Rough Analytic Hierarchy Process Research Articles

Design concept evaluation based on cloud rough model and modified AHP-VIKOR: An application to lithography tool manufacturing process

Design concept evaluation is a wide domain of research as the production process of new product development is mainly based on the evaluations of experts. As different types of uncertainties like vagueness, randomness, and diversity essentially exist in the evaluation information, the manipulation models that deal with just one type of uncertainty are not appropriate for ranking the design alternatives. The integration of multiple approaches into a single mathematical model to create an effective framework is more useful for uncertain information manipulation. This paper presents an innovative group decision-making approach to evaluate design concepts by integrating cloud rough numbers, analytic hierarchy process (AHP) and VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method to introduce a novel cloud rough AHP-VIKOR model. The concept of cloud rough numbers is utilized by fusing the merits of the cloud model theory and rough approximations in addressing randomness in experts’ judgments and intrapersonal uncertainty for handling consensus inconsistency. Some new modified algebraic operations are introduced to remove the errors in already existing operations of cloud rough numbers. The cloud rough AHP technique is introduced to compute weights of design criteria by computing the cloud rough numbers of linguistic values and their reciprocals. Based on cloud rough values of positive and negative ideals, the individual regret, group utility values and evaluation indices are determined. Using the distance of evaluation indices from minimized cloud rough value, the design alternatives are ranked using different formulae. The significance of the proposed approach is illustrated with a real-world application in lithography tool manufacturing process. The out-performance and reliability of the proposed model is studied by a sensitivity analysis of different parameters in the method, and a comparison analysis with existing approaches.

Industry 4.0 project prioritization by using q-spherical fuzzy rough analytic hierarchy process

<abstract> <p>The Fourth Industrial Revolution, also known as Industry 4.0, is attracting a significant amount of attention because it has the potential to revolutionize a variety of industries by developing a production system that is fully automated and digitally integrated. The implementation of this transformation, however, calls for a significant investment of resources and may present difficulties in the process of adapting existing technology to new endeavors. Researchers have proposed integrating the Analytic Hierarchy Process (AHP) with extensions of fuzzy rough sets, such as the three-dimensional q-spherical fuzzy rough set (q-SFRS), which is effective in handling uncertainty and quantifying expert judgments, to prioritize projects related to Industry 4.0. This would allow the projects to be ranked in order of importance. In this article, a novel framework is presented that combines AHP with q-SFRS. To calculate aggregated values, the new framework uses a new formula called the q-spherical fuzzy rough arithmetic mean, when applied to a problem involving the selection of a project with five criteria for evaluation and four possible alternatives, the suggested framework produces results that are robust and competitive in comparison to those produced by other multi-criteria decision-making approaches.</p> </abstract>

Selecting the most suitable blockchain platform: A case study on the healthcare industry using a novel rough MCDM framework

Healthcare networks are sophisticated systems, which are commonly comprised of medical and drug suppliers, insurance companies, third-party logistics (3PL) providers, and regulators. Effective healthcare systems should be capable of sustainably delivering high quality and accessible patient care services using data shared through the best available technologies. However, healthcare data are generally hard to comprehend, use, and share since they are also inaccessible, non-standardized, and disseminated throughout the network. Blockchain may be employed to alleviate the impact of these challenges. However, only a few blockchain platforms (BP) have reached the stable design and established user base needed to give a healthcare organization (HO) confidence in their implementation. Each digital transformation project employing blockchain faces the challenge of picking a BP suitable to the requirements of a HO. While some research has been conducted to choose an appropriate BP, quantitative studies on specific industries, including healthcare, are currently insufficient. This investigation provides a case addressing the selection of the most feasible BP for a healthcare group. To this end, we propose a new multi-criteria decision-making (MCDM) framework that integrates the extent analysis-based rough Analytic Hierarchy Process (RAHP-E) and rough Compromise Programming (RCP). The findings of this study are validated through several analyses.

