Analytic Hierarchy Process Model Research Articles

An unsupervised learning based MCDM approach for optimal placement of fault indicators in distribution networks

This paper proposes a novel integrated model based on multi-criteria decision-making (MCDM) method to assess and rank the feeder sections to optimally locate fault indicators in a large-scale distribution network. First, decision makers’ weights are computed based on the subjective weighting information. Then, dataset including data calculated for every alternative under active power flow, failure rate, repair time, number of customers, and customer type criteria are grouped using mixed-type clustering algorithm. This leads to the number of clusters extracted from the dataset, then obtained number of clusters are utilized to set the required linguistic terms. Finally, the ranking order of alternative is assessed by using the fuzzy similarity measure-based technique for order of preference by similarity to ideal solution (TOPSIS). The newly proposed model combines the merits of integrated enhanced particle swarm optimization (EPSO) fuzzy analytic hierarchy process (AHP) model in dealing with fuzziness and vagueness of linguistic assessments, the merits of clustering algorithm focused on representing performance values of each alternative with respect to each decision criterion and the merits of similarity measure-based TOPSIS in solving complex decision-making problems. The proposed model is applied to the RBTS4 and then sensitivity analysis is performed in the optimal solution.

Modeling rainfall-runoff estimation and assessing water harvesting zone for irrigation practices in Keleta watershed, Awash river basin, Ethiopia

The world’s water demand is increasing twice as quickly as the world’s population. Contrarily, the greatest problem facing humanity in the twenty-first century is the supply of food. During dry seasons, when water collecting is a crucial survival strategy, the communities in the study area experience water deficit for agricultural production. In this study, socioeconomic and biophysical parameters were considered to evaluate the water harvesting zone for irrigation practices. With the aid of this technology, water harvesting sites can be found in acceptable sites, and water resource management can be improved to address water shortages during the dry season when crops are at key stages of growth and filling. The integrated geographical information system/Remote Sensing (GIS/RS), Soil Water Assessment Tool (SWAT), fuzzy logic, and analytic hierarchy process (AHP) model were used to carry this out. Rainfall, drainage density, surface runoff, percentage of clay content, land use land cover, slope, lithology, lineament, and Euclidian distance to settlement and road were the criteria utilized to choose the Rainwater Harvesting (RWH) sites. The run-off was estimated using the SWAT model, weights for each influential component were determined using AHP, the input factor was standardized using fuzzy membership, and factors were combined using gamma fuzzy (ℽ= 0.9) overlay weighting. The model’s statistical performance was demonstrated by R2 values of 0.79 and NSE values of 0.77 for monthly calibration periods and R2 values of 0.81 and NSE values of 0.75 for monthly validation periods. The study area’s Rainwater Harvesting potential suitability classes covered very highly suitable (16.91%), extremely suitable (27.6%), moderately suitable (20.23%), low suitable (13.1%), and not suitable (6.43%), and restrictions (15.73%). The study’s findings could help decision-makers identify more lucrative and long-lasting irrigation investment options in the Keleta watershed and make better decisions regarding the development of irrigation projects there.

Delineation of groundwater potential zones and identification of artificial recharge sites in the Kinnerasani Watershed, India, using remote sensing-GIS, AHP, and Fuzzy-AHP techniques

Abstract The sustainable management of groundwater resources is crucial for ecological diversity, human health, and economic growth. This study employs scientific concepts and advanced techniques, including the analytic hierarchy process (AHP) and Fuzzy-AHP, to identify groundwater potential zones (GWPZs). Thematic maps representing drainage density, elevation, soil, geomorphology, slope, land use and land cover, and rainfall are used to delineate the GWPZs. Both techniques are employed to assign weights to these thematic maps based on their characteristics and water potential. The study revealed that in the investigated area, 17.76 and 18.27% of the final GWPZs (AHP and Fuzzy-AHP) can be classified as having poor potential, while 72.79 and 71.07% are categorized as having moderate potential. Moreover, 9.45 and 10.69% of the final GWPZs are identified as having high potential using the AHP and Fuzzy-AHP models, respectively. Receiver operating characteristics (ROCs) analysis is employed to validate these findings, demonstrating that the Fuzzy-AHP technique achieves an accuracy of 74% in identifying GWPZs in the region. This study utilizes the best method derived from both models to identify 26 suitable locations for artificial recharge sites. The reliable findings of this research offer valuable insights into decision-makers and water users in the Kinnerasani Watershed.

