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In today's competitive environment, industries are required to increase reliability and safety level of their equipment with reasonable cost. Consequently, it is essential to select the appropriate maintenance strategy. In the paper industry, pumping of cooked pulp requires abrasion- and sometimes corrosion-resistant pumps that are able to handle up to 70 % solids content. But the maintenance engineer and supervisor often face failures of the pump. Hence, this article describes the application of multi criteria decision-making (MCDM) technique for the selection of optimum maintenance strategy for pumps used in the paper industry. The proposed hybrid MCDM model comprises fuzzy analytical hierarchy process (FAHP), grey relational analysis (GRA), and technique for order preference by similarity to ideal solution (TOPSIS) technique. The FAHP is used to compute the criteria weights whereas GRA-TOPSIS is used for determining the ranking of alternatives. This study discusses four maintenance strategies: corrective maintenance, predictive maintenance, time-based preventive maintenance, and condition-based maintenance. Four main criteria-safety, cost, added value, and feasibility-have been used to evaluate the optimum maintenance strategy. [ABSTRACT FROM AUTHOR]

Dealing with risk and addressing risk consequences constitute indispensable and specific elements of every business activity. The aim of this paper has been to assess the level of risk connected with the process of exploitation of hard coal deposits used for the production of coke in Poland, that is why a methodology has been developed which takes into account the impact of significant risk factors resulting from both geological and mining conditions upon unit cost of coal mining. This methodology constitutes a comprehensive approach to sustainable management of hard coal resources. The key source of information pertaining to exploitation risk factors is the digital geological model of hard coal deposit which has been developed. It comprises a structural model as well as a quality model of the basic quality parameters of coal. Structural models and coal quality models have been developed on the basis of litho-stratigraphic profiles from geological exploratory boreholes and underground observations (boreholes drilled from underground workings and their profiling). The structural grid model also contains information on tectonic disturbances (faults) or sedimentation disturbances (intercalations, wash-outs, and the like). The digital model was used as the basis for devising time schedules of development and preparatory works, as well as coal extraction proper. Historical results of mining and economic data from 81 longwalls mined in the years 2016–2022 have been used for the purpose of analysis of the impact of risk factors on unit operating costs. The analysis comprised a total of 23 criteria which influence the costs of mining. From that group, 10 risk factors have been selected by means of statistical analysis using segmented regression, these factors have been utilized to make an assessment of the forecast concerning risk factor level for zones of the deposit meant for mining until the year 2035. The risk factors taken into account were those which are due to natural hazards, geological structure of the deposit (coal seam) and technical limitations. Risk factor (RF) indicator has been developed, for its construction the Fuzzy Analytic Hierarchy Process (FAHP) has been used. The value of RF, which expresses the aggregated form of variability concerning individual factors pertaining to geology and mining, has been used to determine the adjusted own risk assessment when estimating the economic efficiency of the coking coal deposit for 8 exploitation zones with the use of discounted cash flow method. The assessed average value of RF for the entire deposit amounted to 0.29. The lowest level of RF was noted in case of zone W (RF = 0.17), whereas the highest value of risk occurs in zone PN (RF = 0.64). The values of RF were used to calculate the rate of discount as consolidated measure of own risk, when assessing investment projects in mining. For zone W with the lowest risk of mining the discount rate amounts to 8.34%, whereas in case of zone PN which has the highest risk level, it amounts to 15.02%. Assessing the level of mining risk provides the possibility to optimize the cost of mining, and may be utilized for making decisions concerning the sequence and time of mining from particular zones of the deposit. [ABSTRACT FROM AUTHOR]

This paper aims to develop an integrated Quality–Cost–Environmental (QCE) indicator for the selection of photovoltaic panels (PVps) offered to customers, considering the following criteria: (i) quality satisfaction; (ii) cost-effectiveness; and (iii) environmental impact throughout the life cycle. The proposed QCE indicator was developed within a framework that incorporated an FAHP (Fuzzy Analytic Hierarchy Process), cost-effectiveness analysis (CEA), and life cycle assessment (LCA). The model test confirmed its effectiveness in choosing a PVp which combines environmental friendliness throughout its entire life cycle with satisfactory quality and a reasonable purchase price for customers. The proposed model can be utilized by individuals, businesses, and public entities for the selection of high-quality, cost-efficient, and environmentally friendly PVps—thereby promoting sustainable development. [ABSTRACT FROM AUTHOR]

This paper aims to examine the main practices that shape sustainable port development in the context of Korean ports and generalize a typology of port–stakeholder decision framework for sustainable port development. First, the main practices of sustainable port development were examined through a comprehensive literature review and a holistic conceptual framework underpinned by sustainable development and stakeholder management theories. Semi-structured interviews were then conducted with 67 port managers in Korea. Lastly, FAHP was performed based on inputs from 18 port managers to analyze the priorities of the proposed sustainable port development practices. It was found that all proposed practices should be used for evaluating sustainable port development. It was also indicated that Optimized Operation Planning is the most important factor while Internal Environment Management is the least important factor perceived by Korean port managers. A typology of port–stakeholder framework for sustainable development was also generalized to assist port managers in making phased investment decisions. This research contributes to theory building by empirically identifying and validating the sustainable port development practices considering all three aspects of sustainability. It has also generalized a typology of port–stakeholder framework for sustainable development which can be used as a guideline for sustainable development decisions. [ABSTRACT FROM AUTHOR]

In lithium mining in the Argentine Northwest, mining companies are located strategically, depending on the availability of brines, but far from urban centers. Therefore, when selecting the right provider, it is necessary to consider multiple criteria. This paper presents the first multi-criteria decision model for the selecting suppliers in the lithium industry in the Argentine Northwest, in which a criterion of great importance for the region is considered and which is novel for the sector. From it, companies can select the best supplier through a ranking of qualifications without the variation that the preference of the person making the decision supposes. Fuzzy Analytical Hierarchy Process (FAHP) methods were integrated with Fuzzy Logic and the SCOR model. Therefore, it can be used in environments of uncertainty and ambiguity, combining quantitative and qualitative information. 6 criteria were defined with 3 levels of assessment: Quality, Price, Financial Solidity, Performance, After-sales Service, and Belonging. 729 combinations with possible selection results were obtained. This model was applied to four local suppliers by evaluating the input criteria. The result of the output variable Supplier Preferability was obtained, and from this, it was established which of them should be selected. This model it is expected to contribute to the decision-making of mining companies in the area. [ABSTRACT FROM AUTHOR]

