Analytical Hierarchical Process Research Articles

DETERMINATION OF SUPERIOR BEAN GENOTYPES IN COOKING AND PHYSICOCHEMICAL BY MULTI-CRITERIA DECISION-MAKING METHOD

It is aimed to examine and predict effects of bean genotypes using cooking and physicochemical properties on seed quality index and yield in this study. The seed quality index was calculated by combining analytical hierarchical process and standard scoring functions, which is one of the multi-criteria decision-making methods, using the linear combination technique. To determine the seed quality index, a data set was created with 11 indicators. analytical hierarchical process was used to weight importance levels of examined traits depending on the genotypes. Seed quality index of registered cultivars according to investigated characteristics of cultivars and genotypes IV. Class, 6 genotype (Bombay genotype) was found to be in class V. Obtained grain quality and physical properties by determining with seed quality index obtained in this study, estimation of seed quality in beans with analytical hierarchical process was evaluated successfully. As a result, according to seed quality index of bean cultivars and genotypes, it was determined that genotype 6 had superior characteristics in terms of productivity, in addition genotypes 8 with 9 and registered cultivars could also show superior characteristics.

Developing an analytic hierarchical process-based tool for assessing sustainability in public schools: a developing country context

ABSTRACT Sustainability and the seventeen sustainable development goals (17SDGs) are gaining increasing importance in different contexts in the globe. Among them are SGD 4 (Quality Education), SDG 6 (Clean Water and Sanitation), SDG 7 (Affordable and Clean Energy), SDG 11 (Sustainable Cities and Communities), SDG 13 (Climate Action) and SDG 15 (Life on Land). To promote these goals, this study aims to develop a reliable tool to assess the economic, environmental and social sustainability in public schools in Palestine, based on the analytic hierarchical process (AHP) approach. To this end, primary data were collected from a random sample of 70 schools via personally administered questionnaires answered by school principals. A school sustainably assessment tool (SSA-tool) was developed based on the analytic hierarchical process (AHP) results using Expert Choice 11 software. The AHP results revealed that environmental, economic and social sustainability weights are 30.3%, 36.5% and 33.2%, respectively. Also, a comparison of the SSA-tool’s weights with other international rating systems, namely, LEED, CASBEE, BREEAM and GP-tool was conducted. To facilitate the use of the SSA-tool, an Excel template of the SSA-tool was developed and validated. The study concludes with recommending specific implementable actions in each sustainability dimension.

Multi-attribute approach for selection of polymeric materials for manufacturing gears: A case study in the automotive industry

Automotive industry is characterized by mass production, a large share in the gross national income and high employment of workers with different knowledge and skills. Improving the production process, as well as product quality, is one of the most important tasks of automotive enterprise as well as government management. This research promotes a new fuzzy hybrid model for determining the priority of polymeric materials for manufacturing gears in an exact manner, which leads to an incremental improvement in the quality of the considered product. The analysis of polymeric materials and their characteristic is based on data from the relevant literature and experiences of the best practice. The relative importance of material characteristics is stated as fuzzy group decision making problem. The weights vector is determined by using the fuzzy Analytic Hierarchical Process and fuzzy geometric mean. The rank of polymeric materials is obtained by employing the proposed Technique for Order Preference by Similarity to Ideal Solution with triangular fuzzy numbers. The fuzzy algebra rules have been used for determining: (i) distances from Fuzzy Positive Ideal Solutions and Fuzzy Negative Ideal Solutions and (ii) closeness coefficient values. The proposed fuzzy hybrid model testing and verification are performed on real data in an automotive enterprise.