Formwork System Selection in Building Construction Projects Using an Integrated Rough AHP-EDAS Approach: A Case Study

The successful completion of reinforced concrete (RC) building construction projects depends, in part, on selecting the appropriate formwork system (FWS) since it may significantly affect the project’s cost, time, and quality performance factors. The selection of the FWS depends on a number of compromising and conflicting criteria, while several FWS alternatives may be available. Therefore, the FWS selection has mostly been treated as a multi-criteria-decision-making (MCDM) problem. Although various MCDM methods have been employed to address the FWS selection problem, none have considered the subjectivity and uncertainty arising from a group decision-making process. This study aims to fill this knowledge gap by proposing an integrated approach using recently developed MCDM methods with rough numbers. In the integrated approach, first, a decision-making team is formed to develop the decision hierarchy. Then, the rough analytic hierarchy process (R-AHP) is used to determine rough criteria weights, followed by the rough evaluation based on the distance from average solution (R-EDAS) method to rank the FWS alternatives. Finally, the results are compared using different rough MCDM methods to ensure the stability of the proposed approach. The proposed approach is applied to a real-life building construction project in Turkey to select the most appropriate FWS. The integrated approach was found to be effective, and it was recommended to be used for future FWS selection problems. The proposed integrated approach in this study may be used as a decision support tool for construction professionals and experts to select the FWS in building construction projects.

Evaluation Method of Highway Plant Slope Based on Rough Set Theory and Analytic Hierarchy Process: A Case Study in Taihang Mountain, Hebei, China

The material foundation of soil and water conservation is built on the integrity of the highway plant slope. The proportional relevance of the components that affect slope quality was evaluated based on an environmental assessment and the actual characteristics of the highway slope. A system of four major indexes and twelve secondary indexes comprising plant traits, geometric factors, hydrological conditions, and vegetation conditions was developed to assess the stability of roadway plant slopes. The rough set theory approach and the analytic hierarchy process were used to solve the weights of the slope evaluation indexes. Based on a rough set and an analytic hierarchy process, an evaluation model is proposed. The model eliminates the inconsistency and uncertainty in the evaluated factors that are used to calculate the slope. The study was conducted in China. The highway plant slope of the Taihang Mountain highway in the Hebei province was evaluated using the assessment model after dividing the highway plant slope stability into four grades. According to the evaluation results, the model can be used as a reference highway plant slope stability study and provide technical help to prevent and lower slope safety accidents. The evaluation model can predict the slope quality of highway plants, demonstrating the efficacy and reliability of the evaluation methodology and approach.

Power Quality Assessment Based on Rough AHP and Extension Analysis

Due to the increasing power consumption of whole society and widely using of new non-linear and asymmetric electrical equipment, power quality assessment problem in the new period has attracted more and more attention. The mathematical essence of comprehensive assessment of power quality is a multi-attribute optimal decision-making problem. In order to solve the key problem of determining the indicator weight in the process of power quality assessment, a rough analytic hierarchy process (AHP) is proposed to aggregate the judgment opinions of multiple experts and eliminate the subjective effects of single expert judgment. Based on the advantage of extension analysis for solving the incompatibility problem, extension analysis method is adopted to assess the power quality. The assessment grades of both total power quality and each assessment indicator are obtained by correlation function. Through a case of 110 kV bus of a converting station in a wind farm of China, the feasibility and effectiveness of the propose method are demonstrated. The result shows that the proposed method can determine the overall power quality of power grid, as well as compare the differences among the performance of assessment indicators and provide the basis for further improving of power quality.

Assessing urban resilience to public health disaster using the rough analytic hierarchy process method: A regional study in China

In the context of frequent occurrences of disasters worldwide, disaster-coping capability is imperative for risk reduction and contemporary emergency management. The global COVID-19 pandemic since 2020 has further highlighted the significance of resilience construction at different geographical scales. Overall, the conceptual cognition of resilience in disaster management covers multiple elements and has diverse yielding on regional assessment. This study assesses the local resilience to the public health disaster in the prefecture-level cities, focusing on two dimensions consisting of vulnerability and capability in the targeted provincial region of Jiangsu in China. To this end, based on the vulnerability-capability framework, the Rough Analytic Hierarchy Process (Rough AHP) method was applied to the resilience assessment. Drawing upon the criteria derived from literature, the criteria weights were determined with the RAHP method and we assessed urban resilience with census data. In addition, the hierarchical factors contributing to urban resilience were determined using robustness analysis. This research provides constructive ideas for regional disaster reduction and contributes to the government's capability to improve urban resilience.

