory, considering four kinds of geological hazards, such as water and mud inrush, large deformation, rock burst, and collapse. Then, based on a super long highway tunnel of the Chizhou‐Qimen expressway in China, the construction risk evaluation is carried out. The results show that the evaluation system can accurately judge the disaster risk level of the tunnel under different conditions surrounding a rock. The cloud model theory can realize the mutual transformation of qualitative indicators and quantitative indicators and avoid the problem of intense subjectivity of evaluation indicators. The evaluation system can be used as a new approach to evaluate tunnel risks in similar projects.

The Performance Evaluation of IEE in Colleges and Universities Based on AHP Model

At present, the country strongly encourages all walks of life to innovate, especially in the field of education. China's major colleges and universities have increased the encouragement of innovation and entrepreneurship education (IEE) projects in keeping with the pace of the times, so it is particularly important to reasonably evaluate the actual benefits of the project. On the one hand, it can greatly improve the recognition of all walks of life for emerging education projects. On the other hand, it can realize the timely and accurate application of the financial funds of the project. Based on this background, through the analysis and summary of existing theories and comprehensive consideration at all levels, this paper studies the new education projects from the aspects of teaching environment, conditions, quality, satisfaction, and financial capital and then constructs a set of performance evaluation index system for IEE in major colleges and universities. At the same time, this paper analyzes the actual education environment in China and evaluates the IEE in all kinds of colleges and universities by using analytic hierarchy process (AHP). Judging from the assessment results, the current teaching conditions and the quality of teachers in Chinese universities are very good. But the conclusion from the perspective of students is opposite, and the investment ratio of their financial capital is not optimistic. Therefore, this paper puts forward the optimization suggestions.

The Research on Adjustment of University Students in Financial Hardship

Funding university students in financial hardship is one of the most important works in education field of China. This paper researches how to adjust the level of students in financial hardship with considering the effect of dormitory culture construction (DCC) and consumption. An evaluation system with considering self-satisfaction, moral performance, academic performance, academic potential, volunteering outside the dormitory, and dormitory hygiene performance is established to measure the effect of DCC and, applying the binary Logistic regression model, the validity of the system is examined. On the basis of taking subjective evaluation and objective quantitative factors into full consideration, the Analytic hierarchy process model is then utilized for the estimation of the effect of DCC, combined with the analysis of campus consumption behavior questionnaire, students’ consumption behavior is divided into 4 categories by K-means clustering algorithm, meanwhile, the average value for each category can be calculated. This paper takes the necessary consumption as the base, determine the adjustment strategy according to the ranking of the effect of DCC to make our funding work more reasonable and efficient. The data from South-Central Minzu University is used to check the model, The comparison of the results before and after adjustment is shown in this paper, and the comparison results reveal that our model has a good stability and can recognize the growth of students.

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.

Application of Analytic Hierarchy Process in Selecting a State-Made Electronic Documentation Management System for Polish Municipalities

This paper considers the problem of selecting a state-made electronic document management system (EDMS) using the analytic hierarchy process (AHP) model. The problem of EDMS selection from two available variants is analysed and the selection criteria related are highlighted on the basis of the literature and the authors’ experience. Calculations related to pairwise comparisons and prioritisation between criteria and variants form the core of the paper. This problem is only applicable to municipalities in Poland that have implemented an older state-made system; based on pair-wise comparisons, retaining the older system is preferable to implementing the new state-made EDMS because of the lack of integration of the new EDMS with internal systems.

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.

Evaluation of Rural Landscape Resources Based on Cloud Model and Probabilistic Linguistic Term Set

Rural landscape resources are important ingredients of rural revitalization and modernization in developing countries and regions. Evaluation methods play a crucial role in the development planning, design, transformation, and protection of these resources. However, there has been a lack of research on the evaluation of rural landscape resources, especially from the perspective of rural revitalization. Based on previous evaluation methods and expert consultations on landscape planning and design, we proposed a new approach for evaluating rural landscape resources by establishing a new index system and using the Analytic Hierarchy Process (AHP) and probabilistic linguistic Cloud Model. To demonstrate its applicability and effectiveness, we applied our model to the case of a village (Xiapu) in Guangdong, China, determined the parameter set of its rural landscape resources, and obtained related results showing that the method is practical and can reflect the value of resources objectively and efficiently. Based on this model, further suggestions are provided to improve the design and other utilizations of rural landscape resources.

