Group Fuzzy Analytic Hierarchy Process Research Articles

Assessing Aging Status and Type of XLPE Cable Insulation With a Graphic Approach Based on PDC Measurement

The polarization and depolarization current (PDC) measurement has been widely used to assess the aging degree of cross-linked polyethylene (XLPE) cables. However, the aging type identification of XLPE cables has not been fully considered. In this study we conduct PDC measurement on thermal-aged and water tree-aged XLPE cable samples respectively, upon which a graphical approach to assess the insulation condition and distinguish the aging type of XLPE cables is proposed. First, to designate the evaluation indexes of the insulation condition, multiple PDC measurement based dielectric parameters are considered. Then, to reflect the sensitivity of each evaluation index to the condition of XLPE cable, a combined weighting method based on the group fuzzy analytic hierarchy process (GFAHP) and entropy method (EM) is introduced. Furthermore, the improved radar chart method (RCM) based graphical approach is proposed to comprehensively and intuitively characterize the evaluation indexes. Finally, the aging degree of the XLPE cable samples is quantitatively assessed by calculating the area of the polygon in the chart. Simultaneously, utilizing the position of the areal coordinate and the shape characteristic parameter of the polygon, the thermal-aged and water tree-aged samples are effectively distinguished.

Research on Performance Management Evaluation of Public Sports Venues Based on GFAHP

The importance of public stadiums has become increasingly prominent, but the efficiency of its performance management operation mechanism is low, which affects the overall operation efficiency of the whole stadium. However, due to the diversity and incompleteness of its data types, the traditional analytic hierarchy process is difficult to construct its index system. This article introduces the grey fuzzy analytic hierarchy process. Based on the analysis of its performance management problems, this article constructs the index system and makes an application case analysis. The results show that the GFAHP method (group fuzzy analytic hierarchy process) can ensure the integrity of information data. In data classification, the highest accuracy of sample classification is 40.13%, and the relative error rate is basically less than 6%. The performance effect is much higher than other classification algorithms. At the same time, the total score of the evaluation index system constructed by GFAHP is more than 3, the overall operation is good, and the risk evaluation effect of each influencing index factor is also good. Using the grey analytic hierarchy process to evaluate the operation and performance management of public stadiums and gymnasiums will help managers do a good job in risk control and quality dynamic adjustment, so as to improve the operation efficiency and benefit of stadiums and gymnasiums.

Evaluation of Comprehensive Ability of Accounting Applied Talents Based on GFAHP-Cloud Model

Through the objective and fair evaluation of the comprehensive ability of accounting talents cultivated in colleges and universities, on the one hand, it is beneficial to provide direction for cultivating accounting applied talents in colleges and universities, and on the other hand, it can also provide reference for enterprises to select talents. Firstly, this study constructs an evaluation index system for the comprehensive ability of accounting applied talents and selects 15 indicators from three aspects of knowledge level, ability level, and moral level. Secondly, the group fuzzy analytic hierarchy process is used to determine the index weight. Finally, a fuzzy comprehensive evaluation model based on the cloud model is constructed and tested in practice. This study hopes to make an objective and fair evaluation for accounting talents by quantitatively evaluating the comprehensive ability of accounting applied talents.

In defense of group fuzzy AHP: A comparison of group fuzzy AHP and group AHP with confidence intervals

Group aggregation of the Analytic Hierarchy Process (AHP), both with crisp and fuzzy numbers, is a widely researched field in group multiple criteria decision-making. Typically, if uncertainty needs to be reflected in the outcome of an AHP, triangular fuzzy numbers are used, although this is a controversial method, as many argue that the traditional 1–9 scale used in crisp AHP introduces uncertainty to the decision-making process, leaving no need for fuzzification. This research introduces the use of confidence intervals around the aggregated group mean to estimate the score ranges generated through group fuzzy AHP (GFAHP), as confidence intervals are simpler to calculate and more familiar to many. A comparison of the score ranges resulting from GFAHP and group aggregation using crisp numbers with confidence intervals around the group mean score, aggregating on individual priorities using both the arithmetic mean and geometric mean, was completed. The concept of using confidence intervals on crisp scores to generate score ranges was implemented through a case study to select a new all-wheel drive crossover vehicle. This study shows that confidence intervals introduce excessive uncertainty to the decision-making problem.

