Classical Analytic Hierarchy Process Research Articles

Advanced digital competency assessment of vocational teachers': A new approach based on fuzzy-analytical hierarcy process

<p>Teachers need digital competence to adapt easily to the current digital era. This study tries to discover the perceptions of vocational high school (VHS) teachers in Indonesia related to advanced digital competencies, which include information, communication, content creation, digital security, and problem-solving competencies. The multi-criteria Analytical Hierarchy Process (AHP) problem-solving method is used to rank the priority digital competencies that are most mastered by the respondents, and then their performance is validated by the fuzzy AHP artificial intelligence-based method. A poll was conducted with 392 respondents, with the research instrument adopting the digital competency measurement platform from DigComp. The study's results show that the fuzzy AHP method has proven that the classical AHP method is a very good way to prioritize VHS teachers' digital skills based on several factors. The two methods gave almost identical results in determining the priority order of VHS teacher digital competencies. The survey results reveal that VHS teachers in Indonesia must immediately develop their skills in terms of digital content creation and digital security. Teachers, teacher professional organizations, and decision-makers are expected to use the findings of this study as a reference in implementing VHS teacher digital competency improvement trainings.</p>

How well may the direct linguistic declarations substitute AHP in defining accurate criteria weights?

AbstractThis paper investigates the problem of defining the weights in multiple criteria decision‐making analysis. In particular, we analyze if weights determined by decision makers (DMs) using the classic analytic hierarchy process (AHP) approach can be reproduced using more straightforward direct linguistic weights declarations (DLWD). Using the dataset from an online decision‐making experiment, we analyze the concordance of systems of weights obtained by DMs from AHP and DLWD. Applying optimization models, we check if the discrepancies between the AHP and DLWD weights result from (a) inefficiently declared mixes of linguistic labels in the symmetrically distributed scale or (b) using the unbalanced linguistic term set by DMs. The main findings are that the systems of weights obtained by DMs in the experiment from AHP and DLWD differ significantly. While using DLWD, most DMs defined criteria ranks contradictory to those resulting from AHP. They avoided extensive use of extreme labels from the 7‐point scale. The optimization results show that DLWD based on the symmetric scale might produce the most similar weights to AHP if a full range of linguistic terms was used, not only the intermediate ones. The differences in DMs’ cognitive profiles seem not to affect the results.

Coding Program Selection Using Spherical Fuzzy Analytic Hierarchy and Pythagorean Fuzzy Analytic Hierarchy Processes

Today, coding is not a field that belongs only to software developers; it has become a field of interest to many people from different professions. The coding education designed for elementary school level resulting from the changes made in the curriculum has led to teaching analytical thinking to children. Deciding the most suitable software for children among all the options is an important issue. This paper aims to extend the classical Analytical Hierarchy Process (AHP) and look at the spherical fuzzy analytical hierarchy (SF-AHP) method to show its applicability to the problems of coding software program selection for children through a comparative analysis using Pythagorean AHP (PF-AHP). After performing the analysis by using the proposed method, it was found that technological facilities, diversity, cost and environmental conditions were the most critical factors according to SF-AHP and PF-AHP methodologies. According to these criteria, the educational programming platform ‘Tynker’ was determined to be the best alternative using both these methods.

Sustainability factors influencing para rubber resources for the implementation of circular economy in Songkhla province, southern Thailand

ABSTRACT Circular economy (CE) has grown in popularity among policymakers as a novel approach to sustainable development, and a trending tool driving sustainable development in many countries around the world. Fundamentally, interactions between socioeconomic, socioecological, and technological factors determine sustainable development. Para rubber is a vital feedstock for bio-based industries. However, utilizing para rubber resources inefficiently can be a barrier to the desirable shift towards a CE system and sustainable development. In this present study, the sustainability factors enhancing the implementation of the CE potential of Para rubber resources in Songkhla province, southern Thailand, was evaluated. The classical Analytical Hierarchy Process (AHP) and Fuzzy Analytical Hierarchy Process (FAHP) were complementarily used to evaluate the main factors and sub-criteria for para rubber CE potential. The findings revealed the factors that will facilitate the implementation of para rubber CE and enhance sustainable development in the following order of priority: resource (0.420)> development (0.177)> environment (0.162)> economy (0.127)> population (0.114). Consequently, the para rubber resource has been identified as a bioeconomic gem in Thailand, with the potential to facilitate CE and enhance sustainable development in the study area. This study is useful to all stakeholders, including policymakers, in promoting para rubber resource efficiency, sustainable consumption and production trends at the national, provincial, and district levels, as well as improve the social, economic, ecological, and cultural resilience of rural areas. To drive Thailand’s CE transition, a comprehensive scientific assessment of Songkhla megatrends and prospects is recommended.