GIS-Based Analytical Hierarchy Process for Identifying Groundwater Potential Zones in Punjab, Pakistan

The quality and level of groundwater tables have rapidly declined because of intensive pumping in Punjab (Pakistan). For sustainable groundwater supplies, there is a need for better management practices. So, the identification of potential groundwater recharge zones is crucial for developing effective management systems. The current research is based on integrating seven contributing factors, including geology, soil map, land cover/land use, lineament density, drainage density, slope, and rainfall to categorize the area into various groundwater recharge potential zones using remote sensing, geographic information system (GIS), and analytical hierarchical process (AHP) for Punjab, Pakistan. The weights (for various thematic layers) and rating values (for sub-classes) in the overlay analysis were assigned for thematic layers and then modified and normalized using the AHP. The result indicates that about 17.88% of the area falls under the category of very high groundwater potential zones (GWPZs). It was found that only 12.27% of the area falls under the category of very low GWPZs. The results showed that spatial technologies like remote sensing and geographic information system (GIS), when combined with AHP technique, provide a robust platform for studying GWPZs. This will help the public and government sectors to understand the potential zone for sustainable groundwater management.

Identifying hidden groundwater reserves: GIS advances and multi-criteria decision analysis for enhanced potential assessment

The aquifer system may become susceptible as a result of excessive groundwater extraction without regard for scientific principles. This study evaluates the Groundwater Potential (G.P.) using multicriteria decision analysis (MCDA) and geospatial modelling. Here in MCDA, the G.P. is measured using Remote Sensing (R.S.) and Geographic Information System (GIS), together with Analytical Hierarchical Process (AHP), Fuzzy Analytical Hierarchical Process (FAHP), and Best Worst Method (BWM). Analysis and model creation took into account 15 groundwater affecting elements that affect the G.P. Groundwater Potential Zones (GPZs) in Cachar District, India varied by the following percentages: 46.97%, 37.41%, and 15.62% for AHP; 46.13%, 40.92%, and 12.95% for FHP; and 50.65%, 36.51%, and 12.84% for BWM, respectively, for low, medium, and high zones. The FAHP and BWM models outperformed the AHP model, according to the results of the qualitative validation. The concerned authorities might identify vulnerable locations and plan sustainable groundwater management with the use of these MCDA approaches combined with GIS.

Verifying Welding Processes Selection for a Case Study Using an Analytic Hierarchical Process

This paper aims to develop a framework for differentiating the selection of welding processes using specialized knowledge-based expert systems, which are particularly useful in dealing with issues that require complex decision-making. A program was created and programmed using the process information maps (PRIMAs) matrix in Visual Basic Access for selecting welding processes in a study. The program is in two stages. In the first stage, it excludes non-candidate operations according to several criteria, the most important of which is the type of metal and its thickness. The second stage is arranging operations using multi-criteria methods for decision-making through research to resolve complicated problems involving multiple factors. The hierarchical analysis process (AHP) was used. It is considered one of the most frequently used multi-criteria decision-making methods. The selection of analytic hierarchical process. AHP criteria depend on experience and knowledge rather than specific data for selecting alternatives and determining weights. The methodology is straightforward, easy to comprehend, and applicable to various domains needing intricate decision-making. The program results are compared with those of a previously published case to choose the best welding processes for a study case, which is a home radiator, and results matching the candidate processes were discovered.

Unveiling the impact of digital transformation: a study on key disciplines, technological unemployment, and neo-Luddism in the textile industry

Purpose The primary aim of this study is to identify and analyze the key digital transformation areas and determine their impact on technological unemployment in the textile sector. In addition, this study explores whether digital transformation contributes to neo-Luddism or Robot Breaking. Design/methodology/approach The advent of digital transformation has raised significant concerns, particularly concerning technological unemployment. This study focuses on conducting an analytical hierarchical process (AHP) analysis to determine the impact of different disciplines within digital transformation on technological unemployment. The investigation specifically delves into the ongoing transition to Industry 4.0 within the textile industry. This study uses a mixed-method approach, consisting of a literature review, bibliometric analysis, eight expert phenomenological interviews, and AHP. Findings This study revealed that artificial intelligence, machine learning and deep learning are the most crucial disciplines that will affect the concept of neo-Luddism. The fact that technological unemployment in the textile sector is examined with AHP Analysis makes this study unique. Originality/value This study contributes to Industry 4.0 literature by examining the nexus of technological unemployment in textile manufacturing and the emergence of neo-Luddism.