The assembly process is generally considered one of the primary factors influencing the quality of complex products. Currently, most existing quality-integrated diagnostic methods for products tend to deteriorate over different processes and degrade over time. To address this issue, this paper introduces a systematic quality-integrated diagnostic method for complex product assembly processes. First, the influence factors and error sources in the complex assembly process are analyzed using the 5M1E and FAHP methodologies. Next, similarity-based multi-task clustering and dismantling using RGMM is applied to divide the assembly tasks. Finally, MMD-MSE is employed to develop a quality prediction model for the complex assembly process using a spatial–temporal transfer learning approach. Experiments were conducted on an array antenna assembly task, comparing the proposed method with conventional methods. The results show that the accuracy and PrUP of the proposed model are 97.6% and 95.2%, respectively, for the quality-integrated diagnostic of complex assembly processes, with a fluctuation in accuracy of less than 6%. The diagnostic results effectively meet expert evaluations and provide a stable, reliable, and practical solution for addressing quality fluctuations in complex production assembly processes. [ABSTRACT FROM AUTHOR]

Agile methods adopted in the software industries have given a new edge as well as scope to software outcomes. To determine anomalies that has been triggered by analytic hierarchical process (AHP) or any other fuzzy AHP methods in evaluation and selection in the establishment of two-way assessments of agile methods, a model methodology dependent on the AHP and fundamental hypothesis of the triangular fuzzy number (TFN) is depicted by communicating fuzzy AHP completely and numerically. In this paper we uncover the disagreement of Fuzzy analytic hierarchical process (FAHP) to decide the process which is considered best in agile according to the benchmark where semantic terms are correlated with triangular fuzzy numbers. Furthermore, the research paper also discovers the process that is considered best amongst the various criteria of decision-making issues for agile methodology. This paper further applies two-way assessment that discusses the viewpoint of software developers as well as managers and focuses on the significance of different identified attributes and then the overall utility is calculated considering the threshold measure from the perspective of the organization. [ABSTRACT FROM AUTHOR]

The aim of the paper is to determine the risk level of a contract extension with the existing policyholders, which is further propagated to the business effectiveness and long-term sustainability of the company. The uncertainties in the relative importance of risk factors, their values, and risk levels are described by the linguistic forms, which are modeled by using the fuzzy sets theory. The evaluations of the relative importance of risk factors are stated as a fuzzy group decision-making problem. The weights of risk factors are obtained by using a fuzzy analytic hierarchy process. The determination of production rules for the assessment of the risk level is based on fuzzy IF-THAN rules. The verification of the model is performed by using real-life data originating from the insurance company which operates in the Republic of Serbia. [ABSTRACT FROM AUTHOR]

• A evaluation model of blasting scheme for tunnel undercrossing existing buildings was proposed. • The negative effect of blasting on the evaluation results by the blasting scheme was considered. • Targeted optimization of blasting parameters was conducted based on index contribution. • Optimization measures was proposed for the blasting program subjected to engineering application. Blasting scheme design of tunnel is the key link of drilling and blasting construction. The rationality of blasting scheme is affected by many factors, which is a complex multi-criteria decision making (MCDM) problem. In order to improve the blasting effect of tunnel crossing under existing buildings and reduce the impact of blasting vibration on existing buildings, this paper proposes a blasting scheme evaluation model and blasting parameter optimization method for under-crossing tunnels. First, a three-level index system and 15 key indices are proposed according to the influencing factors of blasting effect. The weight of each evaluation indices is determined by logarithmic fuzzy preference programming (LFPP) method, and the reliability function of dynamic indices and the grading standard of index rationality are established based on the field conditions. Second, the fuzzy analytic hierarchy process (FAHP) is applied to evaluate the rationality of the blasting scheme, and the contribution degree of each index is calculated according to the evaluation results so as to determine the main parameters affecting the evaluation results. The proposed model is applied to No.3 Tunnel of E60 Highway in Georgia, and the key index parameters are optimized based on the evaluation results of the original blasting scheme. The proposed model is compared with several traditional methods. The comparison shows that the evaluation results of the proposed model are more consistent with the field monitoring results than those of traditional models, which verifies the reliability of the proposed model. This study can provide reference for the formulation of blasting scheme for tunnels crossing under existing buildings. [ABSTRACT FROM AUTHOR]

Online shopping has gradually become an important way of consumption, and consumers are paying more and more attention to negative reviews. In order to avoid the massive amount of negative review information leading to loss of useful information, this paper proposes a method for evaluating the usefulness of negative online reviews. Firstly, the method constructs an evaluation index system for the usefulness of negative online reviews from three aspects: the form feature, text feature, and reviewer feature of negative reviews, and uses a combination weighting method based on fuzzy analytic hierarchy process (FAHP) and entropy method to determine the weight of each index. Secondly, the usefulness ranking results of negative online reviews are obtained through the improved TOPSIS method based on the combined weighting method. Finally, the empirical analysis of the proposed model is carried out by crawling the negative online reviews of JD.com Fresh Food platform, and the improved model is compared with the traditional TOPSIS model, which proves the feasibility and effectiveness of the model. [ABSTRACT FROM AUTHOR]

The residential sector is well known to be one of the main energy consumers worldwide. The purpose of this study is to select the best renewable energy alternatives for electricity generation in a residential building by using a new integrated fuzzy multi-criteria group decision-making method. In renewable energy decision-making problems, the preferences of experts and decision-makers are generally uncertain. Furthermore, it is challenging to quantify the reel performance of renewable energy alternatives using a set of exact values. Fuzzy logic is commonly applied to deal with those uncertainties. The method proposed in this paper combines different methods. First, the Delphi method is used in order to select a preliminary set of renewable energy alternatives for electricity generation as well as a preliminary set of criteria (economic, environmental, social, etc.). Then, the questionnaire is used to study the renewable energy alternatives preferences of the residents of the residential building'. Later, the FAHP (Fuzzy Analytical Hierarchy Process) is implemented to obtain the weighs of the criteria taking into consideration uncertainties in expert's judgments. Finally, the FPROMETHEE (Fuzzy Preference Ranking Organization Method for Enrichment Evaluation) global ranking is performed in order to get a complete ranking of the renewable energy alternatives taking into account uncertainties related to the alternatives' evaluations. The originality of this paper comes from the application of the proposed integrated Delphi- FAHP- FPROMETHEE methodology for the selection of the best renewable energy alternatives for electricity generation in a residential building. A case study has validated the effectiveness and the applicability of the proposed method. The results reveal that the proposed integrated method helps to formulate the problem and is particularly effective in handling uncertain data. It facilitates the selection of the best renewable energy alternatives in a manner that is participatory, comprehensive, robust, and reliable. • This paper presents a new methodology for the selection of the best renewable energy alternatives in a residential building. • A new fuzzy integrated Delphi- FAHP- FPROMETHEE methodology has been applied. • The sensitivity analysis indicates that the proposed methodology is stable with respect to decision-makers' preferences. [ABSTRACT FROM AUTHOR]

