Analytic Hierarchy Process Method Research Articles

The application of grey statistical method and analytic hierarchy process in the evaluation of community park rehabilitation landscapes

The rehabilitation landscape of community parks plays a significant role in the physical and mental health of urban residents, social interaction, improvement of the ecological environment, and the sustainable development of cities. This research applies the Grey Statistical Technique (GST) combined with the Analytic Hierarchy Process (AHP) model to establish an evaluation system for landscape assessment. The system is constructed based on three dimensions: physical rehabilitation, psychological rehabilitation, and spiritual rehabilitation. The GST method is utilized to screen and select evaluation indicators, while the AHP method is employed to construct the landscape evaluation system and calculate the weights of each indicator. The results are as follows: (1) Out of the 30 indicator factors, 13 were not selected through the GST method. (2) The weights of the criteria layer, from highest to lowest, are as follows: physical rehabilitation (D1) with a weight of 0.6370, psychological rehabilitation (D2) with a weight of 0.2583, and spiritual rehabilitation (D3) with a weight of 0.1047. (3) The highest and lowest values in the indicator layer are as follows: D1 (P14: illumination duration 0.2359, P17: hydrological conditions 0.0197); D2 (P21: sense of security 0.1433, P23: human-environment interaction 0.0162); D3 (P34: sense of pleasure 0.0400, P36: aesthetic value 0.0045). This research reduces the subjectivity in the evaluation indicators and provides valuable guidance for the design of rehabilitation landscapes in community parks.

Risk Analysis of Hydrogen Leakage at Hydrogen Producing and Refuelling Integrated Station

Hydrogen energy is considered the most promising clean energy in the 21st century, so hydrogen refuelling stations (HRSs) are crucial facilities for storage and supply. HRSs might experience hydrogen leakage (HL) incidents during their operation. Hydrogen-producing and refuelling integrated stations (HPRISs) could make thermal risks even more prominent than those of HRSs. Considering HL as the target in the HPRIS, through the method of fault tree analysis (FTA) and analytic hierarchy process (AHP), the importance degree and probability importance were appraised to obtain indicators for the weight of accident level. In addition, the influence of HL from storage tanks under ambient wind conditions was analysed using the specific model. Based upon risk analysis of FTA, AHP, and ALOHA, preventive measures were obtained. Through an evaluation of importance degree and probability importance, it was concluded that misoperation, material ageing, inadequate maintenance, and improper design were four dominant factors contributing to accidents. Furthermore, four crucial factors contributing to accidents were identified by the analysis of the weight of the HL event with AHP: heat, misoperation, inadequate maintenance, and valve failure. Combining the causal analysis of FTA with the expert weights from AHP enables the identification of additional crucial factors in risk. The extent of the hazard increased with wind speed, and yet wind direction did not distinctly affect the extent of the risk. However, this did affect the direction in which the risk spreads. It is extremely vital to rationally plan upwind and downwind buildings or structures, equipment, and facilities. The available findings of the research could provide theoretical guidance for the applications and promotion of hydrogen energy in China, as well as for the proactive safety and feasible emergency management of HPRISs.

Exploring and Overcoming Challenges for Digital Transformation in the Energy Sector Toward Carbon Neutrality

ABSTRACTChina is committed to carbon neutral by 2060 to reduce its carbon footprint to zero. This research investigates the challenges surrounding the adoption of digitalisation in the energy sector and proposes policy plans to overcome them to achieve sustainability goals. This study utilised the fuzzy Analytical Hierarchy Process (AHP) method to assess the key challenges and sub‐challenges. Next, the fuzzy Technique for Order of Preference by Similarity to the Ideal Solution (TOPSIS) method is used to rank the policy plans to overcome the challenges for digital transformation in the energy sector toward carbon neutrality in China. The result of fuzzy AHP identified that financial constraints (DES1) is the most crucial challenge hindering digitalisation efforts with a weight of 0.172, followed by operational and management barriers (DES8) with a weight of 0.156, and regulatory and policy challenges (DES2) with a weight of 0.144. Next, the findings of fuzzy TOPSIS revealed that enhancing financial viability and investment (PP2) has obtained the first rank plan with a score of 0.065, following fostering regulatory support and policy development (PP3) with a score of 0.063 and building public trust and engagement (PP10) with a score of 0.060. These policy plans play a crucial role in addressing the challenges associated with adopting digitalisation in China's energy sector, toward a more efficient, sustainable and resilient energy transition.