A Model to Determine the Number of Rescue Brigades in Underground Mines using the Risk Factor Approach

Mine rescue practices have seen significant improvement over the century. There have been developments in breathing apparatus, safe havens, rescue capsules, rescue simulators, underground communication technology, and training for rescue brigades. Most countries practice a mine-owned rescue system and the number of rescue brigades required in a mine is country-specific and determined by the mining regulations of the host country. A review of mining regulations globally shows that the number of brigades required in a mine depends solely on the number of people employed underground. For ages, this has been the only criterion used to determine the number of rescue brigades required in a mine. This criterion is not appropriate since there are other vital factors which must be taken into account. Considering the nature, complexity and innovations in mining operation currently, this paper considers eleven (11) factors that influence the number of rescue brigades in a mine. These eleven (11) factors were subjected to focus group discussions, the Classical Analytical Hierarchy Process, and the Fuzzy Analytical Hierarchy Process to establish seven (7) vital factors with weights more appropriate for determining the number of rescue brigades required in a mine. The results show that the number of rescue brigades required in a mine depends on: the safety culture of the mine; the number of people employed per shift; the resourcefulness of the rescue team; the number of active mines in the mine; the level of mechanisation of the mine, the mining depth; and the nearness and responsiveness of sister rescue teams. A novel model called the Yenzanya Model has been derived for determining the number of rescue brigades for underground mines as a contribution to science. This should be adopted by mine regulators to determine the number of brigades required for mining projects.

A novel methodology for micromobility system assessment using multi-criteria analysis

With cities around the world increasingly looking at micromobility as a means to achieve their goals for cleaner transportation and better air quality, local authorities, planners, and shared mobility operators are increasingly confronted with decision problems related to investment in micromobility systems. In order for decision making to be better informed, and objectives to be achieved, prioritizing investment according to the area needs and characteristics is highly important. In this context, the objectives of the present study are two: (1) propose a framework for the evaluation of neighborhood suitability for micromobility modes, (2) assist decision making with regards to the selection of the optimal micromobility system type for a study area. First, considering a range of both supply- and demand-based criteria, we construct an index calculated using a weighted multi-criteria approach with the purpose of identifying neighborhoods that are more conducive or less conducive to the integration of micromobility. Relative weights of the criteria and the respective indicators used for the calculation of the index are derived through the Analytic Hierarchy Process (AHP) method. The developed assessment framework is applied in three case studies of different scale: an urban district in the center of Paris, a university campus in the southern suburbs, and an eco-district currently under development in the southwestern suburbs of the city. Then, in the context of the second objective of this work, we propose a multi-criteria analysis framework for the selection of the optimal system type among seven alternative options for each study area. Considering multiple factors associated with the desirability of each of these modes in a neighborhood, we calculate priorities for each system type for the three selected case studies, using the classical AHP method.

Application of grey analytic hierarchy process to estimate mode choice alternatives: A case study from Budapest

This study proposes a multi-criteria decision-making approach using the grey theory to analyze mode choices. An extended analytic hierarchy process (AHP) model, which combines the advantages of the classic AHP and the grey theory for the accurate estimation of the commuting mode weight coefficients, is applied to a real transportation problem involving evaluators. The presented approach is applied for a real-life case study in Budapest. Based on the results, for all distances, public transport is ranked first followed by the car mode; however, for short- and mid-distance commuters, home office and bike might be suitable options, too. The results of this method are compared with the fuzzy AHP method. Having the same ranking in case of the two analyses means that the proposed method provides correct results under uncertainty in a group decision-making process. Thus, the outcomes highlight the applicability of the proposed method to the evaluation of mode choice.