Re-design methodology for an under-risk multi-business supply network

ABSTRACT Currently, several supply chains of the same business may be managed independently. This is due to different groups of clients or different marketing channels. Parallely, changes in the environment, due to unexpected situations, lead the decision-makers to modify the configuration of supply chains. Therefore, we propose a redesign methodology based on a progression of steps to study holistic synergies. This design analysis is carried out at a static and dynamic level for strategic, tactical and operational decisions. The use of qualitative and quantitative tools allows a set of solutions to be obtained, which take into account inventory levels, processing times, costs and service levels. To compare the preliminary solutions, AHP (Analytic Hierarchical Process) is combined with TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution). It is applied to an example of pharmaceutical distribution in South America. The results indicate an improvement of service levels and a reduction of costs from risks.

Shadowed AHP for Multi-Criteria Supplier Selection

Numerous techniques of multi-criteria decision-making (MCDM) have been proposed in a variety of business domains. One of the well-known methods is the Analytical Hierarchical Process (AHP). Various uncertain numbers are commonly used to represent preference values in AHP problems. In the case of multi-granularity linguistic information, several methods have been proposed to address this type of AHP problem. This paper introduces a novel method to solve this problem using shadowed fuzzy numbers (SFNs). These numbers are characterized by approximating different types of fuzzy numbers and preserving their uncertainty properties. The new Shadowed AHP method is proposed to handle preference values which are represented by multi-types of uncertain numbers. The new approach converts multi-granular preference values into unified model of shadowed fuzzy numbers and utilizes their properties. A new ranking approach is introduced to order the results of aggregation preferences. The new approach is applied to solve a supplier selection problem in which multi-granular information are used. The features of the new approach are significant for decision-making applications.

A GIS-Based Approach for Assessing Urban Development Potential in Federal Capital Territory Nigeria

Urban development potential assessment is essential for guiding the spatial expansion of cities, optimizing land use, and ensuring sustainable urban growth. In the context of rapidly urbanizing regions, such as Nigeria, understanding development potential helps mitigate the challenges of urban sprawl, infrastructure strain, and environmental degradation, hence, this study is aimed at a GIS based approach for assessing urban development potential in federal capital territory Nigeria. The objectives of the study are to: identify and categorize the key factors influencing urban development in the Federal Capital Territory, Nigeria; assess the reliability of the identified factors using consistency index and sensitivity analysis; determine the potential areas for urban development in the Federal Capital Territory, Nigeria using analytical hierarchical process; and produce an urban development potential map defining the extent of urban development potential across the urban landscape of the Federal Capital Territory, Nigeria. The study employed the assessment of relative priorities in modelling and mapping urban development potential in Federal Capital Territory Nigeria. This assessment was based on a comprehensive set of criteria, including slope, elevation, proximity to road network, population density and proximity to developed areas. The Analytical Hierarchical Process was utilized to compare and establish the relative importance of these criteria by means of matrix comparisons. Subsequently, these criteria were assigned relative weights. Weighted Overlay technique was applied to generate the final development potential map. The study revealed that Abuja Municipal Area had the highest potential development area, covering an area 851.40 km2, with Bwari and Kuje Area Councils as having the second and third highest development potential with an area coverage of 312.40 km2 and 279.69 km2 respectively. Gwagwalada and Kwali Area Councils were ranked fourth and fifth with a developable area coverage of 180.20 km2 and 127.60 km2 respectively, while Abaji Area Council was ranked the least with developable area coverage of 40.27 km2. The study successfully integrated an approach to investigate development potential within the Federal Capital Territory. This evaluation approach, is hereby recommended to be used as tool for planning and decision making in urban development in the study area.