Evaluation of Barriers to Digital Transformation in Maritime Logistics Based on A Spherical Fuzzy Multi-Criteria Decision-Making Framework

Purpose: The objective of this study is to identify and prioritize the barriers to the adoption of digital transformation in order to ensure more efficient and effective operation of the maritime logistics sector. Methodology: The Spherical Fuzzy Analytical Hierarchy Process (SF-AHP) method, which gives successful results in modelling uncertainty and uses Spherical fuzzy sets (SFSs), is used to rank the barriers affecting adoption of digital transformation according to their importance. Findings: In the application part of the study, firstly the barriers in the adoption of digital transformation were determined and as a result of expert evaluations, the barriers were ranked according to their importance by applying the steps of the method. When the results obtained from the study were examined, ‘Technology’ is the most important barrier category (B1) (0.341) for the adoption of digital transformation in maritime logistics, followed by the main barrier categories related to “Security” (B4) (0.266), “Environment” (B3) (0.223) and “Organisation” (B2) (0.171) respectively. Originality: This study represents a pioneering effort in the field of maritime logistics, as it is the first to identify and prioritize the barriers to digital transformation that impede operational efficiency.

Data Value-Added Service Comprehensive Evaluation Method on the Performance of Power System Big Data

With the development of digital economy, the integration and secure sharing of energy big data have become pivotal in driving innovation across the energy production, distribution, and consumption sectors. For power enterprises, leveraging data to enhance operational efficiency and drive business development will play a crucial role in value added. Firstly, based on the value-added service framework system of grid enterprises, this paper explores the basic technologies for power data applications and designs a technical roadmap for value-added services. Secondly, the proposed methodology incorporates the analytic hierarchy process (AHP) and gray comprehensive evaluation method (GCE) to determine the weights of key factors affecting the value-added services. Empirical research is conducted to validate the feasibility of typical value-added services. Additionally, this paper proposes methods for evaluating the benefits of value-added services and identifies key technologies in data mining and management, customer value discovery, and data asset utilization, providing theoretical support and practical pathways for the digital transformation of power enterprises.

Assessment of current and future land sensitivity to degradation under climate change in the upstream Ouergha watershed (Morocco) using GIS and AHP method

Land degradation is a worldwide phenomenon that negatively affects the topsoil of agricultural land. The Mediterranean region is the hardest hit by this phenomenon, which is set to increase due to climate change. This study aims to assess the susceptibility of land to degradation under climate change, based on the calculation of the Land Degradation Sensitivity Index (LDI) in the upstream Ouergha catchment in in Northern Morocco (Southern Mediterranean), using Geographic Information Systems (GIS) and the Analytic hierarchy process (AHP) multi-criteria decision analysis (MCDM) method. In this study, 4 main criteria (climate, vegetation, soil and human environment) divided into 15 sub-criteria were used to assess soil sensitivity to degradation. The weight of each criterion was assigned using the AHP method. The degree of soil degradation was classified on a map based on four categories (low, moderate, high and critical). About 14.9% of land is not very sensitive to degradation, while 37.2% of land is highly sensitive to degradation. Vegetation and climate were identified as the main drivers of land degradation (37% and 28% respectively). Climate scenarios for model EC-Earth3-Veg (CMIP6) indicate a significant drop in precipitation in this region, which accelerates soil degradation. The result represents a planning tool that can help decision-makers to take the necessary measures to ensure sustainable soil management in the face of climate change

