Analytic Hierarchy Process Algorithm Research Articles

Research on safety condition assessment methodology for single tower steel box girder suspension bridges over the sea based on improved AHP-fuzzy comprehensive evaluation

In order to propose a reliable method for assessing the safety condition for single-tower steel box girder Suspension bridges over the sea, a condition monitoring system is established by installing sensors on the bridge structure. The system is capable of gathering monitoring data that influence the safety status of the bridge. These include cable tension, load on the main tower and pylon, bearing displacement, wind direction, wind speed, and ambient temperature and humidity. Furthermore, an improved Analytic Hierarchy Process (AHP) algorithm is developed by integrating a hybrid triangular fuzzy number logic structure. This improvement, coupled with comprehensive fuzzy evaluation methods, improves the consistency, weight determination, and security evaluation capabilities of the AHP algorithm. Finally, taking the No.2 Channel Bridge as an example and based on the data collected by the health monitoring system, the application of the safety assessment method proposed in this paper provides favorable results in evaluating the overall safety status of the bridge in practical engineering applications. This provides a basis for management decisions by bridge maintenance departments. This project confirms that the research results can provide a reliable method for assessing the security status of relevant areas.

Distance-based integration method for human skin type identification

Although identifying human skin types is essential in dermatology, cosmetology, and facial recognition, the classification of human skin types is challenging due to the complex nature, varied characteristics, and the influence of external factors. Traditional methods for skin type identification often rely on subjective assessments, leading to inconsistent and inaccurate results. Therefore, this paper proposes a novel method named a distance-based integration method to identify skin types based on the Fitzpatrick skin scale, also known as the Fitzpatrick skin type. This study focuses on the objective distance measurement, integrated with the Fuzzy Analytic Hierarchy Process (AHP). The objective distance was utilized to determine the distance between each HEX color code for a clinical image and each target skin type. The Fuzzy AHP algorithm was employed to calculate the total score for each target class to identify human skin type. For this study, 1,022 images of human skin were used in the experiment. The results indicated that the proposed method achieved a high average accuracy of 93 %, precision of 80 %, and specificity of 96 %.

Maturity evaluation of real-name management for construction enterprise workers based on PMMM model and AHP algorithm

Since current real-name management for construction workers is unreasonable, this study has divided the management levels of construction companies into five categories, based on their IT applications. Apart from adopting literature induction approach and the project management maturity model (PMMM), the study also considers the six modules of human resource management. It has solicited expert opinions and evaluated them with different indicators and the improved Delphi method. Moreover, analytic hierarchy process (AHP) is employed to determine the algorithm of multiple indicators and the weights. This study has created a system to evaluate the maturity of real-name management of construction workers, offering reference fo enterprises’ personnel information management. It can also be used for industrial and social supervision to promote real-name management.

Selection of municipal solid waste disposal technology using the Analytic Hierarchy Process and Genetic Algorithm for Gulf Cooperation Council Countries

Municipal Solid Waste (MSW) management represents a significant challenge in rapidly urbanizing regions, notably within the Gulf Cooperation Council (GCC) countries. This study focuses on Kuwait, exemplifying the GCC context, to identify the most suitable MSW disposal methods. We integrate the Analytic Hierarchy Process (AHP) with Genetic Algorithms (GA) for a comprehensive evaluation and optimization of disposal options, considering 13 criteria across economic, environmental, technical, and safety dimensions. Five disposal methods (landfilling, controlled dumpsites, composting, incineration, and refuse-derived fuel [RDF] combustion) are analyzed for their fit to Kuwait's unique environmental and socio-economic conditions. The AHP analysis highlights the paramount importance of "Health & Safety of Employees" (19.8%), "Water Pollution" (16.2%), and "Air Pollution Control" (15.4%) as criteria, underscoring a regional prioritization of health and environmental considerations over cost. Composting and RDF combustion emerge as the preferred disposal methods, with AHP-derived priority percentages of 22.7% and 22.3%, respectively. GA optimization further validates these methods as optimally aligned with the regional waste management framework. Conclusively, composting and RDF combustion are identified as the most feasible MSW disposal options for Kuwait, with potential applicability across the GCC, contingent on alignment with local economic and environmental policies. This research provides a critical foundation for policymakers and stakeholders in crafting sustainable, region-specific waste management strategies.

