Triangular Fuzzy Analytic Hierarchy Process Research Articles

Sustainability-oriented monorail transit construction comprehensive evaluation

ABSTRACT Monorail transit is a relatively small form of urban rail transit, having a considerable influence on city infrastructure; however, its quality evaluation needs to be further developed. This study aims to comprehensively evaluate the construction quality of monorail traffic, considering the newly completed Wuhu Monorail Transit Line 1 as an example. First, a comprehensive evaluation system comprising 5 dimensions, namely sustainability, social, economic, city development and technology, and 23 sub-indexes is constructed. Second, for scientific evaluation, the triangular fuzzy analytic hierarchy process is considered to determine the subjective weight of each index; then, the Critic method is used to determine the objective weight of each index. Finally, the game theory equilibrium weight method is used to determine the total weight of each index. Furthermore, considering randomness and fuzziness, the cloud model is used to evaluate the construction quality of the Wuhu monorail Line 1. The evaluation results show that the Wuhu Monorail Transit Line 1 has a high construction grade, with sustainability dimension A1, sub-index of greenhouse gas emission quality B11, and total energy consumption B12 during the construction period. The proposed evaluation method was verified using sensitivity analysis and has a strong practical value.

Exploring sustainable watershed flood risks management: An innovative TFAHP-TOPSIS methodology in the Georges River Basin, Australia

Floods occur frequently in low-lying coastal and riverine areas, making it crucial to effectively identify the distribution of flood risks in flood-prone areas. Traditional risk assessment models based on Multiple-Criteria Decision-Making (MCDM) method have limitations in both accuracy and effectiveness, particularly in identifying potential risks in watershed floodplains. To refine the flood measurement process, an optimized integrated MCDM model is proposed in this paper. Taking the Georges River Basin in Australia is chosen as an example, twelve risk indicators were identified, considering factors related to hazard, exposure, and vulnerability. To more accurately describe the characteristics of watershed floods, the flood hazard indicators were separated into sub-basins. The Triangular Fuzzy Analytic Hierarchy Process (TFAHP) is employed to optimize the weight calculation, and in combination with the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), the spatial distribution of flood risks was determined. The results indicate that high-risk areas are concentrated in the central-eastern part of Liverpool, the eastern part of Fairfield, and the central part of Bankstown-Canterbury. Medium to very-high potential risk areas identified by the integrated TFAHP-TOPSIS model are 17.3 % more than the single TFAHP method and 12.7 % more than the TOPSIS method, indicating that the integrated model performs better in identifying potential risks in floodplains. The results can provide decision support for disaster prevention strategies making in flood-prone areas.

Two-stage site selection of hydrogen refueling stations coupled with gas stations considering cooperative effects based on the CRITIC-ITFAHP-MABAC method: A case study in Beijing

Powering hydrogen-fueled vehicles (HFVs) through hydrogen electrolysis using excess sustainable energy is an effective way to move towards sustainable development. Hydrogen refueling stations (HRSs) coupled with gas stations (GSs) can effectively integrate and utilize the resources in existing GSs, improve operational efficiency, and promote the cooperative income of the two. Aiming at the lack of cooperative effects between gas and hydrogen considered in the current site selection process for HRSs, a general criterion establishment process with refined measurement system are proposed to determine a more comprehensive criterion system, including the cooperative criteria and the precise calculation formula of each criterion. Based on these, a new two-stage site selection framework for HRSs is established. The first stage offers eligible alternatives through veto criteria. Then in the second stage, the Criteria Importance Through Intercriteria Correlation (CRITIC) and Improved Triangular Fuzzy Analytic Hierarchy Process (ITFAHP) methods are used to determine the objective weights and subjective weights of the criteria, and the results are combined according to the minimum deviation estimation (MDE). The rankings of alternatives are finally determined through the Multi-Attributive Border Approximation Area Comparison (MABAC) method. Three scenarios are proposed for further analysis in the case study of Beijing, China. The results show that the two-stage site selection framework with new criterion system makes the evaluation results more differentiated. When the importance coefficient of subjective weights reflecting the importance of the criterion in practice changes from 0 to 1, the score increase of the best alternative A5 (Zhoujiaxiangbei) is 49.14% higher than that of the second-ranked alternative, indicating that this alternative is more in line with people's perception of a good selection. The analysis results also further verify the rationality and robustness of the decision-making framework.