Analysis of Water Harvesting Structures Sites Appropriateness Using GIS-Based Methodology: Diyala, Iraq, as a Case Study

Water harvesting is an effective technology that may be used to collect unused runoff, therefore meeting various water needs and mitigating droughts. The study area is experiencing severe water lacks, so the goal of this research is to find ideal locations for structures of water harvesting through the use of a geographical information system-based multi-criteria analysis model that employs fuzzy logic with the analytical hierarchy process model. According to the hydrology and geomorphic criteria of the research area, a suitability map for water harvesting was constructed, and 17 and 12 sites suitable for check dams and farm ponds, respectively, were suggested in the regions with high and very high classes. Thus, this study’s findings underline the significance of geospatial modeling in planning water facilities and addressing the water shortage issue in the study region.

Consuming perception analysis of the yoga wear using fuzzy AHP model

In this paper, we propose to analyse the consumer perception of yoga wear and then improve its design based on the demand-driven design principle. For this purpose, we break down the problem into three levels: Goal Level (development of the new yoga wear), Requirement Level, and Design Solution Level (garment design solutions corresponding to the requirements of the Requirement Level). For the requirement level, we take into account the FEA (functional, expressive and aesthetic) factors for the consumer perception analysis. Due to the hierarchical characteristics of the analysis, we propose a fuzzy AHP (analytic hierarchy process) approach for the related data analysis. By using the AHP model, we can analyse requirements alongside their solutions in design alongside their respective weights. 50 evaluators (yogis) and 20 designers took part in the experiments. Similar design solutions and performance evaluation of the solutions were defined through consumer research and subjective evaluation experiments with standard procedures. We hope that this paper will guide the analysis and development of yoga wear design.

Assessment of Influencing Factors on Consumer Behavior Using the AHP Model

The influence of numerous factors determines and changes the daily behavior of consumers. This paper aims to estimate and rank the weight of cultural, social, personal, and psychological factors that change the buying habits of individuals. The research was conducted on a sample of 559 respondents in the Republic of Croatia. Data from the survey were used to create a hierarchical model structure. The analytic hierarchy process (AHP), as a decision-making method, was used in the analysis to estimate and rank the factors that influence consumer habits. An analysis of results showed that personal and psychological factors have the principal influence on consumer habits. Personal budget, as the dominant criterion in a group of set criteria, contributed to the fact that personal factors have the dominant influence on consumer habits.

Application of an Integrated Analytic Hierarchy Process and Interpretive Structural Modeling Methodology for Selecting Energy-Saving Methods

Application of an Integrated Analytic Hierarchy Process and Interpretive Structural Modeling Methodology for Selecting Energy-Saving Methods

Development of Risk Management Mitigation Plans for the Infant Formula Milk Supply Chain Using an AHP Model

Infant formula milk (IFM) is critical in the diet of many babies and must be of high-quality. Unfortunately, IFM has been a target of adulteration by those attempting to make illegal profits and has suffered from contamination-related issues. This study’s main objective was to identify the most critical risks affecting IFM quality in the supply chain and determine mitigation strategies to improve IFM performance measurement. We developed a model to reduce adulteration and contamination rates in the infant formula milk supply chains (IFMSCs) and maximize safety. The steps to achieve the study’s objectives included: (1) identifying the importance of IFMs for infant nutrition and their risks; (2) establishing mitigation criteria for evaluating IFMSC’s performance to maximize quality; and (3) analyzing each mitigation criterion to maximize IFM safety. Based on pairwise comparisons by professionals in the food supply chain (FSC) of decision-making, the Analytic Hierarchy Process (AHP) model was used to analyze and prioritize mitigation alternatives. According to the contamination quality risk agent, mitigation alternative (QR.M2) ranked highest. This study’s findings illustrate how vital avoiding risk is when dealing with public health, especially infants’ health, and how IFM must undergo precise testing and quality checks at every supply chain stage to ensure quality.

DEVELOPMENT OF SUSTAINABLE HEALTHCARE MODEL FOR THE HOSPITALS IN NORTHERN INDIA

Background: Healthcare organizations incorporate products and services at economical prices to deliver healthcare services of good quality. All the operations performed in the organizations aimed to achieve a higher level of environmental sustainability governed by the Sustainable Developmental Goals of 2030. Aims: This study aims to develop a sustainable healthcare model using Analytical Hierarchy Process (AHP). Methods: First and foremost, the authors have identified the factors associated with the sustainable healthcare system through a literature review. Based on these factors, a questionnaire was developed and administered to 25 healthcare organizations from December 2020 to March 2021. An Analytical Hierarchy Process is utilized to rank the factors, and a conceptual model is developed. The Felix Hospitals substantiate this model. The authors have also applied sensitivity analysis to validate the results achieved via AHP. Results: The AHP model demonstrates the focus is on the environment first, followed by the economic and social dimensions sustainably. The validated model was also substantiated by the hospital (Felix) results and sensitivity analysis. Conclusion: It can be concluded that hospital sustainability highly depends on the environment in the first stage and economic and social sustainability in the second and third stages. The same result was achieved through AHP. Keywords: analytical hierarchy process, hospital, sustainable healthcare.