Evaluating the comprehensive benefit of hybrid energy system for ecological civilization construction in China

There are obvious ecological benefits of a hybrid energy system (HES) with its advantages of energy resources cascade utilization and multi-energy supply. With the increasing attention to ecological civilization (EC) construction in China, the HES has attracted more and more attention. Constructing HES projects that meet the requirements of EC is meaningful to government policy implementation and corporate social responsibility performance. There are a lot of studies on the benefit evaluation of HES, but all of them lack pertinence to EC construction, and the research results are insufficient to promote EC construction. Therefore, this paper evaluates the comprehensive benefits of HES in close combination with EC construction. Firstly, the connotations of EC and HES and their relationship are analyzed, and the evaluation criteria system of HES based on EC is established. Secondly, the group fuzzy analytic hierarchy process (GFAHP) is introduced to calculate the criteria weights and find out the important indicators. Thirdly, an improved model combining fuzzy synthetic evaluation (FSE) and the cloud model is introduced for the calculation of the EC comprehensive benefits of HES. Finally, the feasibility of the GFAHP–Cloud–FSE model in this paper is verified through a case study. The focuses of general HES projects and the case study are confirmed. This work provides suggestions for the government to evaluate and supervise HES projects for better EC construction, and it is helpful for enterprises to meet the government requirements for EC and fulfill social responsibilities.

A New Method for Deriving Weights in Group Fuzzy Analytic Hierarchy Process and Evaluation Measures

Abstract The paper discusses fuzzy comparison matrices, consistency check, weight prioritization methods and weight evaluation methods in fuzzy group analytic hierarchy process. There are various methods of weight prioritization, however, they are not critically evaluated. In the paper, two measures are introduced for the evaluation of the group weights. Then, a new method is proposed to improve the process of deriving weights and use it in an application compared to another common three methods. Our results show that the new method is a good method for deriving weights of indexes.

The key risk indicators of road traffic crashes in Serbia, Niš region

ABSTRACTTraffic crashes are a serious public health and socio-economic problem, and they are one of leading causes of death of males in Serbia. In order to determine the main causes of road traffic crashes in Niš region, Republic of Serbia, nine key risk indicators of road traffic crashes are identified, organized into four groups (number and structure of crashes, consequences of traffic crashes, temporal and spatial location of traffic crashes, causes and sanctions), and described in detail. The indicators are ranked based on group fuzzy analytic hierarchy process (AHP), where experts from insurance companies, professionally engaged in the process of risk assessment, with different previous experience present different impact on the final ranking. In relation to the most influential factors in the assessment of traffic crashes, improper and unadjusted vehicle speed, overtaking and passing, as well as the physical condition of the driver have the highest effect.

Evaluation of several approaches for deriving weights in fuzzy group analytic hierarchy process

The paper discusses fuzzy group analytic hierarchy process. In the literature, there are found several approaches for determining weights either directly from the individual judgments or via group comparison matrix. However, the quality of the group weights was not studied yet. In the paper, we propose two new measures for the evaluation of the group weights that are adapted from classical analytic hierarchy process. We selected six approaches for deriving weights and use them in an application from the literature. We evaluated the gained weights. Our results show that the weights derived by the most popular extent analysis method are questionable in their reliability.

Selection of key indicators for the improvement of occupational safety system in electricity distribution companies

The paper presents occupational safety indicators, as well as the method for the selection and ranking of indicators on the basis of expert assessment and group fuzzy analytic hierarchy process. The case study was done on the basis of research at the “EPS Distribution” company in Serbia. The key indicators in electricity distribution companies are obtained and ranked based on the outcomes of three studies that included experts who evaluated the risks in this company. The case study identified technical and human factors as dominant for the improvement of safety in the distribution company in Serbia. The indicators describing activities are identified as the most important for the effective improvement of functioning of the occupational safety system.

Partner selection and performance evaluation framework for a construction-related virtual enterprise: a multi-agent systems approach

ABSTRACTTo exploit market opportunities, disparate enterprises can pool their core competencies to form a temporary organisation. This inter-organisational collaboration of enterprises is commonly referred to as a virtual enterprise (VE). However, the VEs’ partner selection problems influence their overall performance. Due to the limited construction-specific studies on the evaluation and selection of partners, the current research sought to address this knowledge gap by investigating the partner selection problem. The partners comprising 10 construction companies carrying out project tasks for a large building in Nairobi, Kenya, were evaluated. Data were collected using a sequential mixed-methods approach consisting of a focus group interview, questionnaires and algorithms. The study proposed the use of the partner selection and performance evaluation technique. This technique combines fuzzy approximate reasoning with the conventional analytic hierarchy process algorithm, designed to deal with imprecise evaluators’ judgments. A multi-agent systems approach was chosen to simulate VEs. Results show that the chosen techniques are both efficient and effective. In particular, the reduced group fuzzy analytic hierarchy process reduces the number of pairwise comparisons required when comparing a large number of attributes. Application to the construction management domain, in particular, is germane to the research.

