Analytic Hierarchy Process Research Articles

Groundwater potential mapping and its sustainable management using AHP and FR models in the Jedeb watershed, Upper Blue Nile Basin, Ethiopia

ABSTRACT Groundwater potential mapping and its sustainable development are important aspects of the Jedeb watershed due to an increase in groundwater demand and the local population. This study aimed to delineate potential groundwater zones in the Jedeb watershed, using the analytical hierarchy process (AHP) and frequency ratio (FR) model. Nine thematic layers, including lithology, geomorphology, slope, drainage density, land cover and land use, lineament density, rainfall, soil, and static water level, were considered. The thematic layers obtained were integrated into a Geographic Information Systems (GIS) environment to generate the groundwater potential map. Four classes of groundwater potential have been identified: low, moderate, high, and very high. The low classes represent 12.8% and 7.02%; moderate 25.35% and 34.84%; high 38.8% and 33.11%; and very high 23.05% and 25.03%, for the AHP and FR models, respectively. The result map was also validated by using receiver operating characteristic (ROC) curve from which result accuracy was obtained is 85.6% and 88.3% for the AHP method and FR method, respectively. The study's validation verified that the FR model produced more efficacious results than the AHP model. This study, will be helpful in providing planners, and decision-makers with rapid decision-making when it comes to managing groundwater resources.

Integrated Geospatial and Analytical Hierarchy Process Approach for Assessing Sustainable Management of Groundwater Recharge Potential in Barind Tract

Groundwater depletion in Bangladesh’s Barind tract poses significant challenges for sustainable water management. This study aims to delineate groundwater recharge potential zones in this region using an integrated geospatial and Analytical Hierarchy Process (AHP) approach. The methodology combines remote-sensing data with GIS analysis, considering seven factors influencing groundwater recharge: rainfall, soil type, geology, slope, lineament density, land use/land cover, and drainage density. The AHP method was employed to assess the variability of groundwater recharge potential within the 7586 km2 study area. Thematic maps of relevant factors were processed using ArcGIS software. Results indicate that 9.23% (700.22 km2), 47.68% (3617.13 km2), 37.12% (2816.13 km2), and 5.97% (452.70 km2) of the study area exhibit poor, moderate, good, and very good recharge potential, respectively. The annual recharge volume is estimated at 2554 × 106 m3/year, constituting 22.7% of the total precipitation volume (11,227 × 106 m3/year). Analysis of individual factors revealed that geology has the highest influence (33.57%) on recharge potential, followed by land use/land cover (17.74%), soil type (17.25%), and rainfall (12.25%). The consistency ratio of the pairwise comparison matrix was 0.0904, indicating acceptable reliability of the AHP results. The spatial distribution of recharge zones shows a concentration of poor recharge potential in areas with low rainfall (1200–1400 mm/year) and high slope (6–40%). Conversely, very good recharge potential is associated with high rainfall zones (1800–2200 mm/year) and areas with favorable geology (sedimentary deposits). This study provides a quantitative framework for assessing groundwater recharge potential in the Barind tract. The resulting maps and data offer valuable insights for policymakers and water resource managers to develop targeted groundwater management strategies. These findings have significant implications for sustainable water resource management in the region, particularly in addressing challenges related to agricultural water demand and climate change adaptation.

Soil Erosion Susceptibility Prediction Using GIS-Based Multicriteria Analysis and Worldview-3 Satellite Images

Soil erosion has been identified as a major threat to existing soil deposits, which negatively affects ecosystem sustainability, agricultural production and clean water supply. This study covered the eastern part of Kaštela Bay with the aim of developing a model of susceptibility to soil erosion by applying the GIS-based multicriteria analysis, based on nine determinant criteria categorized by the Jenks method in five classes. The largest representation of soil erosion susceptibility was detected on the slopes of the Kozjak and Mosor massifs. According to the calculated weighting coefficients using the analytic hierarchy process (AHP), the slope was the most impactful criterion with 29.9 % importance. It was followed by hydrological criteria of topographic wetness index, standardized precipitation index and LS-factor, with 13.1 % importance each. After the development of the model, zones of very high and high susceptibility to soil erosion were delineated, with a combined coverage of 33.34 % of the study area. These areas were identified as a potential threat from the future occurrence of negative effects of soil erosion, which should be addressed in the future by land policy managers and government managers.