Analysis of Factors Affecting the Interest of Buying Muslim Consumers in Minimarket 212 Mart And Indomaret in Kecamatan Pagedangan Kabupaten Tangerang, Banten Province - Indonesia

This study aims to determine what factors influence consumer buying interest in minimarkets 212 Mart in Pagedangan and Indomaret in Pagedangan. The method used in this research is a quantitative method using the Analytical Hierarchy Process (AHP) model. The criteria used in this study are location, service, price, facilities and products. The sampling technique used in this research is purposive sampling technique which is carried out by distributing questionnaires to all consumers who have bought at 212 Mart in Pagedangan and Indomaret in Pagedangan as many as 96 respondents. The results showed that the results of the assessment of the level of importance of the criteria in consumer buying interest at the 212 Mart Pagedangan and Indomaret in Pagedangan minimarkets produced the following priority/ weight scales: Product priority I (0.2897), priority II price (0.2896), Priority III location (0.1681) , Priority IV services (0.1320) and Priority V facilities (0.1206). from the results of the assessment of the level of alternative importance in consumer buying interest at the minimarkets 212 Mart in Pagedangan and Indomaret in Pagedangan produces the following priority / weight scales: Indomaret I Priority (0.6373) and 212 Mart (0.3627).

Evaluating the capability of municipal solid waste separation in China based on AHP-EWM and BP neural network

With the increase in municipal solid waste (MSW), most cities face solid waste management issues. In this study, the analytic hierarchy process (AHP) and artificial neural network (ANN) models were improved to assess the MSW separation capability based on 18 selected indicators of solid waste separation in 15 cities in China. The entropy weight method (EWM) was used in AHP to optimize and determine the indicators and then evaluate their weights, which showed that the general public budget expenditure had the highest weight (0.5239). This implied that the MSW separation capability could be mainly influenced by government financial support. ANN based on scan optimization and machine learning methods were established (R2 = 0.9992) to predict the missing indicators. The mapping relationship between MSW separation indicators and capabilities was also significantly improved from R2 = 0.5317 to R2 = 0.9993, thereby increasing the prediction accuracy of MSW separation capabilities to 95.15%. Thus, this research provides a new avenue for MSW separation and establishes a combined model to predict the separation capability in practical applications.

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.

Comparison of statistical and analytical hierarchy process methods on flood susceptibility mapping: In a case study of the Lake Tana sub-basin in northwestern Ethiopia

Abstract The flood is one of the frequently occurring natural hazards within the sub-basin of Lake Tana. The flood hazard within the sub-basin of Lake Tana causes damage to cropland, properties, and a fatality every season. Therefore, flood susceptibility modeling in this area is significant for hazard reduction and management purposes. Thus, the analytical hierarchy process (AHP), bivariate (information value [IV] and frequency ratio [FR]), and multivariate (logistic regression [LR]) statistical methods were applied. Using an intensive field survey, historical document, and Google Earth Imagery, 1,404-flood locations were determined, classified into 70% training datasets and 30% testing flood datasets using a subset within the geographic information system (GIS) environment. The statistical relationship between the probability of flood occurrence and 11 flood-driving factors was performed using the GIS tool. The flood susceptibility maps of the study area were developed by summing all weighted aspects using a raster calculator. It is classified into very low, low, moderate, high, and very high susceptibility classes using the natural breaks method. The accuracy and performance of the models were evaluated using the area under the curve (AUC). As the result indicated, the FR model has better performance (AUC = 99.1%) compared to the AHP model (AUC = 86.9%), LR model (AUC = 81.4%), and IV model (AUC = 78.2%). This research finds out that the applied methods are quite worthy for flood susceptibility modeling within the study area. In flood susceptibility modeling, method selection is not a serious challenge; the care should tend to the input parameter quality. Based on the AUC values, the FR model is comparatively better, followed by the AHP model for regional land use planning, flood hazard mitigation, and prevention purposes.