Assessment of coastal vulnerability using AHP and machine learning techniques

Vila Belmiro is a significant development in the coastal urban scenario and is nestled along the rugged cliffs of the southern coast of Brazil. Cyclones caused tremendous damage to the shore, destroying infrastructure, eroding the coast, flooding, and displacing people. Determining such low-lying regions' coastal vulnerability index is crucial for developing efficient mitigation strategies and enhancing readiness for calamities. In light of this viewpoint, the current study attempted to determine the Coastal Vulnerability Index (CVI) using the analytical hierarchical process (AHP). The study combined the Physical Vulnerability Index (PVI) and the Social Vulnerability Index (SVI) to create the Coastal Vulnerability Index. This study generated the LULC layer for Vila Belmiro using machine learning techniques and Random Forest based model. A component of the process was evaluating the parameters pairwise based on their importance and relevance to the study's objective. The CVI assessment classified 19.28 Sq.km of the coastline, including Solemar, São Vicente, Santo, and Ponta Da Praia, as very high risk. High-risk areas, such as São Vicente, Vila Caicara, and Guaruja, span 25.26 Sq.km. Medium risk was observed across 16.85 Sq.km, covering Praia Grande, Nova Mirim, and Balneario Praia. Low-risk regions, including Japui and Jarfim Guaiuba, extend over 13.54 Sq.km. Lastly, 10.78 Sq.km of the coastline, including Canto Do Forte, were classified as very low risk. These measurements highlight the varying levels of vulnerability along the coastline. The study concluded that coastal vulnerability zones were effectively identified and assessed, enhancing understanding and management of coastal risks. Planning and mitigating future cyclones can benefit from the identified vulnerable zones. The current study included machine learning, remote sensing, Geographic Information System (GIS), and advanced facilities that were spatially integrated with AHP approaches.

Combination of macroscopic and microscopic crash prediction models with multiple modeling approaches: A highway case study

Road traffic crashes are a global problem and represent a major cause of mortality among children and young people worldwide. Crash prediction models (CPM) play a crucial role in identifying crash-prone areas by predicting the expected number of crashes, thus facilitating the implementation of proactive measures. Previous studies have explored various CPM based on spatial analysis or modeling approaches. Nonetheless, a substantial gap still exists in exploring CPM that simultaneously address the combination of spatial units and modeling approaches, using of heterogeneous data at both the macroscopic and microscopic levels to develop models using Multi-Criteria Decision-Making and Statistical methods. Thus, the objective of this study is to develop multiple CPM using various spatial units of analysis and employing different modeling approaches, combine them, and conduct comparisons to determine the final model that best fits the data. A total of 7 models have been developed: three at the macroscopic level, utilizing Analytic Hierarchy Process (AHP), Negative Binomial (NB), and a combination of both; one at the microscopic level using Geographic Weighted Poisson Regression (GWPR). Additionally, three combined models bring together the previous from both levels, resulting in AHP+GWPR, NB+GWPR, and AHP+NB+GWPR models. These combined and individual models have been compared, and the best-performing has been selected through a validation process. The models were calibrated using data from a case study of a highway located in the northwest of Spain for the period 2016 to 2020. Subsequently, predictions for the year 2021 were made and compared to the actual crash occurrences during that year. The results indicate that the best model is the one that combines the macroscopic and microscopic levels using the approaches AHP+NB+GWPR, which presents a Mean Absolute Deviation (MAD) of 1.55, a Mean Square Error (MSE) of 2.89, does not underestimate any segments and shows a recall of 0.88. The results obtained confirm that the combination of models at the macroscopic and microscopic levels yields the best crashes predictions. This approach offers the advantage that our model, in addition to learning from historical data using statistical methods, also fits to the importance weights assigned by knowledgeable experts on the crashes propensity of the highway in the case study area using the Analytical Hierarchical Process.