Priority Variables for Handling Slum Settlements Based on the Tourism Village Concept in Sedau, Singkawang City

The issue of slum settlements in Singkawang City has garnered government attention, with Sedau identified as the third priority area for intervention. However, many revitalization efforts fail due to mismatched methods that do not consider environmental, social, and economic characteristics. This study aims to identify priority variables for addressing slum settlements based on the concept of developing a tourism village to improve residents' quality of life and support local economic development. The research method employed is expert judgment through the Analytical Hierarchy Process (AHP), which helps evaluate relevant variables. The findings reveal four main priority variables: good accessibility, a unique tourism village concept, provision of clean water, and waste management. These findings provide important insights for decision-making in planning interventions. Recommendations are directed at the government, development sectors, and the Sedau community, emphasizing the need for better planning, particularly regarding accessibility and infrastructure such as roads, water supply, and waste management. The study also notes its limitations to provide context for the generalization of results and to guide future research. Keywords: planning, slum settlement, tourism village, tourism

Optimization of ore pillar recovery based on weighting combined with uncertainty measurement theory

Abstract Given the multi-objective nature and inherent uncertainty in evaluating ore pillar mining schemes, the analytic hierarchy process (AHP) and entropy method were applied to determine factor weights. A new combined weighting method was proposed to obtain more objective and accurate results. Seven quantitative and four qualitative indicators were selected based on various mining performance factors and grading standards. A combined weighting–uncertainty measurement theory evaluation model was then constructed, integrating weight values and confidence levels from the recognition criteria. This model was applied to evaluate three proposed schemes, determining their relative merits and ranking. The evaluation demonstrated that the combined weighting–uncertainty measurement model outperformed both the fuzzy theory and the TOPSIS method in delivering comprehensive, objectivity and reliable results for assessing ore pillar mining schemes.

Fault tolerant & priority basis task offloading and scheduling model for IoT logistics

The Internet of Things (IoT) has connected millions of devices to the internet for communication and computation purposes. Due to constraints such as limited battery power, processing capabilities, and storage capacity, IoT devices often rely on remote fog nodes for task execution, a practice known as task offloading. The NP-hard nature of offloading and scheduling IoT tasks onto fog nodes poses significant challenges. Current IoT task offloading often relies on single parameters like device MIPS, RAM, or battery power. Similarly, task allocation on fog nodes frequently prioritizes VM MIPS. To address energy consumption and task failures in IoT systems, robust fault tolerance, efficient task offloading, and effective scheduling are crucial. This paper introduces a novel Fault-Tolerant, Priority-Based Task Offloading and Scheduling Model (FP-TOSM) for IoT logistics. Utilizing the Analytic Hierarchy Process (AHP) for multi-criteria decision-making, IoT tasks are prioritized. Tasks below a specified threshold are executed locally, while those within a defined range are offloaded to a fog node. Tasks exceeding this range are delegated to the cloud. The Euclidean formula is used to determine the proximity between the IoT logistics vehicle and fog nodes for offloading decisions. Dynamic re-clustering fault tolerance mechanisms are utilized to manage task failures after offloading. Successful offloaded tasks are allocated to suitable VMs in the cloud and fog nodes. The proposed strategy selects the most suitable VM for offloaded tasks using a multi-criteria decision-making process to reduce energy consumption, SLA violations, and execution costs. The model's performance is evaluated through simulations in iFogSim2. Results demonstrate reductions in energy consumption by up to 5.8 % and 10.4 %, decreases in SLA violations by up to 25.2 %, and a 16.28 % improvement in response time compared to an ACO-based model with a response time of 17.8 %. Additionally, the task failure ratio shows a significant reduction of up to 22.1 %. These findings highlight the effectiveness of FP-TOSM in enhancing efficiency and reliability within fog computing environments.