In the last few years, fibers have been proposed as one of the most important additives for the development of reinforced asphalt mixtures. The optimal fiber selection is a very complex task, as an extensive range of criteria and alternatives have to be taken into account. Decision support systems have been applied in the construction sector, but not for selecting fibers for bituminous mixtures. To fill this gap, two Multi-Criteria Decision-Making Analysis methodologies for the selection of the best fiber to be used in Asphalt Concretes are presented in this paper. The Weighted Aggregate Sum Product Assessment (WASPAS) methodology and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) integrated with Fuzzy Analytic Hierarchy Process (FAHP) are used to evaluate the effect of various types of fibers on the mechanical performance of bituminous mixtures. Given the uncertainty involved, a stochastic simulation is proposed using the Monte Carlo method. A statistical analysis is carried out to verify the results obtained. Both methods of multi-criteria analysis were effective, with TOPSIS being slightly more conservative in the assignment of performance scores. Synthetic fibers proved to be a suitable option as did fibers with high tensile strength and elastic modulus. [ABSTRACT FROM AUTHOR]

Nowadays, the industry is undergoing the Fourth Industrial Revolution, and techniques and algorithms for automated compliance checking (ACC) are continually being improved, generalized and flexible with the use of semantic and logic-based representations. However, there is still a lack of research that addresses advances in ACC tools headed for the Industry 4.0 (I4.0) perspective and that point out practitioners' perceptions concerning the current application of these technologies. In this sense, this paper aims to conduct a systematic review to identify the main automated code-checking tools to regulatory compliance in the I4.0 era, indicating new trends and possible gaps, and then ranking the selected technologies with the support of two soft hybrid multi-criteria decision-making techniques. By content analysis, we identified and categorized seven main technologies used to ACC in several industrial areas. As a practical example of group decision-making and modeling of uncertainty, we implemented fuzzy analytical hierarchical process to aggregate different perspectives and obtain the criteria weights and combined it with TOPSIS and VIKOR methods. To do this, by means of expert panel, we evaluated practitioner's perception about the surveyed technologies concerning the ISO/IEC 9126 standard. The results indicate that both methods have shown similar rankings, and although portability was considered the most relevant criterion, open-source tools are key issues when choosing ACC technologies. Several further research trends were also pointed out through this theoretical–empirical approach, such as the use of natural language processing, declarative rule processing and flow-based processing. [ABSTRACT FROM AUTHOR]

Whatever be the nature of underlying software, the impact of the software development process that was used to create it would remain vital. The objective of this paper is to provide a process selection framework for the software development firm's engineers and managers, looking to identify the proper way to build software to run on a mobile, web, or desktop. The motivation behind this work comes from the fact that the applications that fall in one of the above three categories can be significantly different in terms of scale, UI, and memory requirements, time to market, and other characteristics. Software development that needs to be completed in a challenging timeframe has to resort to principles and values as declared in Agile Manifesto. The availability of various agile methodologies has made the project managers often stuck when selecting the most suitable one. The proposed agile process identification system addresses this dilemma of engineering fraternity using a fuzzy variant of a popular multiple‐criteria decision‐making (MCDM) technique called the analytic hierarchy process (AHP). The proposed system is validated through a primary dataset generated as a result of the development of 20 software projects. The results are encouraging enough with a probability of true identification close to 88%. [ABSTRACT FROM AUTHOR]

Finding an appropriate way to improve the investment comprehensive benefits for on-line monitoring is a new issue for power industry. In this paper, a priority assessment model for transformer on-line monitoring is proposed. The assessment model consists of device level and system level. The device level is divided into property assessment and operation assessment. The details of various assessment methods were described in the following sections, including device property assessment based on fuzzy analytic hierarchy process (FAHP), operation condition assessment method based on condition assessment technology and system level assessment method based on risk benefits index. An actual grid is utilized to validate the model and the numerical results illustrate that: the proposed assessment model can provide an appropriate on-line monitoring investment order for transformers. It also verifies that considering multiple aspects related to the target problem could give a more comprehensive assessment result than just considering just one or two of them. This paper provides a feasible solution to achieve more investment benefits for transformer online monitoring, which can provide on-line monitoring investment references for power industry. [ABSTRACT FROM AUTHOR]

From the perspective of the complex multi-factors that affect manufacturing green competitiveness, this study constructs a green competitiveness index measurement indicator system of manufacturing industry in Yangtze River Delta Urban Agglomeration, which includes five dimensions: economic creativity, technological innovation, energy and environmental protection, industrial structure optimization, and social service capabilities.The manufacturing green competitiveness index in Yangtze River Delta Urban Agglomeration in 2014-2018 is measured and analyzed by using the comprehensive evaluation model of gray correlation projection method based on the combined weights of FAHP and maximum deviation. The results show that manufacturing green competitiveness of Yangtze River Delta Urban Agglomeration generally shows a relatively stable and continuous improvement trend, but the regional differences are large: regional cities and general node cities have significantly lower manufacturing green competitiveness than the leading cities and hub cities, and the pace of industrial structure transformation and upgrading in the whole region also needs to be accelerated. Based on these results, this paper puts forward some policy recommendations for comprehensive development of Yangtze River Delta Urban Agglomeration manufacturing industry: focus on improving the effective guidance of the positive incentive effect of technological innovation on manufacturing green competitiveness level, and solving the problem of insufficient technological innovation achievement transformation benefits; replan regional space, strengthen the integration of all industrial resources, reducing homogeneous competition; strengthen the ecological co-construction of regional manufacturing and improve social service security level. [ABSTRACT FROM AUTHOR]