DEVELOPMENT OF SUSTAINABLE HEALTHCARE MODEL FOR THE HOSPITALS IN NORTHERN INDIA

Background: Healthcare organizations incorporate products and services at economical prices to deliver healthcare services of good quality. All the operations performed in the organizations aimed to achieve a higher level of environmental sustainability governed by the Sustainable Developmental Goals of 2030. Aims: This study aims to develop a sustainable healthcare model using Analytical Hierarchy Process (AHP). Methods: First and foremost, the authors have identified the factors associated with the sustainable healthcare system through a literature review. Based on these factors, a questionnaire was developed and administered to 25 healthcare organizations from December 2020 to March 2021. An Analytical Hierarchy Process is utilized to rank the factors, and a conceptual model is developed. The Felix Hospitals substantiate this model. The authors have also applied sensitivity analysis to validate the results achieved via AHP. Results: The AHP model demonstrates the focus is on the environment first, followed by the economic and social dimensions sustainably. The validated model was also substantiated by the hospital (Felix) results and sensitivity analysis. Conclusion: It can be concluded that hospital sustainability highly depends on the environment in the first stage and economic and social sustainability in the second and third stages. The same result was achieved through AHP. Keywords: analytical hierarchy process, hospital, sustainable healthcare.

Key factors for sustainable operation of smart rural communities in aging societies: Voices of Korean community leaders

The purpose of this study is to identify the success factors for achieving sustainable operation of smart rural communities. Smart rural communities, enabled by smart technology, are regarded as a potential solution to the challenges posed by aging populations in Korea. However, the sustainable operation of smart rural communities is complex, as a variety of factors should be addressed. To address issues of aging problems in rural communities, this study proposes a priority factor for smart rural community service by applying an analytical hierarchy process (AHP) method and in-depth interviews. The AHP model was designed based on a socio-technical system, and an AHP survey was conducted with community leaders who have experience in smart rural community projects. This study proposes a total of 4 criteria and 16 factors along with their corresponding priorities. The results indicate that the local culture is the most important for a sustainable smart rural community compared to other factors. Specifically, factors such as empathy of rural residents, stable financial support, and the presence of smart technology professionals and technical staff are critical for achieving successful smart rural communities for the elderly people. This study found that the cultural and human aspects are more critical for the sustainable operation of smart rural communities than technology infrastructure. The findings of this study provide valuable insights to other countries similar to Korea facing aging problems in rural areas planning to introduce smart rural communities.

A Study on the Viability of Adopting Battery Electric Vehicles in Bus Rapid Transit in Brazil Using the AHP Method

Public transport is essential to provide urban mobility, and cities need to offer a fast, comfortable, secure, and low-pollutant public transport mode to attract passengers and reduce private car use. Despite metros, trains, and light rail systems being desirable, the cost of implementation and low flexibility make bus services the best option for many cities. One solution for improving bus service systems is the implementation of bus rapid transit systems that are composed of buses running in segregated lines with pre-payment fares and level boarding platforms in stations. However, the main challenge of bus systems is the use of engines fueled by diesel, which is extremely polluted. One possible solution is the use of battery buses; but are they really feasible regarding daily operation cost? In this paper, we investigate the adoption of battery buses in comparison to diesel engines in a BRT system using municipal data from São Paulo, Brazil, as a reference. We collected operational data from the Sao Paulo city government transport agency and data from the literature to produce an analytic hierarchy process (AHP) model, which allowed us to compare both systems. The AHP model considered a triple-bottom-line perspective using social, economic, and environmental impact criteria. The result showed that the initial costs of acquisition can be a barrier, but in the long run, cities adopting battery buses in their BRT system can benefit from the effects of reduction in gas emissions and longer lifetimes of electric bus components. Moreover, the results showed that the adoption of battery buses in BRT systems depends on local government subsidies being implemented.