Research on a TOPSIS energy efficiency evaluation system for crude oil gathering and transportation systems based on a GA-BP neural network

As the main link of ground engineering, crude oil gathering and transportation systems require huge energy consumption and complex structures. It is necessary to establish an energy efficiency evaluation system for crude oil gathering and transportation systems and identify the energy efficiency gaps. In this paper, the energy efficiency evaluation system of the crude oil gathering and transportation system in an oilfield in western China is established. Combined with the big data analysis method, the GA-BP neural network is used to establish the energy efficiency index prediction model for crude oil gathering and transportation systems. The comprehensive energy consumption, gas consumption, power consumption, energy utilization rate, heat utilization rate, and power utilization rate of crude oil gathering and transportation systems are predicted. Considering the efficiency and unit consumption index of the crude oil gathering and transportation system, the energy efficiency evaluation system of the crude oil gathering and transportation system is established based on a game theory combined weighting method and TOPSIS evaluation method, and the subjective weight is determined by the triangular fuzzy analytic hierarchy process. The entropy weight method determines the objective weight, and the combined weight of game theory combines subjectivity with objectivity to comprehensively evaluate the comprehensive energy efficiency of crude oil gathering and transportation systems and their subsystems. Finally, the weak links in energy utilization are identified, and energy conservation and consumption reduction are improved. The above research provides technical support for the green, efficient and intelligent development of crude oil gathering and transportation systems.

Identifying Critical Stations Affecting Vulnerability of a Metro Network Considering Passenger Flow and Cascading Failure: Case of Xi’an Metro in China

Analyzing the importance grade of each metro station is the premise and foundation to ensure the safe and efficient operation of the metro network. This paper explores the identification method of critical stations in the metro network on the basis of considering the influence of passenger flow. Eight indicators were selected from both the static and dynamic aspects to construct the critical station identification index system considering the impact of passenger flow and cascading failure. Then, the triangular fuzzy analytic hierarchy process (TFAHP) method and critical importance through intercriteria correlation (CRITIC) method were used to calculate subjective and objective weight of all indicators, and the combined weighting method based on game theory was applied to calculate the comprehensive weight. The improved technique for order of preference by similarity to ideal solution (TOPSIS) method was developed to calculate the station importance and rank all stations according to their importance. Finally, the Xi’an metro network by mid-2021 was taken as the case study. The results show that there are 21 critical stations in the Xi’an metro network in three time periods (i.e., morning rush hours, evening rush hours, and nonrush hours) on weekdays and weekends, respectively, and those critical stations are divided into three levels. High centrality, high passenger flow intensity, and strong destructive ability are three important characteristics of critical stations in the metro network, and different critical stations have different importance characteristics. The Xi’an metro operation management authority needs to conduct a classification management scheme for those critical stations. The conclusions can provide the basis for the metro operation management authority to formulate accurate station management scheme, so as to increase the robustness of the metro network.

Research on adaptive combined wind speed prediction for each season based on improved gray relational analysis.