Public bicycle sharing system (PBSS) has been adopted around the globe to reduce traffic congestion, CO 2 emissions and for positive health effects. The first system was initially started in the year 1965 at Amsterdam and now it has been expanded almost in all the continents of the globe. The adoption of this concept was initially seen in developed countries. Now in the past decade various developing countries also have implemented the PBSS in their urban areas. However, the developing countries are facing many implementations and less ridership issues due to various barriers. This paper identifies the barriers which are hinders in the way of implementation of PBSS. An identified 31 barrier was categorized under six groups for ranking. The Fuzzy Analytical Hierarchical Process (FAHP) is applied to examine the relevance and prioritize them with the help of different stakeholders. Total 31 stakeholders were selected as experts from different working backgrounds for this study. The experts were grouped into six namely decision makers, academicians, consultants, scientists and researchers, operators, and users. The perspective of each group is also examined and checked using Kendall' coefficient. The majority of experts opine that City infrastructure barrier and travel characteristics barriers are most influential barriers for successful implementation of PBSS while technological and geographical barriers are least influential barriers. The overall results and opinions by different group of experts will help the decision makers to formulate effective policy to tackle all the barriers prior to implementation of PBSS in Indian urban areas. With the help of this framework, time and financial resources of the government can be utilized in an optimum way and the savings can be utilized for improving necessary city infrastructure. [ABSTRACT FROM AUTHOR]

Due to rising concerns for environmental sustainability, the Indian electronic industry faces immense pressure to incorporate effective sustainable practices into the supply chain (SC) planning. Consequently, manufacturing enterprises (ME) are exploring the option of re-examining their SC strategies and taking a formalized approach towards a sustainable partnership with logistics providers. To begin with, it is imperative to associate with sustainable forward and reverse logistics providers to manage effectively the upward and downstream flows simultaneously. In this context, this paper proposes an integrated SC network for the evaluation and selection of forward distribution partners (FDP) and third party reverse logistic providers (3PRLP) from a sustainable perspective of an Indian electronic ME. The sustainable evaluation of the logistic partners is performed using fuzzy analytic hierarchy process and the technique for order performance by similarity to ideal solution. The integrated logistics network is modeled as a bi-objective mixed-integer programming problem with the objective of maximizing the profit of the manufacturer and maximizing the sustainable score of the selected forward and reverse logistics providers. The novelty of the study is its ranking of the FDPs and 3PRLPs on the economic, environmental, and social dimensions of sustainability and the simultaneous integration of logistics outsourcing decisions for the forward and reverse flow of products. Goal programming approach is utilized to capture the trade-off between the conflicting objectives and to attain a satisfying solution to the bi-objective problem. The results indicate that integrating the strategic decisions of selection of logistics partners with the operational flow planning decisions can immensely improve the sustainable performance value of the SC network and secure reasonable profits. The managerial implications drawn from the result analysis provide a sustainable framework to the ME for enhancing its corporate image. [ABSTRACT FROM AUTHOR]

Abstract An Inland Waterway Transportation System is often claimed to be safe, efficient and economic. However, traffic congestion and vessel collision have become serious threats to marine safety, especially in the one-way waterways. The aim of this paper is to rank the vessels in the controlled waterways of the upper Yangtze River and to generate the optimal traffic commands for each vessel so as to ensure marine safety and traffic efficiency. In this study, the proposed approach is based on the combination of Fuzzy Analytical Hierarchy Process (FAHP) with an Expert System (ES). Vessel data collected from Automatic Identification Systems (AIS) are first analyzed by experts, and some external environment and internal factors are selected as Significant Influencing Factors (SIFs). FAHP is then used for modelling a hierarchical structure and determining the weight of each SIF. Finally, the sorted vessel sequence and appropriate traffic commands can be achieved using ES. The experiment result shows that the waiting time of vessels is averagely decreased about 22 min compared with the existing Traffic Signal Revealing System. This will not only significantly improve the efficiency and accuracy of the vessel traffic scheduling, but also increase the waterway capacity by reducing the travelling time. Highlights • A novel approach is proposed to enhance vessel traffic scheduling for the controlled waterways in the upper Yangtze River. • Based on Fuzzy Analytical Hierarchy Process and the Expert System, the AIS data are discussed and analyzed in detail. • Traffic congestion and vessel collisions in the controlled waterways could be preventable using the proposed approach. • The reliability and efficiency of proposed method have been verified by comparing with Traffic Signal Revealing System. [ABSTRACT FROM AUTHOR]

Abstract Data processing techniques for Ground Penetrating Radar (GPR) image mining provide essential information to optimize maintenance management of Water Supply Systems (WSSs). These techniques aim to elaborate on radargrams in order to produce meaningful graphical representations of critical buried components of WSSs. These representations are helpful non-destructive evaluation tools to prevent possible failures in WSSs by keeping them adequately monitored. This paper proposes an integrated multi-criteria decision making (MCDM) approach to prioritize various data processing techniques by means of ranking their outputs, namely their resulting GPR image representations. The Fuzzy Analytic Hierarchy Process (FAHP) is applied to weight various evaluation criteria, with the purpose of managing vagueness and uncertainty characterizing experts' judgments. Then, the ELimination Et Choix Traduisant la RÉalité III (ELECTRE III) method is used to obtain the final ranking of alternatives. A real case study, focusing on a set of four GPR images as outputs of different data processing techniques, is presented to prove the usefulness of the proposed hybrid approach. In particular, the GPR images are ranked according the evaluation of five criteria namely visualization, interpretation, identification of features, extraction of information and affordability. The findings offer a structured support in selecting the most suitable data processing technique(s) to explore WSS underground. In the presented case, two options, namely the variance filter and the subtraction methods, offer the best results. Highlights • An integrated multi-criteria approach is proposed to prioritize various data processing techniques for GPR image mining. • Four representations of WSSs are produced by analysis of raw images, multi-agent system, subtraction and variance filter. • The FAHP is applied to weight five evaluation criteria by considering judgments of an expert in the field. • The ELECTRE III method is proposed to rank GPR images and establish the technique more suitable for maintaining WSSs. [ABSTRACT FROM AUTHOR]