Decision Support System for Achievement Scholarship Recipients at Vocational High Schools with the Analytical Hierarchy Process Method

In SMK Negeri 2 BIMA, there is a scholarship program, but the process of giving is still running manually and subjectively. The system used is still not computerized, so at the time of selection, the scholarship recipients are directly selected without specific criteria, which could be based on family relationships. So, there is a weakness in the current system running, one of which is less precisely the distribution of scholarships. This happened because it was influenced by the amount of data the incoming scholarship recipients entered. Therefore, a system that can jointly assist the school in decision-making based on these criteria is needed. The AHP algorithm is the basis of decision-making to determine the students who excel in the system to be built. Analytical Hierarchy Process (AHP) provides convenience with multiple criteria assessments with a framework of thinking that uses a hierarchical process which then calculates the weight for each criterion in determining the eligibility of students who will receive achievement scholarships. The results of this study are expected to help SMK 2 Bima decide which students are more entitled to receive outstanding scholarships. The output generated from this system is in the form of a ranking of prospective scholarship recipients.

A hybrid AHP-PROMETHEE II onshore wind farms multicriteria suitability analysis using kNN and SVM regression models in northeastern Greece

Wind energy presents a high growth potential in the EU as an emission reduction strategy and to achieve the climate neutrality goal by 2050. Wind farms suitability analysis is one of the primary goals in the spatial planning of wind energy developments. This research paper introduces a hybrid spatial multicriteria GIS-based framework that combines Analytic Hierarchy Process (AHP), PROMETHEE II and Machine Learning algorithms to determine and predict the most efficient onshore wind farm locations by generating suitability index mappings. The methodology allows to overcome PROMETHEE II limitations in raster driven suitability analysis, utilizing machine learning regression methods as the k Nearest Neighbor and Support Vector Machines to predict a graduating mapping of suitability index for wind farm locations in northeastern Greece. The best configured models presented a RMSE of 0.0344 and 0.0154 respectively, indicating a quite high predictive performance. Suitability results indicate that 56.10 % of the feasible locations in the Thrace area present a positive outranking character for the kNN model and 56.79 % for the SVR model. The proposed framework, enriched by PROMETHEE II capabilities, assists energy and spatial planners in identifying suitable sites for wind farm siting and enables rational decision making that enhances efficient wind energy investments.

Men's Perfume Recommendation System Using Analytic Hierarchy Process (AHP) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) Method

Perfume has been a product used for thousands of years by human civilization. Rapid growth of perfume products creates a problem especially for men to choose the best perfume to fit their personality. This research aims to help men find out which perfume suits each individual's personality by inputting a comparison of four main criteria, namely quality, price, aroma and durability. In this research, the research team built a perfume recommendation system specifically for men using the application of the Analytic Hierarchy Process (AHP) & Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) algorithm. The research resulted in an 89.17% usefulness score, 89.34% ease of use, 89.34% ease of learning, and 91.61% satisfaction, resulting in an overall score of 90.07%. The research results demonstrate that the AHP and TOPSIS algorithm can assist men in choosing appropriate perfume through its implementation in the system built by the research team, which was tested using a questionnaire

Optimize Ranking and Load Shedding in Microgrid Considering Improved Analytic Hierarchy Process Algorithm and Power Stability Index

This paper proposes a load shedding model for the island microgrid based on the ranking of loads and the power stability index (PSI). Loads are ranked based on the improved analytic hierarchy process (AHP) algorithm. Real-time measurement systems have the function of collecting data for very important, important, and less-important loads at each bus load. From this data, the improved AHP method is applied to rank the loads. The advantage of this method is that the subjectivity is eliminated and not depending on the expertise of the system operator when implementing the traditional AHP method. Besides, the minimum amount of load shedding power is calculated, taking into account both primary and secondary control methods. The objective is to minimize the impact on power consumers and ensure that the frequency returns to an acceptable range. In addition, when implementing load shedding, voltage quality, and stability are considered. The PSI serves as a crucial parameter for assessing the voltage stability of microgrid buses. This index is combined with load ranking weights to obtain combined weights for the load shedding plan. Consequently, the proposed load shedding plan prioritizes minimizing damage to customers, improving voltage quality and stability, and ensuring frequency is within permissible limits. The 16-bus microgrid system is applied to compare with traditional methods and to prove the efficiency of the suggested technique.