The stability of the power grid and the operational security of the power system depend on the precise prediction of wind speed. In consideration of the nonlinear and non-stationary characteristics of wind speed in different seasons, this paper employs the weight of wind resource index calculated by triangular fuzzy analytic hierarchy process (TF-AHP), criteria importance through inter-criteria correlation (CRITIC), and entropy weight method (EWM) to improve gray correlation analysis (GRA) and obtain the gray correlation degree of each season. In addition, a wind speed prediction model is provided that includes single-layer and two-layer weighting and is based on both deep and shallow machine learning models. At first, we establish each quarter's wind resource characteristics at typical monthly intervals of 10min, 30min, 60min, and 120min. The GRA's TF-AHP-CRITIC-EWM, enhanced with subjective and objective weights, is used to assess the available wind resources in each season and to compute the forecasted combination of wind speed for each season. As the final prediction results, the prediction values of each layer model are evaluated independently. For the intervals with considerable errors, we apply wavelet denoising and replacement combination. The simulation findings show that the proposed combined model surpasses earlier benchmark models in terms of goodness of fit, prediction accuracy, and generalizability.

Advanced FMECA Method Based on Intuitionistic 2-Tuple Linguistic Variables and the Triangular Fuzzy Analytic Hierarchy Process

Failure mode effects and criticality analysis (FMECA) is a commonly adopted approach to defining, assessing, and reducing possible failures in designs, systems, processes, products, and services. Traditional FMECA ranks the failure modes of products based on a risk priority number (RPN), which is obtained by multiplying the risk elements. Conventional FMECA has the shortcomings of badly handling unknown information and unreasonably assessing RPNs. To deal with these issues, an advanced FMECA method based on intuitionistic 2-tuple linguistic variables (I2LVs) and the triangular fuzzy analytic hierarchy process (TFAHP) is proposed. In this method, the fuzzy evaluation of risk elements given by different FMECA members is represented by I2LVs, which can efficiently handle unknown information. The TFAHP method is adopted to assess the weights of risky elements and rank the risk priorities of different failure modes. Finally, an application case of an insulated-gate bipolar transistor is used to verify the effectiveness and robustness of the proposed method.

A Novel Evaluation Method for the Stability of Construction Sites on an Abandoned Goaf: A Case Study

In recent years, more and more expressways have passed through abandoned goafs. However, the surfaces above the goafs have been experiencing long-term residual deformation, which may bring risks for the construction of expressways. In order to avoid risks, it is very necessary to evaluate the operation safety of the expressway above the goaf. Thus, the precise evaluation of site stability is the key. Based on the variable weight theory and regret theory, the stability evaluation model of the construction site above the goaf was established, which had 12 evaluation indexes. The constant weight of each evaluation index was determined by the triangular fuzzy analytic hierarchy process, and modified according to the variable weight theory. Then, the attribute value matrix was established based on regret theory to evaluate the stability level of the construction site. In order to reduce the influence of subjective factors, validity coefficient and correlation coefficient were used to analyze the validity and reliability of the matrix. The built model was used for Mianluan Expressway. The results showed that the irregular goaf was unstable for the expressway construction site, and the working faces of 18101, 18041 and 21201 were basically stable. Then, the evaluation results were proved by the high-precision leveling results in the field, and the countermeasures of different stability levels were given. The model can accurately evaluate the stability of the construction site above the goaf, and provide a theoretical basis for later management and monitoring to ensure the operation safety of the expressway.

Site selection for hybrid offshore wind and wave power plants using a four-stage framework: A case study in Hainan, China

The site selection for hybrid offshore wind and wave power plants (HOWWPP) is a critical step to a successful HOWWPP project. In this study, a four-stage framework is presented for determining the most suitable marine areas for the siting of HOWWPP. First, wind and wave energy potentials are assessed as a foundation for the implementation of a HOWWPP project. Next, unsuitable areas for the siting of HOWWPP are determined based on exclusion criteria to avoid any potential conflicts of marine spatial planning. Feasible areas (not satisfying the exclusion criteria) are classified and converted into spatial layers separately according to evaluation criteria. Then, the triangular fuzzy analytic hierarchy process is applied to calculate the evaluation criteria weights. Finally, the site suitability of feasible areas is calculated using the weighted overlay approach and then categorized into five classes. To validate the effectiveness of the proposed framework, a case study in Hainan Province of China was conducted. The results indicate that the marine areas with medium to very high suitability are approximately 1312 km2 (4.7% of the study area) for the deployment of HOWWPP. The obtained results of this study can support potential planners in selecting marine areas for the installation of HOWWPP.