Analytic hierarchy process geographic information system based model for sustainable construction and demolition waste landfill site selection

Properly managing waste generated by buildings and public works is a significant challenge in Tunisia, particularly in the city of Bizerte. The inadequate disposal of such waste can cause substantial harm to human life, property, and the environment. This paper proposes an multi-criteria decision making (MCDM) that utilizes the analytic hierarchy process (AHP) decision support tool to identify suitable landfill sites for construction and demolition waste (CDW) in Bizerte. The AHP method is widely used in MCDM applications. The approach involves classifying different scenarios based on various exclusion and appreciation criteria to determine the optimal locations for future landfills. Furthermore, the paper develops a conceptual approach for identifying better sites for the disposal of CDW, resulting in a comprehensive database capable of storing, accessing, and extracting information at both conceptual and operational levels. The proposed model considers spatial, technical, and environmental criteria in the selection of a suitable landfill site. The proposed methodology offers an effective and practical solution for properly managing CDW waste in Bizerte, Tunisia, and can be applied to other regions facing similar challenges.

Environmental risk assessment of concrete construction projects in developing countries based on Analytical Hierarchy Process method

Environmental risk assessment of concrete construction projects in developing countries based on Analytical Hierarchy Process method

Geo-environmental GIS modeling to predict flood hazard in heavy rainfall eastern Himalaya region: a precautionary measure towards disaster risk reduction.

The Eastern Himalaya region is highly susceptible to flood and other hydrological hazards due to frizzle geophysical setup, reshaping geomorphology, and heavy annual rainfall (1600-3200 mm). Despite that, anthropogenic activities have been enhancing this susceptibility which increases the intensity and impact of floods in terms of economic loss, human loss, and environmental degradation. Addressing this environmental problem, a geospatial technology-based case study of the Kohima district, Nagaland state (India), a part of the eastern Himalaya is presented here. Various experiential models are available for computing flood hazards; however, the geospatial technique-based analytic hierarchy process (AHP) method was applied in this study due to its robustness and high accuracy level. AHP integrates reclassified GIS layers of hazard-triggering factors and sub-factors by assigning relative weights 1-9 based on their corresponding impacts on flood occurrence. Overlay operation of reclassified GIS layer (causative factors and sub-factors) in ArcMap 10.8 software generated flood spatial variability map which shows four zones, namely low, moderate, high, and very high hazard zones, covers 23%, 35%, 28%, and 14% proportion of total area (978.96 km2), respectively. The study poses a serious concern for the study area as most of the densely populated urban centers fall into moderate to very high flood hazard zones including the state capital city Kohima. So, to avert a worse flood disaster, a flood hazard zone study is the need of the hour. The present study can be used as a decision support system (DSS) for flood disaster risk reduction, infrastructural development, and land use planning in Kohima district.

The Assessment of the Green Development of the Tobacco Industry Using a Multicriteria Method

The tobacco industry is heavily regulated due to the significant health implications associated with tobacco use. The industry also involves numerous stakeholders, including farmers, manufacturers, distributors, retailers, regulators, and consumers. The aim of this research is to select the most relevant environmental criteria for the green development of the tobacco industry. This article uses Analytical Hierarchy Process (AHP) methods to create a hierarchical structure of the criteria and subcriteria necessary for green business development, establishing the relative weights of these subcriteria to find the areas in which attention and resources are most urgently required. The assessment of the concordance of expert opinions shows a satisfactory level of agreement. The article advances a more comprehensive view towards the evaluation of green criteria that are significant for the whole industry, seeking to highlight the need to think holistically. According to the views of experts, the most significant sub-criteria for the green development of the tobacco industry are increasing energy efficiency; safeguarding against hazardous wastewater in the environment; reducing the content of hazardous materials used in products; improving air, land, and water quality where economic activity takes place; sustainable forest management; eco-design, especially for efficient material use, biodegradability, and recyclability; and collaboration with suppliers. The entire industry should collaborate in seeking global green development by gradually investing in the improvement of green criteria. Doi: 10.28991/ESJ-2025-09-01-018 Full Text: PDF