Evaluation of machine learning, information theory and multi-criteria decision analysis methods for flood susceptibility mapping under varying spatial scale of analyses

The annual average economic losses due to various natural disasters are increasing exponentially across the globe and have reached a mark of US$239.2 billion per year between the period 2000–2019. In India, due to flood hazards, approximately 6.5 million people were affected and the total economic damages were approximately US$3 billion per year between 1990 and 2019. This study proposes to compare and evaluate the performance of the Support Vector Machine (SVM), Shannon's Entropy (SE), and Analytical Hierarchy Process (AHP) methods in the preparation of flood susceptibility mapping and assess their contextual suitability. The study has been carried out in coastal districts of West Bengal, India namely, South 24 Parganas and East Midnapur. Nine flood conditioning factors were identified and used as input parameters for the study. Each flood susceptibility map was subdivided into four categories where 27.29% of the study area were categorized as highly susceptible, while 39.45% of area were categorized as moderately susceptible to flood hazards. The Receiver Operating Characteristic (ROC) curve and the Seed Cell Area Index (SCAI) were applied for accuracy assessment and validation of the selected models. AUC values for ROC curves showed that the performance of the SVM model is better than that of the AHP and SE methods. Moreover, Hot Spots analyses for identification of high flood susceptible clusters revealed that the SVM model was far superior when compared to the other two models. The factors selected for assessment of flood susceptibility in AHP and SE models could not respond to the changing scale of analyses and hence produced significant erroneous outcomes. Hence, the SVM model evolved as the most versatile method in this comparison.

Influencing Factors of Azerbaijan and China’s Sustainable Tourism Development Strategy under the One Belt One Road Initiative

After the Belt and Road Initiative (BRI) was put forward, the tourism industry between Azerbaijan and China developed rapidly, and gradually became an important area of cooperation between the two countries to promote economic cooperation, non-governmental exchange, and cultural exchange. However, there is currently a lack of research on the development strategy of tourism cooperation between the two countries under the BRI. This paper aims to explore the development strategy of sustainable tourism cooperation between Azerbaijan and China under BRI through a hybrid model of SWOT (Strengths, Weaknesses, Opportunities, and Threats) and AHP (Analytic Hierarchy Process). The factor elements of the SWOT matrix introduce ambiguity due to the complex layering of elemental importance. Therefore, the AHP method was used to systematically evaluate the importance of strategic factors and reduce the subjective bias caused by the SWOT analysis method. By constructing the Delphi-AHP-SWOT strategic quadrilateral and calculating the azimuth of the strategy type, the type and intensity map of the tourism cooperation development strategy between Azerbaijan and China under the BRI is drawn. Finally, it is concluded that the development strategy of tourism cooperation between Azerbaijan and China is a pioneering development strategy. Suggestions are given for future development. This paper provides a valuable experience for the sustainable development of tourism cooperation among countries under the BRI.

Assessment of Flood Hazard Mapping Based on Analytical Hierarchy Process (AHP) and GIS: Application in Kencong District, Jember Regency, Indonesia

Flood is one of the most frequent hydrometeorological disasters which leads in economic losses. The first step in flood disaster mitigation efforts is mapping vulnerable areas. Kencong District frequently affected by the annual flooding event. This study aims to assess flood hazard mapping by integrating the AHP method and Geographic Information System. This study used a descriptive quantitative approach through the correlation matrix of the AHP model for each physical environmental factor. These factors include slope, altitude, distance from the river, soil type, Topographic Wetness Index (TWI), and Curvature. Furthermore, with the Geographic Information System (GIS), the weighted overlay stage was carried out to obtain the results of flood-prone areas. Based on the AHP analysis, the most significant factors in determining flood-prone areas were the distance from rivers, slopes, and TWI. The results of flood-prone areas mapping were divided into five classes: from deficient 0.02%, low 4.26%, medium 37.11%, high 51.89%, and very high 6.72%. Validation of GIS mapping results with data in the field has an AUC value of 84%, which indicates that the prediction of the AHP-GIS model is perfect in flood-prone areas mapping in the Kencong District. The integration of AHP method and Geographic Information System in flood hazard assessment were able to produce a model to evaluate the spatial distribution of flood-prone areas.
 Keywords : Flood Hazard Mapping; Multi-criteria decision analysis; AHP Model; GIS; Jember
 
 Copyright (c) 2021 Geosfera Indonesia and Department of Geography Education, University of Jember
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