Decision-making process for gluing on footwear parts using AHP and statistics

In manufacturing processes, there are conditions that continually impact decision-making among when choosing among alternatives; the selection is usually influenced by critical aspects such as quality, productivity, costs and customer feedback, among others. This article analyzes different adhesives for the process of gluing parts for sports shoes in a company located in the city of Purisima del Rincon in Guanajuato, México. The analysis employs statistical engineering tools and an Analytic Hierarchy Process (AHP) methodology. The case studied deals with an issue with gluing parts. The glue currently employed is of good quality but has drawbacks such as its high cost and thickness, which leads to a time-consuming manual application, affecting productivity. We propose and apply an AHP model with input information obtained by means of industrial experimentation in order to select the best alternative. Objective and subjective judgments relate to the quality score, production capacity, ease of application, and utility per pair. The chosen alternative represented the best option after factoring in all aspects of interest for the overall goal.

Risk Assessment Model System for Aquatic Animal Introduction Based on Analytic Hierarchy Process (AHP).

The spread of invasive species (IS) has the potential to upset ecosystem balances. In extreme cases, this can hinder economical utilization of both aquatic (fisheries) and terrestrial (agricultural) systems. As a result, many countries regard risk assessment of IS as an important process for solving the problem of biological invasion. Yet, some IS are purposefully introduced for what is seen as their potential economic benefits. Thus, conducting IS risk assessments and then formulating policies based on scientific information will allow protocols to be developed that can reduce problems associated with IS incursions, whether occurring purposefully or not. However, the risk assessment methods currently adopted by most countries use qualitative or semiquantitative methodologies. Currently, there is a mismatch between qualitative and quantitative assessments. Moreover, most assessment systems are for terrestrial animals. What is needed is an assessment system for aquatic animals; however, those currently available are relatively rudimentary. To fill this gap, we used the analytic hierarchy process (AHP) to build a risk assessment model system for aquatic IS. Our AHP has four primary indexes, twelve secondary indexes, and sixty tertiary indexes. We used this AHP to conduct quantitative risk assessments on five aquatic animals that are typically introduced in China, which have distinct biological characteristics, specific introduction purposes, and can represent different types of aquatic animals. The assessment results show that the risk grade for Pterygoplichthys pardalis is high; the risk grade for Macrobrachium rosenbergii, Crassostrea gigas, and Trachemys scripta elegans is medium; and the grade risk for Ambystoma mexicanum is low. Risk assessment of the introduction of aquatic animals using our AHP is effective, and it provides support for the introduction and healthy breeding of aquatic animals. Thus, the AHP model can provide a basis for decision-making risk management concerning the introduction of species.

ASSESSING THE IMPACT OF FACTORS ON THE SCIENTIFIC RESEARCH PRODUCTIVITY OF LECTURERS

Improving the scientific research productivity of lecturers plays a crucial role in enhancing the quality of teaching and the reputation of a university. The purpose of this study was to determine the priority level of factors impacting the scientific research productivity (SRP) of lecturers. The study employed the Analytic Hierarchy Process (AHP) model to determine the influence of factors on the SRP of lecturers at East Asia University of Technology. In this study, six factors were identified to impact the SRP of lecturers, including: domain expertise (C1), scientific research skills (C2), motivation for engaging in scientific research (C3), lecturer's awareness of scientific research activities (C4), institutional policies for research activities (C5), and research environment (C6). The research findings revealed that domain expertise was the factor with the highest level of impact on the SRP of lecturers, followed by scientific research skills and institutional policies for research activities.
 Keywords: AHP Model, Scientific Research Productivity, Lecturer.

Performance measures of frequency ratio, weight of evidence and AHP models for flood risk assessment of Panchganga river basin (PRB), Kolhapur (India)

Flood events are the most common and frequent natural disasters causing enormous loss to property and life worldwide. In this study, the Panchganga River Basin (PRB) was selected for flood susceptibility mapping using the frequency ratio (FR), weight of evidence (WoE) and Analytical Hierarchy Process (AHP) model with remote sensing and GIS based approach. For this, a flood inventory with 224 historic flood locations was prepared using Google Earth Engine. About 75% of flood locations were randomly selected for training and 25% for testing purposes. The flood susceptibility map prepared using FR, WoE and AHP model was classified into five zones such as very high, high, moderate, low risk and safe zone using ArcGIS software. The receiver operating characteristic (ROC) curves were plotted with area under curve (AUC) of 89.27%, 87.34% and 80.60% for FR, WoE and AHP models respectively. The present study will help people near Panchganga river to move to a safer place during flooding. The flood risk zone maps are extremely helpful in infrastructural developments, town planning and civil protection.