Eigenproblem driven triangular fuzzy analytic hierarchy process

The eigenproblem plays a crucial role on checking acceptability of decision-makers’ pairwise comparison results and deriving priorities from preference relation matrices in the analytic hierarchy process (AHP). This paper analyzes two recent fuzzy eigenvector methods and illustrates their deficiencies. Two frameworks of additively normalized triangular fuzzy priorities (ANTFPs) are introduced to characterize a cluster of equivalent fuzzy priority vectors. Based on the approximation relationship between triangular fuzzy multiplicative preference relation matrices and their most appropriate ANTFPs, three eigenproblems with positive real matrices are established and an eigenvector based linear program is developed to obtain support interval based ANTFPs from fuzzy multiplicative preference relation matrices. The largest eigenvalue weighting consistency index and consistency ratio are defined and an acceptability checking method is then proposed by both examining acceptable consistency of fuzzy multiplicative preference relation matrices and acceptable vagueness of eigenvector based ANTFPs. Afterwards, an eigenproblem driven triangular fuzzy AHP is devised in detail. A numerical illustration including four fuzzy multiplicative preference relation matrices is provided and a comparative study is carried out to demonstrate the superiority and effectiveness of the presented models. Meanwhile, a multi-criteria graduate job selection problem is used to show the application of the proposed triangular fuzzy AHP.

Quality Assessment Method for Mobility as a Service

The ongoing development of the concept ‘Mobility as a Service (MaaS)’ along with Shared Mobility contributes to the integration of transportation systems. Several MaaS or similar services are already in operation. The perceived quality of MaaS by the users varies significantly, and no general method is proposed to evaluate the service quality. This scantiness is identified as the research gap. The objective of the research is to elaborate a quantitative method to assess MaaS services. The research question is how to assess the quality of MaaS, and how to transform the qualitative description into quantitative numerical values, namely, the quality index and the level of quality. Since user expectations towards the importance of criteria are taken into consideration, the modified triangular fuzzy analytic hierarchy process method is introduced to calculate the weights of criteria. A quantitative method to calculate the quality index and to assign the quality level has been elaborated. Ten MaaS services are assessed with the method. It was found that the journey comfort is regarded with significant importance among the respondents. Furthermore, the quality index of MaaS services is not high; accordingly, the service quality requires continuous improvement. Our method facilitates decision-making when planning MaaS to identify the expected service attributes.

Development of an Assessment Method for Evaluation of Sustainable Factories

The role of the industrial sector in total greenhouse gas (GHG) emissions and resource consumption is well-known, and many industrial activities may have a negative environmental impact. The solution to decreasing the negative effects cannot be effective without the consideration of sustainable development. There are several methods for sustainability evaluation, such as tools based on products, processes, or plants besides supply chain or life cycle analysis, and there are different rating systems suggesting 80, 140, or more indicators for assessment. The critical point is the limits such as required techniques and budget in using all indicators for all factories in the beginning. Moreover, the weight of each indicator might change based on the selected alternative that it is not a fixed value and could change in a new case study. In this regard, to determine the impact and weight of different indicators in sustainable factories, a multi-layer Triangular Fuzzy Analytic Hierarchy Process (TFAHP) approach was developed, and the application of the method was described and verified. The defined layers are six; for each layer, the pairwise comparison matrix was developed, and the total aggregated score concerning the sustainability goal for each alternative was calculated that shows the Relative Importance Coefficient (RIC). The method is formulated in a way that allows adding the new indicators in all layers as the verification shows, and thus, there are no limits for using any green rating systems. Therefore, the presented approach by TFAHP would provide an additional tool toward the sustainable development of factories.