Seeking silver lining for leaders' well-being: understanding gender differences in work-family conflict, leadership style and prioritizing coping strategy

PurposeOur study addresses the impact of COVID-19-induced work-family conflict on leaders' well-being and explores the influence of leadership style, coping strategies, and gender disparities in this context, filling a research gap on crisis-related leadership well-being.Design/methodology/approachWe used hierarchical regression analysis and SPSS's PROCESS macro to analyze a dataset of 516 paired responses, including 231 leaders and 285 subordinates, from Mongolian organizations.FindingsStrain-based work-family conflict (WFC) negatively affects leaders' workplace well-being. Servant leadership exacerbates this impact. In contrast, servant leadership positively moderates the relationship between time-based WFC and job-related well-being. Leaders who prioritize work and family responsibilities experience a stronger positive (negative) impact of time-based (strain-based) WFC on their workplace well-being. Furthermore, we observed that strain-based WFC has a more detrimental effect on female leaders' well-being, highlighting gender disparities in leadership roles.Practical implicationsOur study elucidates the intricate relationship between work-family conflict and leaders' well-being, underscoring the need to recognize gender differences and coping strategies. We advocate for organizations to proactively establish support structures tailored to various leadership styles and gender-specific challenges, especially in times of crisis.Originality/valueThis study focuses on leaders' well-being during COVID-19 and how it is influenced by work-family conflict, servant leadership, coping strategy, and gender. The study also differentiates between time-based and strain-based work-family conflict and uses dyadic data from Mongolian organizations. More importantly, we identify that gender disparity plays a crucial role in the pandemic-caused leadership challenges and leaders' coping behaviors.

A fuzzy approach to environmental scanning (ES) of multi-factor bottlenecks to renewable rural energy sustainability in Nepal

ABSTRACT Due to the prevalence of traditional fuels and the increasing awareness of their negative effects on sustainability, policymakers and government authorities in Nepal have been compelled to transition towards promoting the adoption of clean energy. Nevertheless, as a result of numerous obstacles, the rate of renewable energy utilization has remained sluggish. Therefore, the country’s policymakers must become acquainted with the factors that impede the progress of renewable energy. The objective is to pinpoint the constraints, restrictions, and barriers that hinder the advancement of renewable energy access to rural communities in Nepal. The current study used the Delphi Technique of Environmental Scanning to identify the barriers impeding the adoption of renewable energy. In addition, an Exploratory Factor Analysis (EFA) was performed to redefine categories of bottlenecks depending on the direction of the factors in the context of Nepal. Ultimately, the Fuzzy Analytical Hierarchical Process (FAHP) has been employed to determine the priority of distinct bottlenecks of clean energy development. The study suggests that Nepal’s advancement in sustainable energy is hindered by financial obstacles, primarily due to the significant initial investment, which accounts for 19% of the challenges, and the lack of effective fiscal incentives provided by the government to developers and users, which accounts for 10.6% of the challenges. The research identified many contributory reasons, including the function of regulatory organizations (6.4%), inadequate political commitments (6%), inefficient existing energy policy (5%), and poor public knowledge (5%). To promote the development of sustainable energy sources in rural areas, it is crucial to implement economic incentives, provide financial support, establish partnerships between the public and private sectors, and utilize innovative financing methods such as green bonds, crowdfunding, and carbon financing. Additionally, it is necessary to increase political commitments to amend existing renewable energy policies in the country.