Application of a GIS-Based Multi-Criteria Decision-Making Approach to the Siting of Ocean Thermal Energy Conversion Power Plants: A Case Study of the Xisha Sea Area, China

In order to achieve the goals of carbon neutrality and reduced carbon emissions, China is increasingly focusing on the development and utilization of renewable energy sources. Among these, ocean thermal energy conversion (OTEC) has the advantages of small periodic fluctuations and large potential reserves, making it an important research field. With the development of the “Maritime Silk Road”, the Xisha Islands in the South China Sea will see a growing demand for electricity, providing the potential for OTEC development in this region. Optimal site selection of OTEC power plants is a prerequisite for developing thermal energy provision, affecting both the construction costs and future benefits of the power plants. This study establishes a scientific evaluation model based on the decision-making frameworks of geographic information systems (GISs) and multi-criteria decision-making (MCDM) methods, specifically the analytic hierarchy process (AHP) for assigning weights, the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to reclassify the factors, and weighted linear combination (WLC) to compute the suitability index. In addition to commonly considered factors such as temperature difference and marine usage status, this study innovatively incorporates geological conditions and maximum offshore distances of cold seawater based on cost control. The final evaluation identifies three suitable areas for OTEC development near the Xuande Atoll and the Yongle Atoll in the Xisha Sea Area, providing valuable insights for energy developers and policymakers.

Development of a fuzzy analytic hierarchy process model, sensitivity analysis, and addressing barriers to additive manufacturing implementation in small- and medium-sized enterprises (SMEs)

Additive manufacturing (AM) is gaining popularity worldwide due to its potential to revolutionize manufacturing processes, improve product customization, and reduce waste. Nevertheless, small- and medium-sized enterprises (SMEs) encounter major challenges when implementing AM technologies. The objective of this research is to utilize the fuzzy analytic hierarchy process (FAHP) to identify and prioritize the critical challenges that impede the implementation of AM for SMEs. The study employs a two-stage methodology. First, a thorough literature review and expert discussions identify 15 major barriers to AM adoption. Second, a systematic model is proposed to establish a ranking of these barriers, which is based on the FAHP. The results are validated using sensitivity analysis to ensure the robustness of the findings. Additionally, potential solutions to overcome these barriers are discussed. The research indicates that the two most significant barriers for SMEs are the high costs of equipment and the scarcity of skilled designers. The model that has been presented is a valuable resource for SME managers and practitioners, as it allows them to make strategic and informed decisions that facilitate the efficient implementation of AM. This research is groundbreaking in its comprehensive analysis of the prioritization and ranking of AM implementation barriers, with a particular emphasis on SMEs. It offers essential insights for future research and practical applications.

GIS‐based surface irrigation potential assessment of Gololcha River Watershed, Awash Basin, Ethiopia

AbstractThe Gololcha River Watershed is lacking comprehensive assessment of land suitability for surface irrigation, available water potential, and prioritized irrigable areas. This study aims to evaluate the potential of land and water resources for surface irrigation in the Gololcha River Watershed. The study employed a multi‐criteria analysis approach using the analytical hierarchy process (AHP) and ArcGIS to assess land suitability, considering factors like slope, land use/cover, soil characteristics, and proximity to water sources. The observed mean monthly water flow potential for each sub‐watershed was statistically evaluated, and the area ratio approach was used to transfer discharges from gauged sites to the site of interest. Irrigation water requirements for three major crops in the study area were calculated using the CROPWAT8.0 model. The findings revealed an average water availability for irrigation of 2.70 m3/s/month, 1.10 m3/s/month, and 1.03 m3/s/month for the Kurkura, Midagdu, and Wefi sub‐watersheds, respectively, with a total annual river flow of 161 m3/s. Based on the suitability analysis, 2508 ha (7.27%) of the watershed area was classified as highly suitable for surface irrigation, 16,420 ha (47.565%) as moderately suitable, 1502 ha (4.35%) as marginally suitable, and 14,029 ha (40.71%) as unsuitable. The overall surface irrigation potential, aligned with available water, was estimated at 4872.58 ha. However, due to water limitations, only 14.15% of the total suitable land can be irrigated using existing flows. The study highlights the significant potential for expanding surface irrigation in the Gololcha River Watershed, particularly during the rainy seasons when substantial water flows are available. The findings provide valuable insights for developing sustainable irrigation strategies, enhancing agricultural productivity, and contributing to food security in the region.