Logistic processes imply the presence of a large number of different types of risks, primarily in the fields of transport, transshipment, and storage of goods. The main reason for this fact is the presence of numerous participants of logistic systems, the existence of various interactions between large numbers of subsystems or subprocesses, which causes disturbances and uncertainties, both locally and at the system level. The initial idea of this research is to model the total risk of logistic processes based on evaluation of the significance of different risk elements, their interrelations, and their influence on total risk. This paper presents a developed fuzzy logic model based on the analytic hierarchy process (AHP) model and fuzzy analytic hierarchy process (FAHP). The model is designed to be practical, understandable, and easy to implement and maintain. The incorporated data have different forms of crisp numbers, triangular fuzzy numbers, and linguistic variables. Logistic process data are incorporated into the proposed model and validated with an example case. [ABSTRACT FROM AUTHOR]

Risk assessment is vital for cost-effective ship management in maritime industry since numerous maritime activities pose potential hazards according to the human causalities. Therefore, safety practitioners attempt to offer proactive approaches to mitigate risk as much as possible. In this context, this article presents a hybrid risk-based approach for maritime industry by adopting Fuzzy Analytic Hierarchy Process (FAHP) with fuzzy VIKOR (FVIKOR) methods under Fine-Kinney approach. To illustrate the hybrid risk-based approach, ballast tank maintenance process is handled since there are various hazards causing fatalities, severe injuries, and illness during ballast tank maintenance procedure than any other type of shipboard work. An extensive risk analysis is performed to enhance environment safety and operational reliability in maritime industry. Besides its theoretical contribution, the outcomes of the paper contribute to improve overall safety level of ship by considering potential hazards in risk management. [ABSTRACT FROM PUBLISHER]

Being threatened by various facilities in a city, modern urban environments have become extremely vulnerable and fragile. Hospitals are among potentially high-risk facilities. Environmental awareness is relatively lacking in the health sector with few organizations measuring their performance. Therefore, the issue is exceedingly important. This paper aims to identify and prioritize factors that influence environmental performance in hospitals. To identify factors that influence environmental performance in hospitals, a comprehensive review of literature was performed to compile a list of criteria, sub-criteria, and indicators of environmental performance in healthcare centers. The list was then adjusted by experts in the field using the fuzzy Delphi method and the factors were prioritized using fuzzy analytical hierarchy process. In order to verify the results, a fuzzy technique was also applied to determine order of preference by similarity to ideal solution. Therefore to verify the weights and priorities assigned to the factors influencing environmental performance, the factors were once again rated by experts based on the criteria of specificity, measurability, availability, being realistic, and time-related. According to the results, 6 criteria, 22 sub-criteria, and 48 indicators were identified and prioritized. Furthermore, Fuzzy AHP and Fuzzy TOPSIS resulted in the same prioritization of the factors. Therefore, the results obtained from Fuzzy AHP are acceptable. Using appropriate indicators together with appropriate techniques can serve to improve environmental performance in health care centers and the obtained results showed that the FAHP method can be used for prioritizing environmental performance factors in hospitals successfully. [ABSTRACT FROM AUTHOR]

Increase of population, development of industry, environmental problems and continuous energy consumption in the world render renewable energy resources crucial. This paper focuses on multiple criteria decision making (MCDM) models for energy saving and using energy resources efficiently in order to maintain sustainable operations at wastewater treatment plants (WWTPs). An integrated fuzzy quality function deployment (FQFD) framework and technique for order preferences by similarity to an ideal solution (TOPSIS) selection algorithm is proposed. Fuzzy analytic hierarchy process (FAHP) is used to determine importance weights of attributes in MCDM model to avoid inconsistent results of crisp QFD analyses caused by the variability of human judgment. Fuzzy analytical network process (FANP) is used to consider both symmetrical and asymmetrical relationships between customer requirements (CRs) and engineering characteristics (ECs) for constituting internal and external correlation matrices in the house of quality (HOQ). The comprehensive weight vector of ECs is used as the weights of the selection criteria in the TOPSIS side of the integrated methodology. The proposed MCDM methodology is used for the goal of choosing the ideal gas fuel at WWTPs. Regarding to the results of application of the proposed MCDM model at a WWTP in Turkey, the most important EC regarding to the goal is hydrocarbons with the weight value of 0.32, while gas processing system with 0.21 is the second and impurities with 0.19 is the third EC. Biogas is chosen as the ideal gas fuel. In addition, natural gas is the second, liquefied natural gas is the third, compressed natural gas is the fourth and landfill gas is the fifth gas fuels in turn at the WWTP in Turkey. [ABSTRACT FROM AUTHOR]

Occupational Health and Safety (OHS) is a basis to reduce occupational accidents in an acceptable level, and it covers employee health, safety, and welfare in the workplaces. Hospitals as the largest employer group in healthcare industry in Turkey face major hazards categorized as chemical, biological, physical, ergonomic, and psychosocial risks. Although Turkey demonstrates rapid economic growth, OHS practices have not been fully put into practice, and necessary attention has not been paid to the health industry. For this reason, this paper aims to assess risks for health staff, contribute for planning of health services, and enhance regulations. A case study was carried out in a leading hospital in Turkey using a two-stage fuzzy multi-criteria approach, which provides more consistency in decision-making process and gives an appropriate final rank of hazard types. Fuzzy Analytic Hierarchy Process (FAHP) is used in weighing five risk parameters, which are severity, occurrence, undetectability, sensitivity to maintenance non-execution, and sensitivity to personal protective equipment (PPE) non-utilization. The fuzzy VIKOR (FVIKOR) approach is then applied for prioritization of hazard types in each department of the hospital. On conclusion of the hazard control hierarchy, measures are overtaken for the hazards, and areas open for improvement are presented. [ABSTRACT FROM PUBLISHER]