The Study of APIPA Model Concept Development through the Application of Analytical Hierarchy Process (AHP)

Improving the quality of teacher performance programs certainly requires the important role of teachers and school leaders. The role of teachers can be seen in the implementation of performance programs which require systematic and structured evaluation of performance programs. The results of the evaluation and monitoring of the implementation of the teacher performance program by school leaders are used as material for consideration in making decisions about the quality level of the teacher performance program. Making this decision is very difficult for a school leader in evaluating teacher performance programs. In this case, a modified program evaluation was developed by the CIPP model program evaluation with ALKIN model program evaluation. The research used Development Research (R&D) using 4D design (Define, Design, Development, Dissemination). The Define stage conducts a literature review regarding weaknesses in the CIPP and ALKIN model program evaluation syntax. The Design stage prepares the topology related to the main ideas of the program evaluation development syntax. The Development stage carries out operational definitions and indicators for each program evaluation syntax. The dissemination stage carries out an expert judgment or assessment of the experts who are analyzed using the analytical Hierarchical Process (AHP) to determine the consistency of the program evaluation development concept. The results using AHP are consistent with the concept of developing the APIPA model program evaluation which has the syntax Assessment, Planning, Implementation, Product, and Appreciation for evaluating teacher performance programs.

Structure of Public Passenger Transport Lines in the Region of Prešov in Slovakia to Support the Development of an Integrated Transport System

In the framework of sustainable development, the most important goal in the transport sector is sustainable mobility. It is necessary to improve the quality of the means of transport and the organisation of their operation in transport systems in addition to the management systems, coordination, and integration of individual types of transport. The aim of this paper is to propose a complex system of public transport lines in the region to achieve an effective transport service, in accordance with the principles of sustainable mobility, supporting the development of an integrated transport system. This research presents a proposal for the public transport lines of the region of Prešov in Slovakia, which is currently connected to an integrated transport system (IDS Východ). The proposal is defined by the tracing and functions of the lines, the mode of transport and headways on individual lines, the necessary number of vehicles for the operation of individual lines, transfer times at relevant points and directions, and the border of the radius of attractive daily commuting to the centre of the region, as well as a rough timetable for each line. Using an analytical hierarchical process (AHP method), we determine the two most suitable variants of traffic services. The results indicate that based on the multicriteria evaluation of these variants using descriptors, it is possible to determine the optimal variant of the transport service of the region, which will be introduced into a functional integrated transport system.

Selection of optimal areas for the installation of Wind Farms in the north-eastern part of Cuba

The present research aims to select optimal areas for the installation of wind farms in the north-eastern part of Cuba. The research is based on the free software QGIS, Hierarchical Process Analysis, databases of the information of the alternatives and criteria and Geographic Information Systems (GIS), which makes it possible to know the places where these farms will be installed. In addition, experts were consulted to obtain the weights or level of importance of the selected criteria, such as distance to ports, distances to common roads, distances to population centers, to electrical grids and finally the wind speed. As a result, a mathematical conceptual model was obtained for the selection of optimal zones for the installation of wind farms in the eastern north of Cuba, by means of the MCDM and GIS methods, where it was determined that, within the evaluated alternatives of wind farms, Gibara III is the optimal one. These models will allow the development of wind projects in the eastern region of Holguin, and to be able to manage human, financial and material resources.

Analyzing barriers to the adoption and development of electric vehicles: A roadmap towards sustainable transportation system

Electric vehicles (EVs) are positioned as an alternate green energy technology, which potentially can enable the efficient transition to sustainable low-carbon emission transportation systems. However, different barriers hamper the public adoption of EVs. The degree to which these barriers prevent the adoption of EVs and the potential alternatives to these barriers are mostly unknown. To fill this research gap, the current study contributes by systematically identifying those barriers based on their importance. Initially, several barriers were identified using existing literature, and then by employing the modified Delphi method, a total of twenty-five barriers were classified into five significant dimensions. The Analytical Hierarchical Process (AHP) determined the rankings of these barriers based on weight allocation. As a next step, the Grey Technique for Order Preference by Similarity to Ideal Solution (G-TOPSIS) ranked alternative solutions to these barriers. The findings indicate that 'technological barrier' is the top-ranked barrier among all major dimensions. The overall ranking indicated that 'battery technology' is most influential among sub-dimensions. It is recommended that "investment in research and development" is the best alternative to overcome these barriers. In order to improve the renewable and sustainable urban transportation system, all stakeholders should cooperate in a consistent and coherent manner.