Decision Making in Bank Personnel Selection Using the Analytical Hierarchy Process

Banks, like in many other areas, must make the right decisions in personnel selection. Incorrect personnel choices can lead to customer loss and increase internal organizational problems. Therefore, it is crucial for banks to make the right personnel selections and use objective criteria when making these decisions. Selecting the most suitable employee who can contribute to increasing the value of the organization from numerous applications requires a multi-stage process. Recent studies have observed that multi-criteria decision-making methods are frequently used in evaluating recruitment processes. In this regard, the Analytical Hierarchy Process (AHP) method is a tool that can assist banks in making accurate personnel decisions. The aim of the study is to identify the criteria used in personnel selection in banks and prioritize these criteria. In the research, key factors in the recruitment process include personal characteristics, organizational expectations, and experience as the main criteria. Using the AHP method, priority rankings of these factors have been made, and the most important criteria have been identified. The results highlight that determining the right criteria is crucial for enhancing the quality of the workforce and designing efficient recruitment processes in the banking sector. Furthermore, the AHP model provides a concrete tool for recruitment processes in the sector, helping decision-makers to make more informed and objective decisions.

Analytical Hierarchy Process Method in the Decision Support System for Non-Cash Food Assistance Recipients

Analytical Hierarchy Process Method in the Decision Support System for Non-Cash Food Assistance Recipients

Comparison of the Distance Learning Modalities Regarding Teaching Capacities and Performances on the Learners

ABSTRACTEspecially after the COVID‐19 pandemic, people have distances among each other, and this situation has affected everything. Education, which has been the most important thing for humanity since the beginning of history, has also been affected. To continue and survive the system, people started using and adapting different distance learning with the help of electronic devices, internet and technology. However, the impact of these new distance learning modalities does not have the same teaching capacity and performance on the learners. Besides, evaluation of the learners, fairness, interaction, feedback, etc. are the other important problems of the new distance learning modalities. Nevertheless, to discover the effect of the distance learning modalities regarding teaching capacities and performances on the learners, they are compared in this study with an integrated fuzzy multi criteria decision making model. The proposed model consists of two parts; fuzzy analytic hierarchy process and ELECTRE methods. In the first part, weights and the decision matrix are calculated by using a fuzzy analytic hierarchy process. Then, in the second part, distance learning modalities are evaluated with the application of the ELECTRE method through the decision matrix according to weights.

Selection of Low-Carbon Contractors in a Fuzzy Multi-Objective Environment

The selection of contractors entails multiple uncertainties, including the lack of clear delineation of contractor qualifications, ambiguity surrounding project manager capabilities, and the uncertain nature of carbon emissions. These uncertainties compound the complexity involved in genuinely evaluating and choosing contractors. This paper establishes a fuzzy multi-objective contractor selection model that accounts for cost reduction, optimization of contractor qualifications, organizational management enhancement, carbon emissions reduction, and reputation optimization. Leveraging the Fuzzy Analytic Hierarchy Process (F-AHP) and Fuzzy Compromise Programming (F-CP) methods, we have devised a fuzzy multi-objective contractor selection model and outlined the procedural steps for its implementation. A case study was conducted to validate the effectiveness of the model we proposed.By applying this model to the case, we successfully transformed the complex multi-objective programming into a straightforward single-objective linear programming. Furthermore, based on the model, the weights assigned to cost, qualification indicators, management level, carbon emissions, and contractor reputation are 0.54, 0.09, 0.05, 0.19, and 0.13, respectively. By solving the model, we were able to identify the most suitable contractor.This paper aids the decision-making process in selecting an appropriate low-carbon contractor.