WITHDRAWN: Assessing Urban Resilience to Public Health Disaster Using The Rough Analytic Hierarchy Process Method: A Regional Study in China

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An Integrated Approach for Failure Analysis of Natural Gas Transmission Pipeline

The main aim of this study is to identify the most important natural gas pipeline failure causes and interrelation analysis. In this research, the rough analytic hierarchy process (Rough-AHP) is used to identify the natural gas pipeline failure causes rank order. Then a combination of rough decision-making trial and evaluation laboratory (DEMATEL) and interpretive structural modeling (ISM) method is applied to generate the level of importance. The comparison of traditional DEMATEL and Rough-DEMATEL are also performed to establish the cause-effect interrelation diagram. Finally, the Bayesian Belief Network (BBN) is combined with Rough DEMATEL and ISM to identify the interrelation analysis among the most crucial failure causes. As a result, the energy supply company and government policymaker can take necessary safety plan and improve the operation. The main outcome of this study is to improve the security management and reduce the potential failure risks.

Modular design research of computer numerical control machine tools oriented to customer requirements

In order to study the modular design of computer numerical control machine tools oriented to customer demands, the customer demand information model was established based on rough analytic hierarchy process and information entropy by analyzing and transforming customer demands. Based on the domain mapping method of axiomatic design and quality function deployment integration, the product function model and structure model of computer numerical control machine tools are established. Based on fuzzy clustering analysis, the module division of computer numerical control machine tools is studied, and the dynamic clustering diagram of computer numerical control machine tools is formed with MATLAB as the operating environment. Based on Technique for Order Preference by Similarity to Ideal Solution method, the scheme of computer numerical control machine tools module division is evaluated. Taking the horizontal computer numerical control machine tool products of Shenyang Machine Tool Group as an example, the module division is carried out. The example design and the result analysis prove that the module division system is very effective and fast.

Integration of interval rough AHP and fuzzy logic for assessment of flood prone areas at the regional scale

This study was conducted to prepare a flood susceptibility map in northwest of Hamadan Province, Iran. For this purpose, six criteria related to flood (i.e., distance to discharge channel, slope (%), elevation, soil texture and land use, topographic wet index, and check dams) were chosen. Then, based on the role of these criteria on degree of flood susceptibility, were weighted both in the context of inter-weighting (fuzzy logic) and outer-criteria (Interval Rough Analytic Hierarchy Process). Finally, by combining these primary weights by weight overlay method in GIS, the flood susceptibility mapping was prepared in the study area. The resulted map based on K-means clustering and Silhouette function was divided into 9 clusters, whereas the lower clusters show low susceptibility to flood and vice versa. To assess the accuracy of the produced map, 102 flood observation points were overlaid on the clustered flood susceptibility map. The results showed that among these 102 flood points, 66 points are located in the clusters 8 and 9 and 3 points are located on cluster 7. These values show that the produced flood susceptibility mapping has a high accuracy.

Assessing social vulnerability to earthquake disaster using rough analytic hierarchy process method: A case study of Hanzhong City, China

This study assesses the local social vulnerability to earthquake disasters at a county (urban district) level, with a particular focus on Hanzhong City. A Rough Analytic Hierarchy Process based model was proposed for social vulnerability assessment. Based on criteria derived from the literature, the researchers determined the criteria weights using Rough Analytic Hierarchy Process method, and assessed social vulnerability for each county based on census data. furthermore, the most important factors contributing to social vulnerability were highlighted based on the results of sensitivity and robustness analysis. This research provides some implications for disaster mitigation and risk reduction strategies as well.

Status evaluation of mobile welding robot driven by fuel cell hybrid power system based on cloud model