Avalanche susceptibility mapping with the use of frequency ratio, fuzzy and classical analytical hierarchy process for Uzungol area, Turkey

As expressed in many studies in literature, the dynamic nature of snow avalanches is affected by the meteorological, environmental, topographical and human-related factors of the region. To better appreciate and forecast the snow avalanche, one of the hydro-geological disasters, becomes possible thanks to the approaches that take these parameters into consideration. They are commonly seen in mountainous areas, cause loss of life and property when they reach settlements, energy transmission lines, highways, ski resorts and other structures. Field studies, GIS, remote sensing, and various numerical avalanche modeling programs are used in determining avalanche-prone zones. There are various methods for producing avalanche susceptibility maps. In this study, susceptibility maps were created using the Frequency Ratio (Fr), Analytical Hierarchy Process (AHP), and Fuzzy-AHP (FAHP) methods for avalanche potential, in the tourism region of Uzungol, Trabzon located in northeastern Turkey. There has been no literature so far in the application of Fuzzy-AHP methods on avalanche susceptibility analysis, which has been used in other fields. This work will be the first case study on this subject. The results were compared according to existing land and inventory data; the success rates of the methods were found to be 89.12% for Fr, 71.15% for AHP and 73.24% for FAHP, and the effectiveness of the Fuzzy-AHP method was further tested. Comparing the results of the different methods, it has been found out that the Fr method is the most successful, while the AHP and FAHP methods provide approximate results.

An Integrated Multi Criteria Decision Making Model for Evaluating Park-and-Ride Facility Location Issue: A Case Study for Cuenca City in Ecuador

A park-and-ride (P&R) system is a set of facilities where private vehicle users can transfer to public transport to continue their journey. The main advantage of the system is decreasing the congestion in the central business district. This paper aims to analyze the most significant factors related to a Park-and-Ride facility location by adopting a combined model of Analytic Hierarchy Process (AHP) and Best Worst Method (BWM). The integrated model is applicable for complex problems, which can be structured as a hierarchy with at least one 5 × 5 pairwise comparison matrix (PCM) (or bigger). Applying AHP for at least 5 × 5 PCM may generate inconsistent matrices, which may cause a loss of reliable information. As a solution for this gap, we conducted BWM, which generates more consistent comparisons compared to the AHP approach. Moreover, the model requires fewer comparisons compared to the classic AHP approach. That is the main reason of adopting the AHP-BWM model to evaluate Park-and-Ride facility location factors for a designed two-level hierarchical structure. As a case study, a real-world complex decision-making process was selected to evaluate the Park-and-Ride facility location problem in Cuenca city, Ecuador. The result shows that the application of multi-criteria methods becomes a planning tool for experts when designing a P&R system.

Interval-Valued Intuitionistic Fuzzy-Analytic Hierarchy Process for evaluating the impact of security attributes in Fog based Internet of Things paradigm

Internet of Things (IoT) may be defined as a network of smart devices that are involved in data collection and exchange. This technology has automated the day-to-day jobs and thus made our lives easier. But, real-time analysis of data is not always possible in a typical cloud-IoT architecture, especially for latency-sensitive applications. This led to the introduction of fog computing. On one side, fog layer has the capability of data processing and computation at the network edge and thus provides faster results. But, on the other hand, it also brings the attack surface closer to the devices. This makes the sensitive data on the layer vulnerable to attacks. Thus, considering Fog-IoT security is of prime importance. The security of a system or platform depends upon multiple factors. The order of selection of these factors plays a vital role in efficient assessment of security. This makes the problem of assessment of Fog-IoT security a Multi-Criteria Decision-Making (MCDM) problem. Therefore, the authors have deployed an Interval-Valued Intuitionistic Fuzzy Set (IVIFS) based Analytical Hierarchy Process (AHP) for the said environment. Using this integrated approach, the Fog-IoT security factors and their sub-factors are prioritized and ranked. The results obtained using above hybrid approach are validated by comparing them with Fuzzy-AHP (F-AHP) and Classical- AHP (C-AHP) results and are found to statistically correlated. The ideology and results of this research will help the security practitioners in accessing the security of Fog-IoT environment effectively. Moreover, the outcome of this analysis will help in paving a path for researchers by shifting their focus towards the most prioritized factor thereby assuring security in the environment.