The rapid development of information technology has made a wide range of cutting-edge technologies accessible, supporting the flourishing of human existence. Modern technology has made it possible for new computer-based technological strategies like gamification. The pedagogical framework is based on the “gamification” game format, which is one of the most recent teaching strategies and has an engaging component for students. Gamification, flipped learning, and problem-based learning are three examples of the technical aspect of escape rooms. In the academic setting, gamification aims to boost student engagement and motivation in order to produce a better user experience. Gamification has been found to increase levels of participation, foster it, and improve activity outcomes. Gamification is recommended in educational settings to improve students’ achievement, focus, and contentment in light of these benefits. In order to establish an effective learning environment where students may effectively improve their learning capacities and boost their performance, it can be difficult to select a higher performing technique among the available techniques due to the ongoing use of gamification techniques. The fuzzy analytical hierarchy process (FAHP) and evaluation based on distance from average solution (EDAS) are applied in order to determine the criterion weighting and assess the techniques in order to make a good decision. The presented paper analyzed numerous game-based learning techniques along with their applications in the educational field. Additionally, ten criteria and eight gamification methodologies are used to assess and pick the prior pertinent works. By utilizing the suggested approaches, the decision problem has been resolved. The FAHP approach is used in the suggested analysis to evaluate the criteria and determine their weights. Then, using the EDAS method, places are assigned to the chosen procedures based on their evaluation score and criterion weighting. The results of the appraisal show that the gamification technique with the highest production takes first place and is regarded as the best-performing and most successful technique. On the other hand, it is clear that the technique with the lowest production takes the bottom spot and is referred to as the least expensive and lowest performing technique. In order to increase students’ motivation, which could have a substantial impact on learning, it has been discovered that gamification is a feasible strategy. [ABSTRACT FROM AUTHOR]

In precision machine assembly process, the product quality is not only dependent on the tolerance design, but also on the assurance of the assembly process planning. Therefore, there is a need to develop a mathematical analysis method to predict and control the variation in an assembly process. In this paper, to improve assembly precision and finally improve assembly quality stability for machining products, a mechanical assembly accuracy prediction model based on a state space equation is put forward. In this approach, fuzzy analytical hierarchy process (FAHP) is used to identify the key factor affecting the product quality. With the help of current variation of assembling process, the state space equation is used to build the variation propagation model of a mechanical assembly system, predict the influence law of machine precision, and guarantee the machine assembly precision within the boundary. Finally, the validity is verified by using the application of the small six-axis precision machine tool. [ABSTRACT FROM AUTHOR]

This paper presents a performance assessment of 88 Association of Southeast Asian Nations banks from 2010 to 2013, using an integrated three-stage approach on financial criteria that emulates the CAMELS rating system. More precisely, fuzzy analytic hierarchy process is used first to assess the relative weights of a number of criteria related to capital adequacy (C), asset quality (A), management quality (M), earnings (E), liquidity (L), and sensitivity to market risk (S) based on the opinion of 88 Association of Southeast Asian Nations experts. Then, these weights are used as technique for order of preference by similarity to ideal solution inputs to assess their relative efficiency. Lastly, neural networks are combined with technique for order of preference by similarity to ideal solution results to produce a model for banking performance with effective predictive ability. The results reveal that contextual variables have a prominent impact on efficiency. Specifically, parsimony in equity leveraging derived from Islamic finance principles may be the underlying cause in explaining higher efficiency levels. [ABSTRACT FROM AUTHOR]

In this paper, the application of hexagonal fuzzy multiple-criteria decision-making (MCDM) methodology for the site selection of electric vehicle charging stations is considered. In this regard, four factors and thirteen sub-factors have been taken into consideration for E-vehicle charging site selection. In this research, the geographic information system (GIS) has been incorporated with MCDM techniques. The fuzzy analytic hierarchy process (FAHP) is used to obtain a fuzzy weight of factors and sub-factors. MCDM tools fuzzy technique for order of preference by similarity to ideal solution (FTOPSIS) and fuzzy complex proportional assessment (FCOPRAS) have been used to rank the selected sites. A centroid-based method for defuzzification and distance measure between two hexagonal fuzzy numbers (HFN) has been developed for this paper. A practical example in Howrah, India, is considered to show the applicability and usefulness of the model. The results depict the suitability of the proposed research. Comparative and sensitivity analyses have been demonstrated to check the reliability, robustness and effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

This paper addresses the problem of evaluating vehicle failure modes efficiently during the driving process. Generally, the most critical factors for preventing risk in potential failure modes are identified by the experience of experts through the widely used failure mode and effect analysis (FMEA). However, it has previously been difficult to evaluate the vehicle failure mode with crisp values. In this paper, we propose a novel hybrid scheme based on a cost-based FMEA, fuzzy analytic hierarchy process (FAHP), and extended fuzzy multi-objective optimization by ratio analysis plus full multiplicative form (EFMULTIMOORA) to evaluate vehicle failure modes efficiently. Specifically, vehicle failure modes are first screened out by cost-based FMEA according to maintenance information, and then the weights of the three criteria of maintenance time (T), maintenance cost (C), and maintenance benefit (B) are calculated using FAHP and the rankings of failure modes are determined by EFMULTIMOORA. Different from existing schemes, the EFMULTIMOORA in our proposed hybrid scheme calculates the ranking of vehicle failure modes based on three new risk factors (T, C, and B) through fuzzy linguistic terms for order preference. Furthermore, the applicability of the proposed hybrid scheme is presented by conducting a case study involving vehicle failure modes of one common vehicle type (Hyundai), and a sensitivity analysis and comparisons are conducted to validate the effectiveness of the obtained results. In summary, our numerical analyses indicate that the proposed method can effectively help enterprises and researchers in the risk evaluation and the identification of critical vehicle failure modes. [ABSTRACT FROM AUTHOR]

Abstract: The material plays an important role in an engineering design process. The suitable material selection for a particular product is one of the vital tasks for the designers. In order to fulfil the product’s end requirements, designers need to analyze the performance of various materials and spot suitable materials with precise functionalities. Due to the presence of large number of materials with diverse properties, the material selection process is complicated and time consuming task. There is a necessity of systematic and efficient approach towards material selection to choose best alternative material for a product. The aim of this paper is to describe the application of four Multi Criteria Decision Making methods for solving pipes material selection problem in sugar industry. FAHP-TOPSIS, FAHP-VIKOR, FAHP-ELECTRE, FAHP-PROMTHEE are the four methods used to choose the best alternative among the various materials. The ranking performance of various MCDM methods is also compared with each other and exploring the effectiveness and flexibility of VIKOR method. Five stainless steel grades such as J4, JSLAUS, J204Cu, 409M, 304 and seven evaluation criteria such as yield strength, ultimate tensile strength, percentage of elongation, hardness, cost, corrosion rate and wear rate are focussed in this study to choose the suitable material. [Copyright &y& Elsevier]