The comprehensive evaluation of the performance parameters of the mobile welding robot driven by the fuel cell hybrid power system is beneficial to optimizing the energy efficiency and control performance of the system. However, few studies have paid attention to this aspect. Rough analytic hierarchy process and entropy weight method are used to calculate the weight of the evaluation index. Cloud model is used to synthesize all evaluation indicators to determine the status level. First, the golden section method is used to determine the evaluation criteria, and through cloud model, the evaluation criteria and measured parameters of the single evaluation index are transformed into corresponding evaluation reference clouds and evaluation clouds. Second, the weight of the evaluation index is determined by the method of the rough analytic hierarchy process, and the method of the entropy weight is used to revise the method of the rough analytic hierarchy process. The single evaluation reference cloud and evaluation cloud are aggregated to get the comprehensive evaluation reference cloud, and the comprehensive evaluation of the reference cloud is carried out. The evaluation cloud for each evaluation cycle. Finally, according to the correlation between the comprehensive evaluation cloud and the comprehensive evaluation standard cloud, the performance level of each evaluation cycle is determined. In this paper, the randomness and fuzziness of the qualitative concepts are solved by using the characteristics of the cloud model. Combined with rough analytic hierarchy process, the objectivity of the data is maintained and the advantages of the expert evaluation are enhanced. The validity of the model is verified by comparing the existing methods. These studies evaluate and classify the real-time status of the fuel cell robot, and provide a basis for the performance optimization and energy optimization of the hybrid power system controllers.

Multi Criteria Evaluation Framework for Prioritizing Indian Railway Stations Using Modified Rough AHP-Mabac Method

Abstract This study proposes a hybrid multiple criteria decision making (MCDM) methodology for evaluating the performance of the Indian railway stations (IRS). Since the customers are heterogeneous and their requirements are often imprecise, the evaluation process is a critical step for prioritizing the IRS. To improve the existing approaches, an efficient evaluation technique has been proposed by integrating rough numbers, analytic hierarchy process (AHP) and multi-attribute border approximation area comparison (MABAC) methods in rough environment. The relative criteria weights based on their preferences given by experts is determined by rough AHP whereas evaluation of the alternatives based on these criteria are done by the modified rough MABAC method. A case study of prioritizing different railway stations in India is provided to demonstrate the efficiency and applicability of the proposed method. Among different criteria “proactively” is observed to be the most important criteria in our analysis, followed by ‘Railfanning’ and ‘DMO’ is found to be the best among the forty IRS in this study. Finally, a comparative analysis and validity testing of the proposed method are elaborated and the methodology provides a standard to select IRS on the basis of different criteria.

Integration of interval rough AHP and interval rough MABAC methods for evaluating university web pages

Websites are one of the most widely distributed information resources. Educational institutions use this resource to ensure that the best quality of information transmission is achieved. As such, academic sites have become a very important aspect of academic institutions, one that affects their overall quality. Bearing in mind the importance of university websites’ quality, the authors of this paper presented a multi-criteria model for evaluating the quality of university websites. This paper presents the hybrid IR-AHP-MABAC (Interval Rough Analytic Hierarchy Process - MultiAttributive Border Approximation Area Comparison) model. The model is adapted to group decision making as based on the application of a new approach to treating uncertainties through the use of interval rough numbers (IRN). The modified IR-AHP method was used to determine the weight coefficients of the criteria in the group decision-making process. The results of the IR-AHP model are compared with results provided by the traditional AHP method and the fuzzy AHP approach. The IR-MABAC model was used for the evaluation of university websites. In order to verify the results of the IRN based approach, the IR-MABAC model was compared to the F-TOPSIS (Fuzzy Technique for Order of Preference by Similarity to Ideal Solution), F-VIKOR (Fuzzy MultiCriterion Optimization and Compromise Solution), F-COPRAS (Fuzzy COmpressed PRoportional ASsessment), F-MAIRCA (Fuzzy MultiAtributive Ideal-Real Comparative Analysis), and F-TODIM (an acronym of Interactive and Multi Criteria Decision Making in Portuguese) models. The credibility of the IR-AHP-MABAC model was demonstrated by comparing the results of different multi-criteria techniques and analyzing viability. The results of the IRN approach and fuzzy comparison have shown that the new approach to dealing with imprecision yields credible, reputable ranks.

Integrated Product and Process Development of Clutch Friction Material Using Quality Function Deployment Processes

Using an improved quality function deployment (QFD) process, an integrated product and process development method was proposed for the clutch friction material, one key part of driveline. The importance ratings of customer requirements for the clutch friction material was calculated and synthesized through the reasonable selection of respondents and the method to determine customer requirements based on importance of rough analytic hierarchy process (AHP) in QFD. Using improved QFD decomposition model, the quality house between customer requirements and part features, process matrix and the key process control sample table were established. The method can be widely used in the development of other key parts.