AHP and geospatial technologies for identifying groundwater exploration target regions in Dindigul, southern India

Recent advances in space technology are being widely utilized in resource mapping and management as they provide a high level of accuracy over a short duration and at a lower cost, when compared to traditional methods. Remote sensing and the geographical information system (GIS) play a vital role in collecting and analyzing information used to map resources and earth surface features. For example, anthropogenic activities and climate change affect the natural interaction between the surface and ground water making the monitoring and management of groundwater resources mandatory for future sustainable development. In this study, we attempt to identify the groundwater potential zones in the Dindigul district of Tamil Nadu, India using these emerging technologies. To map regions with groundwater potential, the analytical hierarchical process (AHP) was used to assign weights to all classes in each thematic layer based on groundwater-influencing factors. The sub-features of every parameter were also ranked, using a pairwise comparison method, based on the groundwater-influencing factors and expert knowledge. The parameters selected for the analysis were geology, geomorphology, soil, land-use/land-cover, drainage density, lineament density, slope, rainfall, thickness of top-soil, thickness of fractured zone, thickness of weathered zone, topographic wetness index, roughness and curvature. The weighted overlay analysis method was adopted for all the thematic layers, with technical support from the AHP for assigning weightages. The results were classified into five categories viz., very high, high, moderate, low, and very low potential zones, and used to prepare a groundwater potential map. This map revealed a nuanced distribution of groundwater potential across the district, with varying degrees of potentiality in different regions. Very high potential zones occupy a minimal area (0.07%) but are strategically located in areas characterized by high weathered zone thickness and conducive soil characteristics. High potential zones cover a significant area (22.33%) and are dispersed throughout the district, with specific concentrations in regions featuring highly fractured zones and favorable geological attributes. Moderate potential zones (35.12%) are primarily located in the northeastern part of the study area, while low and very low potential regions cover 19.56% and 22.92% of the study area. The low and very low potential zones appear particularly in hilly terrains, with unfavorable top soil and geological conditions. The validation of the groundwater potential zone (GWPZ) map using the annual average water level data demonstrates a substantial match (60.53%) between the identified groundwater conditions and actual well depths, affirming the reliability and significance of the findings from this study.

Flood Monitoring and Mapping in the Ghatal Region of West Bengal, India

Abstract The Ghatal block of Paschim Medinipur district in West Bengal, India experiences frequent flooding due to the overflow of the rivers Dwarakeswar, Rupnarayan, Shilabati, and their tributaries. Although the Ghatal master plan was prepared and the foundation stone was placed in 1982 to reduce the flood vulnerability in this region, the plan is still not being implemented. To determine the flood vulnerability in the Ghatal block, very few research investigations have been carried out. The previous studies just applied a successful scientific methodology to evaluate flood risk; they did not engage in participatory research with local community perception. Hence, a thorough investigation is needed to manage floods in a way that increases community resilience. Using a comparative review and the geographic information system (GIS), the study seeks to identify the flood-prone locations in the Ghatal block, which is essential for flood management in any region. The article uses a multi-criteria analysis to pinpoint probable flood hazard regions. Seven parameters are used in the study to carry out the multi-criteria analytical hierarchy procedure. Based on their relative importance for the event, the criteria’s weights are determined using the Analytical Hierarchical Process (AHP) method, and a Suitability Index is prepared. The index indicates that the severe problem of river flooding in the Ghatal block of Paschim Medinipur needs to be looked after on an urgent basis and with path-breaking solutions, especially for the Ghatal municipality and the various gram panchayats such as Irpala, Mansuka-I, Monoharpur-I, Ajobnagar-I, Mohonpur, Dewanchak-I and the North-Eastern part of Sultanpur and the Southern part of Dewanchak-II.