Solar Energy Application in Malaysia’s Manufacturing Industry: Analysis of the Challenges and Success Factors

This study analyzes challenges and success factors in the use of solar energy in Malaysia’s manufacturing sector. A hierarchical tree based on the Analytical Hierarchy Process (AHP) method was modeled to identify the sub-criteria of challenge aspects and success factors. A questionnaire study based on the sub-criteria was conducted on 30 respondents among supervisors and above from various companies involved in the electrical, electronic, and mechanical manufacturing industries that employ machines intensively in the Klang Valley area, Malaysia. Data for the study were collected from survey respondents’ evaluations. The collected data was analyzed using the AHP method. Findings show that there is a significant positive relationship between the challenges and success factors of implementing solar energy in the manufacturing industry in Malaysia. As a result of the study, government initiatives are the key challenges and success factors for the industry involved in utilizing solar energy. The development of a framework for solving the challenge of using solar energy in the industry has been proposed. As a result, the framework can provide added value to government and funding agencies involved in improving Malaysia’s solar energy policy. This contribution will assist them with drafting, developing, and improving existing policies and plans, thereby, leading to more solar energy usage in Malaysia’s manufacturing industry.

Simple and objective determination of criteria weights for evaluating alternatives when using the Analytic Hierarchy Process

In both design and project management, it is usually necessary to make decisions based on criteria that, in many cases, are not completely objective. One of the most widely used methods to assist in multi-criteria decision making is the Analytic Hierarchy Process (AHP). The construction of the pairwise comparison matrix is the most critical element of the AHP method. Its construction usually requires a group of experts to make value judgments among the criteria for evaluating alternatives. This article presents a simple and objective method to construct the AHP pairwise comparison matrix, thereby reducing the degree of subjectivity. This contribution focuses on the step of assigning the scale values (1-9) to build the criteria matrix. The only step that requires human intervention is the ranking of the criteria. The rest of the steps can be programmed, e.g., in a spreadsheet, and performed automatically. Two options are presented to relate the criteria based on their positions in the ranking: option A by means of the ratios of the order of the criteria, and option B by means of the differences in the order of the criteria. The applicability of both options is evaluated using hypothetical cases compared to the rank-order centroid weight method, and an example taken from the literature. Both options of the method give good results, but option B seems to be more appropriate for problems with more than five criteria. Option A would be the most appropriate for problems with three to five criteria.

Three-Dimensional Printed Auxetic Insole Orthotics for Flat Foot Patients with Quality Function Development/Theory of Inventive Problem Solving/Analytical Hierarchy Process Methods

Foot disorders affect approximately 10% of adults, with plantar heel pain significantly impacting foot-related quality of life and altering walking patterns. Flat feet, characterized by a lack of longitudinal arches, can lead to fatigue during walking. This study aims to develop 3D-printed shoe insoles tailored to the needs of patients. The design process incorporates Quality Function Deployment (QFD), Theory of Inventive Problem Solving (TRIZ), and Analytic Hierarchy Process (AHP) methods to create insoles that alleviate concentrated loads while meeting patient requirements. The AHP analysis indicated that patients prioritize insoles that effectively manage pressure distribution to achieve optimal functionality. QFD and TRIZ facilitated the identification of four product alternatives and production specifications. The analysis indicated that 3D-printed insoles made from TPU filament with 20% auxetic infill best align with patient preferences. This auxetic TPU option emerged as the top choice, achieving a priority value of 0.2506 due to its superior functionality and comfort. Load distribution measurements confirmed that TPU with auxetic infill resulted in the lowest load distribution, with a standard deviation of 0.1434 and a 25.4% reduction in maximum load compared to conditions without the insole.