Research on the Structural Design of a Pressurized Cabin for Civil High-Speed Rotorcraft and the Multi-Dimensional Comprehensive Evaluation Method

For civil high-speed rotorcraft designed to operate at specific cruising altitudes, this study proposes nine structural design schemes for pressurized cabins. These schemes integrate commonly used materials and processing technologies in the aviation industry with advanced PRSEUS (Pultruded Rod Stitched Efficient Unitized Structure) technology. An analysis of the structural composition reveals that frames constitute 8–19% of the total structural weight, while stringers and beams make up 15–50%, and skins account for 11–25%, with thicknesses ranging from 1.0 mm to 2.0 mm. The separating interface of the pressurized cabin contributes 4–29% of the total structural weight. The weight distribution of each component in the pressurized cabin structure varies significantly depending on the chosen materials and processing technologies. Utilizing the Analytic Hierarchy Process (AHP), along with Gray Relational Analysis (GRA) and Dempster–Shafer (D-S) evidence theory, this study compares the simulation results of the nine schemes across multiple dimensions. The findings indicate that the configuration combining 7075 aluminum alloy and T300 composite material has the greatest advantages in terms of the high structural reliability of the configuration, light weight, mature processing technology, and low production cost. This comprehensive evaluation method quantitatively analyzes the factors influencing the structural configuration design of the pressurized cabin for civil high-speed rotorcraft, offering a valuable reference for the design of similar structures in related fields.

Cloud Model-Based Intelligent Construction Management Level Assessment of Prefabricated Building Projects

Intelligent construction is vital for achieving new building industrialization by enhancing prefabricated buildings through integrated, digital, and intelligent management across production and construction processes. Despite its significance, detailed research on evaluating the intelligent construction management (ICM) level of prefabricated projects remains limited. This study aims to develop a comprehensive, multi-level, multi-dimensional ICM assessment system. By reviewing the literature, engaging in expert discussions, and conducting case studies—specifically using a project in Guangzhou as an example—this study employs the Analytic Hierarchy Process (AHP) and entropy weight methods to assign indicator weights. Utilizing cloud model theory, it establishes evaluation standards for intelligent construction management. This model identifies the project’s ICM level, suggests practical improvement methods, and validates its applicability. This work not only advances theoretical understanding but also provides a practical framework for assessing ICM levels in prefabricated projects, thus contributing significantly to the field by offering new research perspectives and empirical evidence.

Analisis Supplier Relationship Management (SRM) Produk Bahan Cat pada PT. XYZ Menggunakan Analytical Hierarchy Process (AHP)

PT. XYZ, a major automotive company in Indonesia, requires supplier evaluation to maintain the stability of its production processes. To achieve this, a comprehensive analysis is necessary, utilizing the Analytic Hierarchy Process (AHP) method. This method involves evaluating criteria such as delivery time, price, and quality. The number of suppliers evaluated is two. Data for the criteria was gathered through direct interviews with the Purchasing Administration Division. The results of the AHP analysis indicate that Supplier A is the best supplier for providing raw materials to PT. XYZ.

Land cover and drought risk assessment in Türkiye's mountain regions using neutrosophic decision support system.