Soft consensus model for the group fuzzy AHP decision making

The fuzzy analytic hierarchy process (AHP) is an extension to the classical AHP that enables dealing with the impreciseness and vagueness of judgments. It has been frequently used for handling complex decision making problems that demand a group rather than a single decision maker. Group decision making aggregates the judgments of individuals into a joint decision. Although consensus is the desired result in group decision making, it is difficult to achieve due to the diversity of opinions, knowledge and experiences of the decision makers. Therefore, the concept of soft consensus can be applied. We propose a new soft consensus based model for fuzzy AHP group decision making. The judgments in the model are presented as triangular fuzzy numbers. The closeness between judgments of two decision makers is measured by the individual fuzzy consensus index which in turn is based on the compatibility index from classical AHP. In each iteration, two decision makers with the most dissimilar opinions are identified and their judgments are adapted. The process is repeated until the desired consensus level is reached. The model can also take into account the weights of importance of individual decision makers. A fuzzy extension of the geometric mean method is employed for deriving fuzzy weights from a group fuzzy pairwise comparison matrix. The application of the model is provided in an example from the literature.

Personnel selection using group fuzzy AHP and SAW methods

Personnel evaluation and selection is a very important activity for the enterprises. Different job needs different ability and the requirement of criteria which can measure ability is different. It needs a suitable and flexible method to evaluate the performance of each candidate according to different requirements of different jobs in relation to each criterion. Analytic Hierarchy Process (AHP) is one of Multi Criteria decision making methods derived from paired comparisons. Simple Additive Weighting (SAW) is most frequently used multi attribute decision technique. The method is based on the weighted average. It successfully models the ambiguity and imprecision associated with the pair wise comparison process and reduces the personal biasness. This study tries to analyze the Analytic Hierarchy Process in order to make the recruitment process more reasonable, based on the fuzzy multiple criteria decision making model to achieve the goal of personnel selection. Finally, an example is implemented to demonstrate the practicability of the proposed method.

THE ANALYSIS OF HUMAN ERROR AS CAUSES IN THE MAINTENANCE OF MACHINES: A CASE STUDY IN MINING COMPANIES

This paper describes the two-step method used to analyse the factors and aspects influencing human error during the maintenance of mining machines. The first step is the cause-effect analysis, supported by brainstorming, where five factors and 21 aspects are identified. During the second step, the group fuzzy analytic hierarchy process is used to rank the identified factors and aspects. A case study is done on mining companies in Serbia. The key aspects are ranked according to an analysis that included experts who assess risks in mining companies (a maintenance engineer, a technologist, an ergonomist, a psychologist, and an organisational scientist). Failure to follow technical maintenance instructions, poor organisation of the training process, inadequate diagnostic equipment, and a lack of understanding of the work process are identified as the most important causes of human error.

Application of fuzzy group analytic hierarchy process in partner selection of international joint venture projects

Partner selection is gradually recognized as an essential factor in gaining success in a cooperative settings. In this paper, a novel approach based on fuzzy AHP group decision-making for partner selection of joint venture projects is proposed. In this approach, rst, the in uential factors for selection of appropriate partners based on literature review and interviews with experts are identi ed. Then, using a method considering the risk, knowledge, and educational background of decision-makers, the impact of decision-makers is calculated. Pairwise comparison matrices are performed, and the weights of criteria are calculated based on two methods (multiplicative and additive). Then, the calculated weights of criteria and the potential partners have been ranked via an ecient ranking index. Finally, the application of this methodology to a real case study in National Iranian Petrochemical Company (NPC) is conducted. The contribution of this study is developing a fresh systematic approach for partner selection of international joint ventures and application in a real-life case study to present an operational guideline to the petrochemical industries. The results of this study reveal that the equipment of the partner, its nancial capacity, trusts and management skills are the most important criteria for establishing the durable partners in the international joint venture of NPC.

The selection of the key ergonomic indicators influencing work efficiency in railway control rooms

This paper presents an analytical–synthetic model of ergonomic research of the abilities of the dispatcher/operator in the control room for the automatic control of railway transportation. Twenty performance indicators describing the operators’ performance (work capacity and perceptive abilities) and the main characteristics of the control room (work organization and ergo-technical analysis) are identified. A group fuzzy analytic hierarchy process is applied in the process of ranking and selection of key performance indicators of railway control rooms. The selected key performance indicators (the operator’s hand movement, visual symptoms of fatigue, device error analysis, location and dimensions of the control desk) are analysed in detail.