Slum Structuring Strategy With Collective Housing Concept

Telaga Tujuh Village, located in West Langsa Sub-district, Langsa City, on the eastern tip of Aceh, has a very high population density. In addition, 373 housing units in the village do not meet the technical criteria set out in the Minister of Public Works and Housing Regulation No.02/PRT/M/2016, and the city has limited access to critical infrastructure. Based on seven criteria, including building regularity, neighborhood road network, neighborhood drainage, drinking water needs, wastewater management system, waste management facilities and infrastructure, and fire protection facilities, Telaga Tujuh Village is classified as a severe slum, with an average slum rate of 100%. Discovering the structural needs of the slum environment in Telaga Tujuh Village and creating a structural design is the objective of this study. Five indicators - on-site upgrading, on-site relocation, on-site redevelopment, land sharing, and relocation - were used in the communal housing methodology in this study. On-site redevelopment was chosen as the minimum solution after the five indicators were selected using the Analytical Hierarchy Process (AHP) method. After on-site redevelopment, the settlement pattern in this area is in the form of an iron grid, with main centers-the construction of places of worship, village halls, auxiliary health centers (pustu), and village offices that function as government and community service centers-and supporting centers-education and neighborhoods-by providing public open spaces.

Pemetaan Potensi Geografis Pengembangan Peternakan Ayam Ras Petelur di Kecamatan Lintau Buo Kabupaten Tanah Datar

This study aims to map the geographical potential for the development of layer chicken farming in Lintau Buo District, Tanah Datar Regency. The method used is the weighted overlay method, which works by overlaying multiple maps representing various parameters of an area's conditions. Each parameter is assigned a weight based on its importance using the Analytic Hierarchy Process (AHP) method. The alternative data used in this study consists of four nagari in Lintau Buo District: Nagari Pangian, Nagari Tigo Jangko, Nagari Buo, and Nagari Taluak. The research results indicate that Lintau Buo District has varying potential for poultry farming development. Nagari Pangian has a high-potential area of 391 hectares and a medium-potential area of 2,317 hectares. Nagari Tigo Jangko dominates the high-potential classification with an area of 3,514 hectares, while the medium-potential area covers 857 hectares, making it an ideal region for large-scale poultry farming. Meanwhile, Nagari Buo falls entirely within the medium-potential category, covering 906 hectares. Nagari Taluak has a high-potential area of 417 hectares and a medium-potential area of 3,125 hectares. These findings suggest that the development of layer chicken farming in Lintau Buo District should integrate geographical factors and regional carrying capacity to ensure sustainability and productivity.

Assessment of a Groundwater Potential Zone Using Geospatial Artificial Intelligence (Geo-AI), Remote Sensing (RS), and GIS Tools in Majerda Transboundary Basin (North Africa)

Groundwater in northwest Tunisia plays a vital role in supporting the domestic, agriculture, industry, and tourism sectors. However, climate change and over-exploitation have led to significant degradation in groundwater quality and quantity. Traditional spatial analysis techniques such as Geographic Information Systems (GIS) and Remote Sensing (RS) are frequently used for assessing groundwater potential and water quality. Yet, these methods are limited by data availability. The integration of Geospatial Artificial Intelligence (Geo-AI) offers improved precision in groundwater potential zone (GWPZ) delineation. This study compares the effectiveness of the Analytical Hierarchy Process (AHP) and advanced Geo-AI techniques using deep learning to map GWPZ in the Majerda transboundary basin, shared between Tunisia and Algeria. By incorporating thematic layers such as rainfall, slope, drainage density, land use/land cover (LU/LC), lithology, and soil, a comprehensive analysis was conducted to assess groundwater recharge potential. The results revealed that both methods effectively delineated GWPZ; however, the Geo-AI approach demonstrated superior accuracy with a classification accuracy rate of approximately 92%, compared to 85% for the AHP method. This indicates that Geo-AI not only enhances the quality of groundwater potential assessments but also offers a reliable alternative to traditional methods. The findings underscore the importance of adopting innovative technologies in groundwater exploration efforts in this critical region, ultimately contributing to more effective and sustainable water resource management strategies.