Application and Performance Evaluation of Industrial Internet Platform in Power Generation Equipment Industry

The development and application of the industrial Internet platform (IIP) has brought enterprises huge benefits, such as improving the efficiency of resource management and equipment maintenance, achieving the precipitation and reuse of industrial knowledge, and enhancing the development ability of industrial APPs, etc. Therefore, in order to accelerate the application of the IIP, promote the digital transformation of enterprises, and enhance the application effect of the IIP, it is necessary to evaluate the application level and performance of the enterprise IIP. In this paper, taking the IIP in the power generation equipment industry as the research object, the background, architecture, and implementation process of the platform is described, and an evaluation method is proposed. First, a third-level evaluation index system is proposed via reference analysis and the Delphi method from four dimensions—platform basic condition, platform technology capability, platform application service capability, and platform input–output capability—and a total of sixty-five bottom indexes are designed in particular. Then, the fuzzy analytic hierarchy process (FAHP) and particle swarm optimization (PSO) algorithm are used to determine the weights of indexes, where FAHP is used to construct a fuzzy judgment matrix and PSO is adopted to adjust the consistency of the fuzzy judgment matrix in the FAHP. Finally, through the weights of indexes and questionnaire scores, the evaluation results are obtained, and the application level and performance of the IIP in the power generation equipment industry is analyzed. Through analysis, the important indexes that have a significant influence on the evaluation are determined, and the weaknesses that need to be enhanced are also pointed out, which can guide enterprises to make targeted improvements on the IIP in the power generation equipment industry so as to ensure the sustainable development of the power generation equipment industry.

Ranking load in microgrid based on fuzzy analytic hierarchy process and technique for order of preference by similarity to ideal solution algorithm for load shedding problem

<span lang="EN-US">This paper proposes a method to rank the loads in the microgrid by means of a weight that combines the criteria together in terms of both technical and economic aspects. The fuzzy analytic hierarchy process technique for order of preference by similarity to ideal solution (fuzzy AHP TOPSIS) algorithm is used to calculate this combined weight. The criteria to be considered are load importance factor (LIF), voltage electrical distance (VED) and voltage sensitivity index (VSI). The fuzzy algorithm helps to fuzzy the judgment matrix of the analytic hierarchy process (AHP) method, making it easier to compare objects with each other and remove the uncertainty of the AHP method. The technique for order of preference by similarity to ideal solution (TOPSIS) algorithm is used to normalize the decision matrix, determine the positive and negative ideal solutions to calculate the index of proximity to the ideal solution, and finally rank all the alternatives. The combination of fuzzy AHP and TOPSIS algorithms is the optimal combination for decision making and ranking problems in a multi-criteria environment. The 19-bus microgrid system is applied to calculate and demonstrate the effectiveness of the proposed method.</span>

Analytical Hierarchy Process Algorithm for Traffic Sign Improvement Priority

Analytical Hierarchy Process Algorithm for Traffic Sign Improvement Priority

AHP algorithm used to select suitable abandoned underground mines for energy storage infrastructure – iCAES technology. A specific case study for León (Spain)

In the energy transition, the promotion of renewable sources entails the development of storage technologies to manage the mismatch between energy production and demand. In this scenario, the use of CAES (Compressed Air Energy Storage) technology enables the efficient and cost-effective storage of large amounts of energy. However, this technology is developed in salt domes who have an inherent risk associated of underground exploration phase. To address this, we propose to develop an infrastructure (iCAES) in abandoned underground mines, where the exploration phase is completed and well known. For its implementation, this paper defines a structure hierarchization method gathers the technical and socio-economic criteria. It involves a multi-criteria problem, and the correct selection of the location must be based on specific mathematical algorithms. For this case the Analytic Hierarchy Process (AHP) from multi-criteria decision making (MCDM) methods allows quantified by means of a scientific and mathematical scale and the assignment of weights, so that it is possible to evaluate different alternatives. This is possible thanks to the application of the AHP model in absolute terms. The information gathering has been based on the specific case study of coal basins in the north of Spain, in the region of León. Considering the proposed methodology, the most suitable alternative locations to implement iCAES in the region of León were identified.