An axiomatic property based triangular fuzzy extension of Saaty’s consistency

The fuzzy analytic hierarchy process (FAHP) is a widely applied fuzzy multi-criteria decision making method. In triangular FAHP, consistency of triangular fuzzy multiplicative preference relations (TFMPRs) plays a very important role for checking the quality of human fuzzy judgments. This paper introduces some indices to measure fuzziness of triangular fuzzy judgments and row fuzziness proportionalities in a TFMPR. An expected interval based possibility degree formula is developed to compare two triangular fuzzy judgments and used to judge whether the average-based intensity of a triangular fuzzy judgment is changed. The paper proposes four axiomatic properties aimed at characterizing multiplicative consistency of TFMPRs, and illustrates that four known consistency definitions fail to meet all the four axiomatic properties. By analyzing the axiomatic property of restriction on ambiguity of single judgments, a constrained triangular fuzzy multiplication based transitivity equation is devised and used to construct a triangular fuzzy matrix from a TFMPR. Based on the constructed fuzzy matrix, the paper establishes an ordinary triangular fuzzy multiplication based transitivity equation to define consistency of TFMPRs. Important properties of consistent TFMPRs are offered to demonstrate that all the four axiomatic properties are satisfied by the proposed consistency definition. Three numerical examples are given to illustrate the use of the proposed consistency model and the obtained properties for judging consistency of TFMPRs and determining unknown values of incomplete TFMPRs.

Summary of the Port Shoreline Resource Evaluation Based on Triangular Fuzzy Analytic Hierarchy Process

Abstract Port shoreline resources are the basis of port and shipping development, and its assessment method has become one of the hot issues in port research. On the basis of constructing a reasonable index evaluation system, this paper constructs the fuzzy evaluation matrix based on the triangular fuzzy analytic hierarchy process and constructs the fuzzy evaluation matrix by using the fuzzy comprehensive evaluation method, and obtains the maximum membership degree of the port shoreline resources. Compared with the traditional port shoreline Resource evaluation methods, the new one got more advantages in objective and quantitative. Finally, Combined with the Nanjing section of the Yangtze River as a case for verification, the results show that the model can accurately solve the problem of resource evaluation of port shoreline.

Approaches to group decision making with incomplete information based on power geometric operators and triangular fuzzy AHP

In this paper, we investigate the multiple criteria group decision making (MCGDM) problems in which decision makers (DMs)’ preferences on alternatives (criteria) are depicted by triangular fuzzy numbers and take the form of incomplete reciprocal comparison matrices. We aim to develop integrated methodologies for the MCGDM problems. First of all, we develop a triangular fuzzy power geometric (TFPG) operator and a triangular fuzzy weighted power geometric (TFWPG) operator for aggregating the DMs’ preferences into the group preferences. Furthermore, we construct a consistent recovery method and a δ-consistent recovery method for estimating the missing preferences. Next, we propose two integrated approaches to the aforementioned MCGDM problems by utilizing triangular fuzzy analytic hierarchy process (TFAHP) to combine the TFPG (TFWPG) operator, the recovery methods and extent analysis method (EAM) effectively. Finally, an illustrative example of small hydropower (SHP) investment projects selection is given to show our approaches.

Application of a triangular fuzzy AHP approach for flood risk evaluation and response measures analysis

Flood risk evaluation and prediction represents an essential analytic step to coherently link flood control and disaster mitigation. The paper established a hybrid evaluation model based on fuzzy analytic hierarchy process (AHP) and triangular fuzzy number. It comprises flood risk evaluation and prediction to obtain risk factors ranking and comprehensive flood risk prediction, and then analyzed flood risk response measures. A case study is proposed entailing a flood risk evaluation and prediction in the Lower Yangtze River region. The evaluation results showed that the proposed evaluation and prediction model was capable of adequately representing the actual setting. In addition, a comparison with the previously described AHP and trapezoidal fuzzy AHP, and experimental results are encouraging, which fully demonstrates the effectiveness and superiority of the proposed model.