The engineers can frequently encounter with the situation to select the optimum option among the alternatives related with tunneling operations. The optimum choice can be selected by the experienced engineers taking into consideration their judgment and intuition. However, decision-making methods can offer to the engineers to support their optimum selection for a particular application in a scientific way. The Fuzzy Analytical Hierarchy Process (FAHP) is one of the multi attribute decision-making (MADM) methods utilizing structured pair-wise comparisons. This paper presents an application of the FAHP method to the selection of the optimum support design for water transporting tunnel in Naien. The methodology considers six main criteria, considering: displacement values for determined history locations, factor of safety (FOS), cost (total cost), time, mechanization and applicability factor for the selection of support design. The displacements and stress values were obtained by using the finite difference program FLAC2D as the numerical studies have been widely used by engineers examining the response of tunnels, in advance. After carrying out several numerical models for different support designs, the FAHP method was incorporated to evaluate these support designs according to the pre-determined criteria. These studies show that such FAHP application can effectively assist engineers to evaluate the alternatives support system for tunnels. [ABSTRACT FROM AUTHOR]

The classification performance evaluation goal for an air classifier is usually limited to one of the classification performance indices including cut size, classification precision, Newton classification efficiency and degree of dispersion. This method hardly evaluates these performance indices of an air classifier comprehensively and suitably. In order to evaluate the classification performance truly and synthetically, Fuzzy Analytic Hierarchy Process is used to calculate the weights of the classification performance indices after determining the hierarchical model in the present paper. The dimensionless transformation eliminates the effect of the different dimensions. Then, the comprehensive evaluation value of the classification performance for each experiment is obtained using the linear weighted method. The maximum value corresponds to the best classification performance among these evaluation values. In the present study, a turbo air classifier is used as the classification system and talc powders are used as materials. The best classification performance indices are a cut size of 16.5 μm, a classification precision of 0.59, a Newton classification efficiency of 57%, and a degree of dispersion of 2.13. The corresponding optimal operational parameter combinations are: the feeding speed is 40 kg·h-1, the air inlet velocity is 5 m·s-1 and the rotor cage's rotary speed is 1200·min-1. This assessment method avoids the limitation of evaluating a single classification performance index and the incomplete information derived from single factor experiments. Furthermore, the method also provides quantitative evaluation criteria for the classification performance of an air classifier. In the proposed method, the classification performance indices can be selected and the precedence relation matrix of Fuzzy Analytic Hierarchy Process can be set flexibly according to production requirements. [ABSTRACT FROM AUTHOR]

Systems Engineering (SE) allows addressing the design of complex systems from a holistic standpoint, starting from the early stage until the end of its lifetime. Using a SE approach, all the stakeholders' needs can be considered, encompassing requirements coming from all the different fields connected to design. Adopting SE, the ranking of the proposed design alternatives can be carried out using Multi-Criteria Decision Making (MCDM) methods, which foresee the involvement in the decision-making process of a team of experts. Among MCDM methods, fuzzy-based ones could be advantageous whenever the decision-making process is mainly based on experts' sensibility, because there is a lack of reliable quantitative information and/or the project is in the very early stage. This is the typical case of R&D activities on nuclear fusion, where big projects (ITER, DEMO) must contend with significant uncertainties. Therefore, a MCDM-based SE approach could help to improve the progress of these projects. Several applications are recalled in this paper and a further case study, regarding the Automated Inspection and Maintenance Test Unit (AIM-TU) concept design, is presented. In the framework of EU DEMO project, the AIM-TU has been proposed to provide to the international community a facility able to perform, with high reliability, robotic maintenance and inspection procedures in DEMO-oriented environments. In this paper the SE approach has been applied to the AIM-TU concept selection, adopting the fuzzy Analytic Hierarchy Process MCDM method for the best option selection. To this purpose, a novel fuzzy-based decision support tool named ELIGERE has been used. [ABSTRACT FROM AUTHOR]

Abstract: The low carbon economy (LCE) is considered as a kind of development mode (low carbon development, LCD) in this paper. So several problems appear, e.g., what kind of development is LCD? And, how to evaluate the level of LCD? The aim of this study is just to answer these questions. Firstly, the indicators’ system of the LCD level was constructed, which contains five main indicators and 10 sub-indicators. Then, 47 representative countries (areas) worldwide were taken as the numerical case. In the empirical research process, a two step methodology of combining the Fuzzy Analytic Hierarchy Process (FAHP) with the Technique for Order Performance by Similarity to Ideal Solution method (TOPSIS) is proposed. FAHP was used to determinate the main and sub-indicators’ weights of the 47 countries’ (areas’) LCD level, then the TOPSIS method used these weights as its own input weights to complete the whole calculation process. The results indicate that the method proposed can be successfully used in the study and the concept of the LCD level be considered as a very useful tool because the conclusions related to it have some certain directive significances when we have to take decisions on some items. In the end, some reasonable policy suggestions are proposed and some directions for future studies are put forward. [Copyright &y& Elsevier]

Abstract: A new classification system is presented to evaluate and ranking the sawability of carbonate rock. The sawability of carbonate rock is classified into five categories: excellent, good, fair, poor and very poor. The sawability is assumed to depend on the uniaxial compressive strength, Young’s modulus, Mohs hardness, and a new abrasivity index. The FAHP approach is used to determine the weights of the above-mentioned parameters by decision makers. Moreover, in this paper, a new classification system was developed to modify Schimazek’s F-abrasiveness factor. In this new abrasivity classification, each parameter has a different importance coefficient. The new abrasivity index of carbonate rocks can be obtained from this new abrasivity classification system. The calculated sawability index of developed classification is applied for Iranian carbonate rocks to evaluation the energy consumption in rock sawing process. A variety of two groups of carbonate rocks (seven types) were saw using a fully instrumented laboratory sawing rig at different feed rates, peripheral speeds, and depth of cut. Then, a new statistical model was obtained using multiple regression method based on operating parameters and rock sawability index. [Copyright &y& Elsevier]

Abstract: For manufacturing industries, financial performance evaluation is very important in a highly competitive environment. Therefore, an accurate and appropriate performance evaluation is critical. As financial performance indicators reflect the competitiveness of a company, they must be carefully identified in the evaluation process. Generally, traditional accounting-based financial performance (AFP) measures are used for performance evaluation. However, these measures are not sufficient for performance evaluation solely in the modern industry time. So, value-based financial performance (VFP) measures have recently been introduced to express the company value. In this paper, we propose a new financial performance evaluation approach to rank the companies of each sector in the Turkish manufacturing industry. For this purpose, a hierarchical financial performance evaluation model is structured based on the AFP and VFP main-criteria and their sub-criteria. We use fuzzy analytic hierarchy process (FAHP) to determine the weights of the criteria. The companies are ranked according to their own manufacturing sector by using TOPSIS and VIKOR comparatively. The results show that the obtained ranks of the companies by these methods are almost same with respect to their own sectors. [Copyright &y& Elsevier]