An Integrated Approach of Multi-Criteria Decision-Making and Grey Theory for Evaluating Urban Public Transportation Systems

Improving the local urban transport system’s quality is often seen as one of the critical points for the government and the local operator. An amelioration of the system can improve users’ satisfaction and attract new users while simultaneously decreasing traffic congestion and pollution. Efficient methodologies are required to achieve sustainable development regarding complex issues associated with traffic congestion and pollution. In this study, we propose using the analytic hierarchy process (AHP) grey values to overcome the limitations of the uncertainty in the classical AHP approach. The presented grey-AHP model assumes an efficient contrivance to facilitate the public transport system’s supply quality evaluation, especially when respondents are non-experts. Finally, we estimate and rank the public transport system’s supply quality criteria by adopting the proposed model for a real-world case study (Amman city, Jordan). The study’s outcome shows the effectiveness and the applicability of the developed approach for enhancing the quality of the public transport system.

Combination of D-AHP and Grey Theory for the Assessment of the Information Security Risks of Smart Grids

As a modern power infrastructure, smart grids have great advantages over traditional power grids, but their effective operation is largely restricted by information security. Hence, a smart grid information security risk assessment (ISRA) method is proposed. This method combines D numbers to improve the classical analytic hierarchy process (D-AHP) independent of experts’ subjective qualitative assessment and then integrated with grey theory which does not require complete and unambiguous information. First, we establish a smart grid ISRA system according to the characteristics and development reality of smart grid technology. The proposed system includes 5 first-level indexes as an intelligent terminal, a wireless communication channel, password security, application code and embedded system, and corresponding 13 secondary indexes. Second, a D-AHP method aimed at the uncertainty of human subjective judgment and fuzziness of language assessment is used to obtain the weight of each index. The D-AHP method is then combined with the grey assessment matrix solved by grey theory, to obtain the comprehensive assessment value and corresponding risk grade. With a smart grid demonstration project in Suzhou, China, as an example, an empirical study is carried out using expert scoring. The comprehensive assessment risk value is 3.8199, and the corresponding risk level is moderate. The results of this work could serve as a reference for the information security protection of smart grids.

Towards an objective decision-making framework for regional airport site selection

Airport site selection requires consideration of several criteria constrained by complicated trade-offs. Airport literature and practice provide valuable insights in terms of influencing factors and multicriteria assessment methods, at the pace that reported siting processes follow non uniform decision-making structures. Current developments in geoinformation unveil a valuable opportunity of development of a structured methodology in the field of airport siting. Brazilian public sector decision-makers recognize that such methodology has the potential to improve the allocation of federal budget for new regional airports, in terms of implementation time and political friction. This research proposes a methodology termed MESA - Metodologia de Escolha de Sítios Aeroportuários (in Portuguese, Airport Site Selection Methodology). The purpose of MESA is to be sound under technical grounds and at the same time provide a more objective decision-making process. The proposed methodology consists of 4 phases: i) literature review of airport site selection criteria; ii) criteria systematization; iii) setting up of eliminatory criteria and their thresholds; and iv) setting up of scoring criteria and of an approach for their quantification. Eliminatory criteria reduce the original screening area, while scoring criteria are used for ranking purposes. MESA combines GIS (Geographic Information System) and classic AHP (Analytic Hierarchy Process) with direct assessment of alternatives through specific techniques. So far, the methodology has been applied to two real cases in the Brazilian context. In addition to effectively reducing subjectivity in airport site location decision, MESA has been demonstrating to be a powerful tool for mitigating environmental and social impacts associated to airport site selection. MESA is designed in such a way that simplifies improvements and adaptations, making it widely applicable.