Earth observation (EO) provides dynamic scientific methods for tracking and defining ecological parameters in mountainous regions. Open-source platforms are frequently utilized in this context to efficiently collect and evaluate spatial data. In this study, we used Collect Earth (CE), an open-source land monitoring platform, to reveal and assess land cover, land cover change, and relevant ecological parameters such as drought risk. Mountain ecosystems were subject to an evaluation for the first time by combining remote sensing with a hybridization of Decision-Making Trial and Evaluation Laboratory (DEMATEL), analytic hierarchy process (AHP), and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) for neutrosophic sets in risk assessment problems of several connected criteria. The high and dispersed high alpine environment of Türkiye accommodates land with relatively less human influence, making it suitable to observe climate change impacts. In the framework of the study, we evaluated more than two decades (2000-2022) of land use and land cover (LULC) changes in the mountain regions of the country. Using nine identified ecological parameters, we also evaluated drought risk. The parameters included were the LULC classes and their change, elevation, slope, aspect, precipitation, temperature, normalized difference vegetation index (NDVI), water deficit, and evapotranspiration (ET). The risk map we produced revealed a high to very high drought risk for almost throughout the Türkiye's mountainous areas. We concluded that integrating geospatial techniques with hybridization is promising for mapping drought risk, helping policymakers prepare effective drought mitigation measures to reasonably adapt to climate change impacts.

Extraction, pharmacological prediction and experimental verification of Coreopsis tinctoria flowers

Coreopsis tinctoria (C. tinctoria) is a traditional plant with high medicinal value and edible value. It has the effect of invigorating spleen and stomach and has the potential to develop into flower tea. Therefore, the extraction process of C. tinctoria extract (CTA) was optimised by analytic hierarchy process (AHP) combined with orthogonal test, and its activity was predicted by network pharmacology and verified by experiments. The optimal extraction conditions: temperature of 80 °C, extraction period of 10 min, solid-liquid ratio of 1:70 and times 2. CTA had no gastrointestinal irritation and can significantly increase the faecal water content of mice, inhibit amylase activity, increase protease, xylanase and cellulase activity, increase the number of intestinal Lactobacillus and Bifidobacterium, reduce the number of Escherichia coli and Enterococcus. In summary, CTA can effectively improve the intestinal digestive enzyme activity and the number of probiotics and has the potential to treat gastrointestinal diseases.

Landfill site selection using analytical hierarchy process and GIS: a case study in Al-Zubair district, Basrah, Iraq

Landfill site selection using analytical hierarchy process and GIS: a case study in Al-Zubair district, Basrah, Iraq

A Risk Assessment Model of Gas Pipeline Leakage Based on a Fuzzy Hybrid Analytic Hierarchy Process

Given the rising urban demand for gas, it has emerged as a primary energy source for urban activities and daily life. However, China’s urban gas pipeline network has witnessed a surge in accidents, leading to significant losses and disasters. Therefore, it is particularly necessary to study the disaster risk assessment model caused by urban gas pipeline leakage. There are some problems in the previous evaluation methods, such as less consideration of the influence relationships between disaster factors. To redress this issue, a novel fuzzy hybrid analytic hierarchy process evaluation methodology is proposed. First, a hybrid hierarchical risk assessment model is developed by combining the analytic hierarchy process and the network analytic hierarchy process. Membership matrices and impact matrices are utilized to calculate comprehensive factor weights. This approach enhances the understanding of relationships between risk factors within the hierarchical structure model. Subsequently, employing a fuzzy evaluation method, the risk level matrix is derived by using multiplication and bounded operators to ascertain the risk level state. This solves the problem of the fuzzy boundaries when measuring the index factors of the gas pipeline network. Finally, experimental analysis is carried out on the gas pipeline network in the central area of a city and validates the model’s accuracy in practical applications.

Groundwater Potential Zone Delineation through Analytical Hierarchy Process: Diyala River Basin, Iraq

Groundwater recharge zone identification is vital for managing water resources, particularly in semi-arid and dry climates. Accurate and quantifiable assessment is necessary for the sustainable management of groundwater resources, and it is possible to carry this method out using modern techniques and technical standards. To identify likely groundwater locations in the Diyala River Catchment, Iraq, which serves as an example study basin, the current research examines a new methodology that employs a geographic information system, and an Analytical Hierarchy Process connected with remote sensing data. The technique of ArcGIS was employed to generate spatially distributed thematic layers of rainfall, lithology, slope, drainage density, land use/land cover, relief and soil. The raster data from these layers were then converted and categorized. The weights assigned to thematic strata depended on their significance relative to groundwater occurrence. A pairwise judgement matrix for the Analytical Hierarchy Process was used, with the categorized ranking, to assess the standardized weights of the layers under consideration. The layers for the formation of groundwater zones have then been placed using the overlay-weighted summation approach. Three regions, which are classed as excellent, good and moderate, have been identified on the resulting groundwater potential zones map, representing roughly 29, 69 and 2% of the basin’s total area, respectively. The study’s conclusions indicate that, in such a climate, the adopted strategy would produce favourable results to promote the organizing of opinions and the sustainable use of groundwater resources.