Estimating seismic vulnerability in West Bengal by AHP-WSM and AHP-VIKOR

West Bengal is situated primarily in the Surma Valley at the foothills of the Himalayas and near the western foreland of the Assam-Arakan Orogenic Belt. Several low to moderate-magnitude earthquakes are felt in the region frequently. In this study, we use integrated multi-criteria decision-making (MCDM) models to assess the seismic vulnerability in West Bengal. Twenty-four parameters that were susceptible to seismicity in the region have been used to evaluate geotechnical, structural, social, and physical vulnerability. The analytical hierarchy process (AHP) model was used to estimate the priorities of the parameters, which was then used to estimate seismic vulnerability using the VIseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) and the weighted sum method (WSM). The results reveal that approximately ∼17.81% of the total area and ∼65.36% population may fall under a high to very high-vulnerable zone, causing concerns for planning and disaster mitigation. The receiver operating characteristic curve estimated to validate the results, indicate that the AHP-VIKOR performs better for seismic vulnerability estimation. The results of this study may help various mitigation and planning agencies in identifying earthquake-vulnerable zones and preparing in advance for any potential large magnitude earthquakes that may occur in the region.

Why defuzzification matters: An empirical study of fresh fruit supply chain management

The measurement validity of analytic hierarchy process (AHP) questionnaires used for multi-criteria decision-making (MCDM) and their fuzzification-based extensions have not yet been definitively investigated. In this context, we investigated the effect of a fuzzification procedure on the variable measurement validity and statistical results of an AHP model. Based on market data regarding factors influencing the production and marketing stages of the Taiwanese litchi export chain, we verified whether the estimated variables exhibit unbiased validity after applying a fuzzification procedure using the balanced scorecard framework and MCDM. We also measured the effectiveness of two defuzzification methods—centre of gravity (COG) and extent analysis method (EAM)—and compared their estimation performances. Further, we successfully established fresh fruit supply chain indicators and assigned weights to them corresponding to their importance. The results revealed that global priority values determined using COG were similar to those estimated using the fuzzification-free AHP, which is critical for simple hierarchical structures. The EAM accurately identified the crucial indicators and variables affecting the complex supply system of fresh fruit, highlighting the benefits of fuzzy AHP data application corresponding to extensive hierarchies. The proposed method is expected to aid decision makers in improving the quality of their decision-making by evaluating the effect of data fuzzification with respect to information scale and applying appropriate defuzzification methods to reduce option screening.

IMPACT OF COVID-19 PANDEMIC ON THE AIR QUALITY OF INDIA

Towards the end of 2019, a novel contagious virus (COVID-19) came out of Wuhan, China and turned into a disastrous pandemic. Many countries were locked down; completely or partially. The ongoing pandemic not only affected our economies and routine life, but also the environment. This study was aimed to compare the air quality of the Indian subcontinent prior to and during the COVID-19 pandemic. In this regard, air quality parameters (ozone, nitrogen dioxide, sulfur dioxide, carbon monoxide, PM2.5 and PM10) and meteorological parameters (wind speed and relative humidity) were analysed. The data was obtained from 229 monitoring stations in India and satellite-based Aerosol Absorption Index (AAI) during the springs of 2019 and 2020. The result indicated a significant decline in the concentration mean, six air pollutants (i.e., PM2.5, PM10, NO2, SO2, O3 and CO) decreased by 36.27, 42.96, 44.62, 28.88, 18.35 and 20.51 %, respectively during April 2020 due to less to no industrial activities and vehicular emissions. The spatial variation of each parameter was simulated using the Inverse Distance Weighted (IDW) interpolation method. An Analytical Hierarchy Process (AHP) model was applied to generate the overall air quality severity zonation map of the country. The zonation map indicated that by adopting cleaner fuel and restriction on biomass burning in the rural and urban sectors can improve the ambient air quality.

Online Learning Quality Measurement Application for Higher Education: Development and Analysis Using ISO 9126

This study aims to develop an application for measuring the quality of online learning in higher education using the analytical hierarchy process (AHP) model and analyze the quality of the application using the ISO 9126 standard. This is a Research and Development study. The application development process uses the software development life cycle (SDLC) method with the waterfall method. Furthermore, the application quality analysis process uses the ISO 9126 standard, consisting of functionality, reliability, efficiency, maintainability, usability, and portability. The results showed that the application for measuring the quality of higher education online learning based on the AHP model had been successfully developed using the SDLC method with the waterfall model. Furthermore, the results of the analysis of application quality using the ISO 9126 standard show that the average results are excellent and suitable for assessing the quality of online learning in higher education.
 Keywords: online learning, higher education, analytical hierarchy process (AHP), ISO 9126