Fuzzy Analytic Hierarchy Process-Based Multi-Criteria Decision Making for Universities Ranking

High competition between universities has been increasing over the years, and stimulates higher education institutions to attain higher positions in the ranking list. Ranking is an important performance indicator of university status evaluation, and therefore plays an essential role in students’ university selection. The ranking of universities has been carried out using different techniques. Main goal of decision processes in real-life problems is to deal with the symmetry or asymmetry of different types of information. We consider that multi-criteria decision making (MCDM) is well applicable to symmetric information modelling. Analytic hierarchy process (AHP) is a well-known technique of MCDM discipline, and is based on pairwise comparisons of criteria/alternatives for alternatives’ evaluation. Unfortunately, the classical AHP method is unable to deal with imprecise, vague, and subjective information used for the decision making process in complex problems. So, introducing a more advanced tool for decision making under such circumstances is inevitable. In this paper, fuzzy analytic hierarchy process (FAHP) is applied for the comparison and ranking of performances of five UK universities, according to four criteria. The criteria used for the evaluation of universities’ performances are teaching, research, citations, and international outlook. It is proven that applying FAHP approach makes the system consistent, and by the calculation of coefficient of variation for all alternatives, it becomes possible to rank them in prioritized order.

New look at the inconsistency analysis in the pairwise-comparisons-based prioritization problems

The main goal of the multiple-criteria decision analysis is to create a ranking of available decision-alternatives, which is conventionally achieved by estimation of their priority weights. Among the most widely used prioritization methodologies is the Analytic Hierarchy Process (AHP). The prioritization methods that are used under the AHP scheme are based upon pairwise comparison matrix (PCM) that contains the decision-makers' evaluations of the priority-weights-ratios. In praxis, these evaluations are usually erroneous and as a result, the PCM is inconsistent. Because serious inconsistency makes the data contained in the PCM useless it is important to distinguish between useful and useless PCMs. In this paper, a novel principle for the assessment of the inconsistency-indices-usefulness is introduced. It is proposed to take into account their relationship with the correctness of the final ranking of the alternatives – a crucial and natural criterion for the performance of the indices. To find the best one in this regard, various inconsistency indices (both well-known and new) are compared via simulation experiments. Next, a new PCM-acceptance method is proposed. In this method, regression models that relate the probability of incorrect-ranking occurrence to the indices values, are used to assist the decision-making process. Those models enable decision-makers to accept or reject the PCMs, based on the assessment of incorrect-ranking risk. Thus, in contrast to the procedure still supported by the classical AHP, that new approach is based on sound statistical concepts and complies with the modern risk-analysis-based uncertain-decision-making.

Research on the Calculation Method of Regional Grid Construction Efficiency and Power Demand under the Background of High Power Grid Complexity

With the gradual development of power grid, the characteristics of power grid, such as regionalization, multi-dimensional and network complexity, have become more and more obvious. At the same time, the new round of power system reform has higher requirements for the development of power grid in all aspects. One of the key points of the reform is to achieve accurate investment in power grid, improve the efficiency of power grid construction and meet the demand of power grid construction. In this paper, the classic Analytic Hierarchy Process (AHP) is used, combined with the development situation of the power grid under the new requirements, the index system and model for the calculation of the construction efficiency and demand of the local and municipal power grid under the background of the highly complex development of the power grid are put forward. The model takes the time line of the power grid construction as the axis, through the pre-evaluation and post-evaluation of the power grid construction, the calculation of the construction situation of the regional power grid is completed. The efficiency and demand of power grid construction in different cities are analyzed. The example shows that the model can effectively identify the construction attributes of each region, reflect the construction requirements of the provincial power company system through different judgment matrix, and verify the final calculation results, optimize the construction and demand of the power grid system. The model effectively improves the operation efficiency of the power grid system, and realizes the ultimate goal of energy conservation and emission reduction.