Evaluation and selection of medical tourism sites: A rough analytic hierarchy process based multi‐attributive border approximation area comparison approach

AbstractThis paper presents a novel Multiple Criteria Decision Making methodology for assessing and prioritizing medical tourism destinations under uncertainty. A systematic evaluation and assessment approach is proposed by incorporating analytic hierarchy process and multi‐attributive border approximation area comparison methods in the rough environment. Rough number is used to aggregate individual judgements of decision makers and express their true perception to handle vagueness without any prior information. Rough analytic hierarchy process analyses the relative importance of criteria based on their preferences given by experts, whereas rough multi‐attributive border approximation area comparison evaluates the alternative sites based on the criteria weights. A case study of prioritizing different sites (cities) in India for medical tourism services is shown to demonstrate the applicability of the proposed method. Among different criteria “quality of infrastructure of healthcare institutions” is observed to be the most important criteria in our analysis, followed by “supply of skilled human resources and new job creations” and “Chennai” is found to be the best medical tourism site in India. Finally, a comparative analysis and validity testing of the proposed method are elaborated, and the methodology provides a standard for select medical tourism sites on the basis of different criteria.

Application of GIS-Interval Rough AHP Methodology for Flood Hazard Mapping in Urban Areas

Floods are natural disasters with significant socio-economic consequences. Urban areas with uncontrolled urban development, rapid population growth, an unregulated municipal system and an unplanned change of land use belong to the highly sensitive areas where floods cause devastating economic and social losses. The aim of this paper is to present a reliable GIS multi-criteria methodology for hazard zones’ mapping of flood-prone areas in urban areas. The proposed methodology is based on the combined application of geographical information systems (GIS) and multi-criteria decision analysis (MCDA). The methodology considers six factors that are relevant to the hazard of flooding in urban areas: the height, slope, distance to the sewage network, the distance from the water surface, the water table and land use. The expert evaluation takes into account the nature and severity of observed criteria, and it is tested using three scenarios: the modalities of the analytic hierarchy process (AHP). The first of them uses a new approach to the exploitation of uncertainty in the application of the AHP technique, the interval rough numbers (IR’AHP). The second one uses the fuzzy technique for the exploitation of uncertainty with the AHP method (F’AHP), and the third scenario contemplates the use of the traditional (crisp) AHP method. The proposed methodology is demonstrated in Palilula Municipality, Belgrade, Serbia. In the last few decades, Palilula Municipality has been repeatedly devastated by extreme flood events. These floods severely affected the transportation networks and other infrastructure. Historical flood inundation data have been used in the validation process. The final urban flood hazard map proves a satisfactory agreement between the flood hazard zones and the spatial distribution of historical floods that happened in the last 58 years. The results indicate that the scenario in which the IR’AHP methodology is used provides the highest level of compatibility with historical data on floods. The produced map showed that the areas of very high flood hazard are located on the left Danube River bank. These areas are characterized by lowland morphology, gentle slope, sewage network, expansion of impermeable locations and intense urbanization. The proposed GIS-IR’AHP methodology and the results of this study provide a good basis for developing a system of flood hazard management in urban areas and can be successfully used for spatial city development policy.

Determining the Importance Ratings of Customer Requirements of Automotive Clutch Based on Quality Function Deployment

To obtain more comprehensive customer requirements and accurately determine the importance ratings of customer requirements in automotive clutch Quality Function Deployment (QFD), Affinity Diagram, expert evaluation method and rough Analytic Hierarchy Process (RAHP) were introduced in this paper. Firstly, fourteen requirements were identified for automotive clutch by using Affinity Diagram. Then rough numbers and rough boundary intervals were utilized to characterize vagueness and uncertainty of customer requirements, and constructed rough group decision matrices and rough pairwise comparison matrices. Finally, the importance ratings of customer requirements were determined by solving eigenvalues and eigenvectors of rough pairwise comparison matrices.

Research on Cigarettes Customer Needs Importance Algorithm Based on KJ / RAHP / KANO

To express the ambiguity and uncertainty of customer needs importance, an algorithm was proposed. It integrated KJ method, rough analytic Hierarchy Process and KANO model. It calculated the customer needs importance in rough set. A case study of cigarettes customer needs importance illustrated the feasibility and validity of the algorithm.