Genetic algorithms-based optimal site selection of solar PV in the north of Afghanistan

ABSTRACT This study evaluates the renewable energy potential in northern Afghanistan by employing the Analytical Hierarchy Process (AHP) and a genetic optimization algorithm. Eleven geodata layers, including factors like solar radiation, elevation, and proximity to various infrastructures, were considered for assessing suitable solar energy development sites across nine provinces. The research combines AHP and genetic algorithm approaches to determine optimal locations for solar energy projects, aiming to aid policymakers and investors in decision-making. Morphological factors such as slope, elevation, and solar radiation were identified as significant determinants of site suitability for solar photovoltaic systems. The study revealed that Afghanistan's northwest and western regions have the most promising areas for solar PV systems due to their lower topographic complexity. The genetic algorithm accurately outperformed AHP, identifying over 29,000 square kilometers of suitable land for solar power plants in northern Afghanistan. The outputs of genetic algorithm are classified into strongly suitable (4504 km²), moderately suitable (5899 km²), and suitable (7088 km²) categories for solar energy development. Balkh province demonstrated the highest potential with an area of 7960 km², while Badakhshan showed the lowest capacity. These findings offer valuable insights for stakeholders interested in solar energy development in northern Afghanistan, aiding them in making well-informed decisions and investments.

Retracted: English Teaching Quality Evaluation Based on Analytic Hierarchy Process and Fuzzy Decision Tree Algorithm.

[This retracts the article DOI: 10.1155/2022/5398085.].

Location Selection of Electric Vehicles Charging Stations Based on Analytical Hierarchy Process and Clustering Algorithm

In recent years, the charging infrastructure for electric vehicles (EVs) in China has been developing quickly, yet the charging station industry still faces problems such as unreasonable layout, difficulty in profitability and limited coverage. Based on this, this paper systematically compared the key factors of charging facility location and used the AHP method to measure the degree of influence of various factors at different levels on the location of charging stations of enterprises, so as to establish a scientific and reasonable evaluation model for the location of charging stations. Secondly, we selected 12 typical enterprises such as TELD NEW ENERGY Co., Ltd.from the dimensions of company scale and strategic objectives, and then classified them into state-owned enterprises, vehicle enterprises and specialized operating enterprises through k-means clustering. Finally it turns out that various types of enterprises are in the stage of differentiation in the investment and construction speed of charging station enterprises. In addition, this study proposes personalized siting solutions for different types of charging piles, and makes referenceable suggestions for the siting of charging stations.
 
 
 atasets MNIST and CIFAR-10. After a few epochs, the model is convergent and reaches high accuracy of 99.34% in MNIST and 92.04% in CIFAR-10. This model outperforms the single CNN and some state-of-the-art models in classifying both datasets, especially in distinguishing similar images like ‘6’ and ‘9’, ‘bird’ and ‘plane’. These results indicate the model's good robustness and generality.

Analysis of the environmental resources value and enterprises economic benefits based on combination algorithm

Abstract To solve the problems of fuzziness, nonlinearity and complexity of economic factors and environmental factors in the evaluation of ecological economic benefits of enterprises are studied. Based on the theory of environmental-economic benefits (EEB), this paper defines the value of environmental resources and economic benefits of enterprises, and puts forward the indicators of environmental and economic benefits. The evaluation model of enterprise EEB based on the analytic hierarchy process and fuzzy set algorithm is constructed. By establishing the hierarchical structure model of index system, the intuitive fuzzy judgement matrix is obtained, and the final score of enterprise environmental benefits is calculated by consistency test and weight analysis. After verifying the model, the evaluation method of enterprise EEB proposed in this paper is accurate and reliable, which is helpful to deeply analyse the hidden order and adaptation mechanism of complex adaptation system of enterprise environmental management.