Extended Earned Value Management Based on Fuzzy Multi-Criteria Decision Making

This paper proposes an extended earned value management (EEVM) as an integrated comprehensive project progress measurement technique. The method considers all of project key success factors, simultaneously. That is the method guaranties the realistic weights achievement to implement project control and scheduling. The weights are employed to publish a correct and comprehensive progress reports which can guarantee the future decisions for the project. It is noteworthy that the weighting approach is not just an earned value management (EVM), but it covers its concept. Since, the method is comprehensive and according to its ability to take any key success factors in to account, it can be used as a good alternative for the EVM approach, and can be called as an EEVM. The method combines the fuzzy group analytic hierarchy process (FGAHP) and fuzzy technique of order performance by similarity to ideal solution (FTOPSIS) to define activity weights according to some projects uncertain data. Taking to account the advantages of FGAHP for criteria weighting besides FTOPSIS for activity weighting provides a flexible method works with human habits and projects vagueness and uncertainty. Efficiency of the proposed method has been practically verified on a stadium in Kurdistan. The results illustrate superiority of the method in case of comprehensiveness and flexibility in comparison with the other methods.

Application of Interval-valued Fuzzy Analytic Hierarchy Process Approach in Selection Cargo Terminals, a Case Study

Cargo terminals are the gateways for entrance of commodities into the transportation network. Therefore, locating them in optimal location could have a major impact on the cost effectiveness and efficiency of transport, traffic safety and reduction in environmental pollutions. Due to the presence of a large number of parameters involved and the existing uncertainties, decision making in this field is a complex task. If the decision makers cannot reach an agreement on the method of defining linguistic variables based on the fuzzy sets, favorable results and more accurate modeling can be achieved by using the interval-valued fuzzy sets (IVFSs), which provide an additional degree of freedom to represent the uncertainty and fuzziness in the real world. This study presents a group fuzzy analytic hierarchy process (AHP) based on IVFSs (IVF-AHP), and its application to find the optimal location for the Ghaen (Qayenat) cargo terminal in Ghaen City, Iran. The results show that the proposed method is a reliable method in selecting the optimal location for cargo terminals.

Improvement and application for group fuzzy analytic hierarchy process

Improvement and application for group fuzzy analytic hierarchy process

Developing a fuzzy AHP model to evaluate environmental sustainability from the perspective of Secured by Design scheme—A case study

Abstract In environmental security, Secured by Design (SBD) is one of the most important schemes which promote environmental sustainability in cities with prevention and reduction actions such as increase natural surveillance determine the specific definition of urban spaces and create a sense of ownership and responsibility in citizens. This paper discusses a model for evaluating environmental security from the perspective of SBD scheme and investigates the extent to which crime and fear of crime are integrated within environmental sustainability. For this purpose a hierarchical model with four levels suggested. This model decomposes the main principles of SBD scheme to localized criteria and sub criteria which influence it. These factors later prioritized using pairwise comparison logic and fuzzy group analytic hierarchy process (AHP) method and the relative importance of each factor on achieving environmental security determined. In addition the proposed model has been used to calculate the overall rating of quadratic areas in region 17 of Tehran based on their environmental sustainability. Also, using the calculation results, strategies were suggested separately for each SBD principle in order to reduce urban crime and improve the environmental sustainability of the studied area. Results showed that the area 4 and area 1 have the highest and lowest environmental security rate respectively. Finally this paper argues that SBD as an initiative is useful to assist in achieving environmental security and development of environmental sustainability.

A fuzzy goal programming model for strategic information technology investment assessment

PurposeThe high expenditures in information technology (IT) and the growing usage that penetrates the core of business have resulted in a need to effectively and efficiently evaluate strategic IT investments in organizations. The purpose of this paper is to propose a novel two‐dimensional approach that determines the deferrable strategy with the most value by maximizing the real option values while minimizing the risks associated with each alternative strategy.Design/methodology/approachIn the proposed approach, first, the deferrable investment strategies are prioritized according to their values using real option analysis (ROA). Then, the risks associated with each investment strategy are quantified using the group fuzzy analytic hierarchy process. Finally, the values associated with the two dimensions are integrated to determine the deferrable IT investment strategy with the most value using a fuzzy preemptive goal programming model.FindingsManagers face the difficulty that most IT investment projects are inherently risky, especially in a rapidly changing business environment. The paper proposes a framework that can be used to evaluate IT investments based on the real option concept. This simple, intuitive, generic and comprehensive approach incorporates the linkage among economic value, real option value and IT investments that could lead to a better‐structured decision process.Originality/valueIn contrast to the traditional ROA literature, the approach contributes to the literature by incorporating a risk dimension parameter. The paper emphasizes the importance of categorizing risk management in IT investment projects since some risk cannot be eliminated.