Development of an Indicator System for Evaluating Risks in Trekking Tourism

In today’s fast-paced and and high-stress society, trekking tourism is a leisure activity for stress relief and closer nature engagement. Given the adventurous nature inherent in trekking tourism, risk assessment is deemed both crucial and imperative. This study aims to develop a risk assessment framework for trekking tourism based on the Delphi method and Analytic Hierarchy Process (AHP). Initially, we conducted a literature review and expert interviews grounded in the Systems Theory of Accident Causation and the Human Factors Theory to establish the risk assessment paradigm specific to trekking tourism. Subsequently, we ascertained specific weights for each evaluation criterion and delineated explicit data sources for each operational indicator. The findings indicate that the formulated risk assessment system for trekking tourism is both scientifically grounded and practical, furnishing stakeholders in the tourism industry, organizational teams, and management authorities with an efficacious tool for evaluating the safety conditions of trekking tourism activities.

An approach for urban agglomerations integration evaluation based on multivariate big data: case of the Central Plains Urban Agglomeration

ABSTRACT The Central Plains Urban Agglomeration (CPUA) is a link of economic development to connect the eastern part and western part in China. Current research on urban agglomeration integration mainly uses urban properties’ data. This paper conducts an evaluation method for urban agglomeration integration based on multivariate big data. This method mainly applies eigenvector centrality to assess the integrated situation of the CPUA from four dimensions (internet connection, industrial economy, public service and coordinated governance). The data of this research mainly includes cell phone signaling data, Baidu index, industrial investment data and statistical data for planning. The main innovations and contributions of this research is that (i) on the theoretical aspect, this research proposed an index indicator evaluation system for integration of urban agglomerations based on Analytic Hierarchy Process (AHP) and expert rating. It contributes for the further development of regional integration and other related theories; (ii) on the practical aspect, this study, taking the CPUA as example, presents an assessment approach that uses multivariate big data to measure the current integrated situation of urban agglomeration. This method provides decision-making support for the development of urban agglomeration integration.

ANALYSIS OF ECOTOURISM AND DISASTER MITIGATION DATA AT THE KUALA LANGSA MANGROVE FOREST BY USING THE ANALYTIC HIERARCHY PROCESS

The problem in the management of a public area is to determine aspects that contribute most as its best practices. This paper explores the contributions of the Kuala Langsa Mangrove Forest located in Langsa City, Aceh Province, for ecotourism and disaster mitigation. This research was intended to analyze the aspects of forest management that has successfully reformed dry coast into an ecotourism site. The Analytic Hierarchy Process (AHP) as a multicriteria decision making method was used to analyze the best indicators data. This method was selected as the suitable method since it utilizes the objectivity of mathematics in comparing some subjective criteria to obtain the best indicators. The implementation of the AHP method consists of three stages: the development of the criteria’s hierarchy table; the development of pairwise matrix related to the intention of giving weights for the criterion’s elements; the logical concistency verification of the matrix. Indicators were written on a five point scale related to a value judgement. The results of the research show that as an ecotourism site, the activities of the mangrove forest are motivated and based on the existing rules which attract people to become interested. The role of the local government has resulted: developed the programs according to the existing mangrove management law that reached 67% among other law related indicators; budget allocation priority by self-generating which get priority of 59% among budget indicators; oriented on the increasing of fishermen, obtained 49% of economical function elements; encouraged the involvement and partnership of the local resources around the mangrove forest which reached 31% among other programs offered and sustainability approach by considering ecological functions aspect. For physical contribution for disaster mitigation, the largest dissipation is given by Rhizophora mucronata due to its height compared to the other types.