A Combined Fuzzy AHP and GA Approach to Machine Scheduling Problems from an Environmental Perspective

With increasing concerns about the need for environmental protection and reduction of energy consumption, enterprises have to demonstrate their capabilities in lowering resource consumption by enhancing the efficiency of their systems. Although some approaches to quantifying the environmental burden generated by a product or service system such as life cycle assessment (LCA) and carbon auditing have been developed, expert judgments are often required to implement them. From an industry’s perspective, small- and medium-sized enterprises need an efficient tool to determine the best solution when considering various attributes simultaneously. Thus, a combination of fuzzy analytical hierarchy process and genetic algorithm has been introduced to solve scheduling problems and support the decision-making process. This study aims to effectuate the green scheduling on optimized machine-task assignments with fuzzy evaluation. The proposed approach is illustrated using a case example from a centralized dishwashing company. Results show that the global warming potential value can be reduced by 1.86% and the cost of operation is slightly increased by only 1.28%. The result of the proposed approach is presented simply in the form of machine-task assignments with optimized environmental impact values and associated costs. Therefore, no further result interpretation by environmental experts is required. This study can be a reference for government policymakers in formulating policies to synthesize operation optimization and business sustainability.

The Utility of Decision Tree and Analytics Hierarchy Process in Prioritizing of Social Aid Distribution due to Covid-19 Pandemic in Indonesia

The Indonesian government provided various social assistance programs to local governments during Covid-19. One of the difficulties for the local governments in determining candidates for social aid is ensuring that the number of candidates is in balance with the available quota. Therefore, the local governments must select the most eligible candidates. This study proposes a priority model that can provide recommendations for candidates who meet the criteria for social assistance. The six parameters used in this study were: number of dependents, occupation, income, age, Covid status, and citizen status. The model operates in two stages, namely classification followed by ranking. The classification stage is conducted using a decision tree, while the ranking stage is performed conducted using the Analytical Hierarchy Process (AHP) algorithm. The decision tree separates two classes, namely, eligible and non-eligible. In addition, the classification process is also used to determine the dominant attributes and played a role in the modeling. The proposed model generates a list of the most eligible candidates based on our research. These are sorted by weight from greatest to most eligible using five dominant parameters: number of dependents, income, age, Covid status, and citizen status.

Sistem Pendukung Keputusan Rekomendasi Game Menggunakan Metode Analitycal Hierarchy Process (AHP) (Studi Kasus di Warung Internet Edelweiss)

Warnet Edelweiss (Edelweiss internet cafe) is a type of business that provides services and internet network connections, the main services provided to customers are internet browsing and games. Currently, the game is very liked by several groups ranging from adults, teenagers to children. The phenomenon of this game certainly has positive and negative impacts for its users, especially for children who currently dominate the game world. There needs to be a good and appropriate game selection based on age and gender through the application of a decision support system using the Analytical Hierarchy Process (AHP) method. The purpose of this study is to design and apply the AHP algorithm method to create a decision support system in the selection of game recommendations at the edelweiss internet cafe. The stages in this research start from data collection, analysis, design, implementation and system testing. The decision support system for selecting game recommendations at the edelweiss internet cafe has been successfully designed by utilizing the Object Oriented Programming (OOP) design method and the AHP method has been successfully applied. The results of testing with the black box method concluded that the system is running well and can be used.

A multi-criteria decision-making approach for portfolio selection by using an automatic spherical fuzzy AHP algorithm

Portfolio selection for Stock evaluation and selection by an investor is multi-criteria decision-making (MCDM) problem of finding the best portfolio among an efficient set of portfolios, which should be tackled by using the appropriate techniques. The Analytic Hierarchy Process (AHP) is amongst the most widely used MCDM methods, which is often used in operation management. The main feature of AHP is, that, it firstly reduces the complex decision problems in hierarchical structures of objectives, criteria, sub-criteria, and alternatives and then, uses a fundamental scale to construct pairwise comparisons. The Spherical Fuzzy Sets (SFS) have many advantages in handling the uncertainty and vagueness of ordinary and 2D Fuzzy Sets (FS)s. Therefore, taking the advantage of AHP and SFSs in this paper, we modify the Fuzzy Analytic Hierarchy Process (FAHP) into Spherical fuzzy AHP (SFAHP). We introduce the concept of Spherical Fuzzy Preference Relation (SFPR) and develop an automatic algorithm to construct a consistent SFPR from an inconsistent one. The validity of the proposed approach is tested through an illustrative application of portfolio selection on the Pakistan Stock Exchange to make a prototype of our results.