Classical, fuzzy, hesitant fuzzy and intuitionistic fuzzy analytic hierarchy processes applied to industrial maintenance management

A multi-criteria problem involves the consideration of two or more criteria in the prioritization of alternative solutions. The Analytic Hierarchy Process (AHP) is a leading multi-criteria method. Consistency checking is a great advantage of AHP. Since in AHP priorities come from pairwise compariso ns, it is possible to check the consistency of these comparisons. However, a problem occurs when comparisons fail the consistency check. Then, the excluding options are to review some comparisons (Option 1) or to keep the comparisons (Option 2). This paper presents an AHP application in the maintenance management of an industrial plant. Industrial maintenance is not in the core business of an organization. However, maintenance costs can account over 50% of production costs. One of the first maintenance management decisions is on the maintenance strategy. Shall maintenance anticipate the occurrence of failure? Or shall maintenance be performed after an equipment breakdown? Answering those questions with classical AHP resulted in inconsistent comparison matrices. In that case, Fuzzy AHP (FAHP) were applied, avoiding this situation. Therefore, the purpose of this paper is to present the applications of four AHP models: Classical AHP and three models of FAHP, including hesitant fuzzy sets and intuitionistic fuzzy sets. The application of Hesitant FAHP (HFAHP) and Intuitionistic FAHP (IFAHP) are the novelty of this paper. The four AHP models were also applied in the same case of maintenance management of an industrial plant. Results were very similar, but experts could express their preferred model.

Extraction of Miao Embroidery Culture Factors Based on Perception Analysis

Through the way of creating model, this paper deeply explores and analyses the extraction of Miao embroidery cultural factors, endows traditional embroidery with new vitality, further enriches the cultural connotation of products, inherits the fine Miao embroidery culture and endows it with new vitality, promotes it to be further developed on the basis of adapting to the development environment of the new era, and better meets the diversification and individualization of various users. Firstly, this paper collects data from various channels, collects appropriate morphological samples according to relevant standards or requirements after integrating them scientifically and reasonably, chooses the method of semantic difference which is widely used at present, and compiles a five-point psychological scale which is reliable, reasonable, standardized and effective. At the same time, it discusses it comprehensively and deeply through the classical analytic hierarchy process. Various factors affecting the vocabulary of stylistic features and their importance are ranked to determine the most significant and prominent cultural factors. The main purpose of this paper is to combine the two different fields of culture and design rationally, so as to promote the further enrichment of product culture on the basis of inheriting and developing traditional culture.

Multi-Criteria Analysis of Design Solutions in Architecture and Engineering: Review of Applications and a Case Study

The primary goal of this paper is to present the application potential of MCDM/MCDA (multi-criteria decision-making/multi-criteria decision analysis) methods in the field of architecture and urban planning and in energy efficient construction, especially in the context of sustainable development paradigm. The first part of this paper is devoted to literature studies pertaining to multi-criteria decision-making support in the selected fields. On the basis of the delivered review, it was demonstrated that the most popular methods belonging to the MCDM/MCDA group that have been used so far for the purpose of resolving selected decision-making challenges, is the AHP (analytic hierarchy process) method with modifications, TOPSIS (technique for order of preference by similarity to ideal solution) method, as well the up-and-coming COPRAS (complex proportional assessment) method. In addition, by reviewing the literature, it was found that MCDM/MCDA methods constitute an effective support tool at the stage of evaluating and selecting project solutions, and are especially helpful in framing various social, economic, environmental criteria that are permanently linked to the rule of sustainable development. The empirical section of this paper, through a case study, presents a comparative analysis of the classical AHP method with its extension onto fuzzy sets. The case study pertained to the criteria for the location of single-family residential buildings with solar installations.

A Distance-based Method for Computing Priorities of Intuitionistic Fuzzy Preference Relation and Its Application in AHP

The notion of multi-criteria decision-making is regarded as the process of finding the best possible alternative or course of action by decision-makers. Often, it entails handling vague, incomplete and inconsistent information. The intuitionistic fuzzy set (IFS) has been proven more effective than a fuzzy set in handling vagueness and uncertainty. The aim of the article is to incorporate the effectiveness of the IFS with the powerfulness of the analytic hierarchy process (AHP) and develop intuitionistic fuzzy AHP (IF-AHP) to cope with the decision problems involving imprecise and hesitant information. In this article, we develop a distance-based novel priority method, which derives unambiguous non-fuzzy priorities of the alternatives from intuitionistic fuzzy preference relations (IFPRs). The proposed priority method is simple in computation yet effective in results. To validate the method, we applied it to the adapted supplier selection problem. This article also presents a comparison of the proposed method with classic and fuzzy AHP using Monte-Carlo simulation approach.