Abstract: This paper is aimed to present a fuzzy decision-making approach for prioritizing effective 7Ms to improve production systems performance. In this research systematic approach has been used for organization and production system inputs which named as 7Ms (Management, Manpower, Marketing, Method, Machine, Material, and Money). Linguistic values are used to assess the ratings and weights for 7Ms. These linguistic ratings can be expressed in trapezoidal or triangular fuzzy numbers. Then, a hierarchy multiple criteria decision-making (MCDM) model based on fuzzy-sets theory including FAHP and FTOPSIS are applied. The results obtained from AHP, FAHP; FTOPSIS were compared with each other. This research has been conducted on a manufacturing plant however the results can also be used for other types of organizations that are located in a competitive environment. [ABSTRACT FROM AUTHOR]

Abstract: Monitoring the market has crucial roles for executing the shipping investment decisions in maritime transportation industry. The high level of managerial effort requires bringing market tendencies with the up-to-date data over dynamic parameters. This paper extends the Quality Function Deployment (QFD) principles towards shipping investment process via the originally proposed Ship of Quality (SoQ) framework. Furthermore, the Fuzzy Analytic Hierarchy Process (FAHP) and Fuzzy Axiomatic Design (FAD) algorithms are integrated into the SoQ frame in order to involve quantitative outcomes into the shipping investment decisions. The SoQ is performed over a set of periodical data and recent trends of the principal crude oil tanker markets such as Very Large Crude Oil Carriers (VLCCs), Suezmaxes, and Aframaxes in order to ensure the illustrative results. As an effective investment tool, the proposed SoQ model is expected to provide invaluable decision aid for the relevant shipping executives. [Copyright &y& Elsevier]

In Vietnam, as more and more organizations are moving toward globalization, green supplier selection (GSS) has emerged as a strategic approach in supply chain management that requires supplier practices in lessening the environmental risks to society. Based on both conventional and environmental criteria, this paper aims to evaluate a set of suppliers by establishing a multi-criteria decision-making (MCDM)-based framework using an integrated fuzzy analytical hierarchy process (FAHP) with the VIseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method. Initially, five GSS criteria of the environmental aspect (wastewater treatment, solid waste generation, energy consumption, air pollution, corporate social responsibility) and conventional criteria (quality, cost, delivery, and technology) are identified from the literature and consulting field experts to employ the MCDM approach. The trustworthiness of the proposed integrated framework is presented by discussing a case study in the coffee bean supply chain in Vietnam. The FAHP is used to generate criteria weights in which fuzzy set theory is applied to translate the linguistic evaluation statements of experts, and VIKOR is used to rank the alternatives against the selected criteria. From FAHP findings, the most important criteria are quantity discount, solid waste generation, order fulfillment rate, logistics cost, and purchasing cost. A consistency test is performed to ensure the uniformity of the expert's input. The best suppliers are determined through the final ranking of the VIKOR model for the case study. The work presented provides insight to decision-makers of supplier selection that helps determine significant GSS criteria and aids in the minimization of environmental risks to society arising from the supply chain on corporate sustainability standards. [ABSTRACT FROM AUTHOR]

Choosing a supplier is a complex decision-making process that can reduce the total cost of production inputs and increase profits without increasing the price or sacrificing product quality. However, supplier selection processes usually involve multiple quantitative and qualitative criteria which increase the complexity of the problem and may decrease the accuracy and effectiveness of the process. Such complex decision-making problems can be supported by using multicriteria decision-making (MCDM) models. While there have been multiple MCDM models to support supplier selection processes in different industries and sectors, only a few are developed to support the supplier selection processes in the garment industry, especially under uncertain decision-making environment. This paper presents an integrated mathematical model under a fuzzy environment and applies it to the supplier selection process in the garment industry. In this research, the authors utilize the Buckley extension based fuzzy Analytical Hierarchical Process (FAHP) method in combination with linear normalization based fuzzy Grey Relational Analysis (F-GRA) method to develop a MCDM approach to the supplier selection process under a fuzzy environment. As a result, supplier 08 (SA08) is the optimal supplier. The contribution of this work is to propose an MCDM model for ranking potential suppliers in the garment industry under a fuzzy environment. The proposed approach can also be applied to support complex decision-making processes under a fuzzy environment in different industries. [ABSTRACT FROM AUTHOR]

• 16 most popular biodiesel feedstocks were analysed for screening the best feedstocks. • 15 economic, technical, environmental, and social criteria were used. • 5 weighting methods (EQUAL, CRITIC, ENTROPY, AHP, and FAHP) have been used. • 4 MCDA processes, namely PROMETHEE GAIA, WSM, WPM, and TOPSIS were implemented. • Soybean was ranked as the worst feedstock and Coconut rated the best performer. The interest in sustainable energy sources such as biodiesel is growing due to unpredictable fossil fuel prices, depletion of their origins, inconsistent supply, geopolitical instability, and conflicts of fuel/oil-producing countries, global politics, and sanctions. The selection of the right biodiesel feedstocks is the first step of mass biodiesel production. This paper is aimed at defining the best possible biodiesel feedstocks using various multiple criteria decision analysis (MCDA) processes. Several facets that can effect on the biodiesel feedstocks selection process are economic, technical, environmental, and social aspects. This study concentrated on fifteen 'criteria' based on the economic aspect (cost of biodiesel production), technical aspects (physicochemical properties and structural composition (fatty acid) of biodiesel feedstocks), and environmental aspects (sustainable land usage for crop production) for the selection process. Sixteen most popular biodiesel feedstocks, namely Palm, Soybean, Sunflower, Moringa, Jatropha, Pongamia, Mustard, Coconut, Tallow, Peanut, Corn, Cottonseed, Ricebran, Beauty leaf, Rapeseed and waste cooking oil biodiesel were investigated as 'alternatives' in this analysis. For 'weight' determination of each criterion, five weighting methods in percentage, namely EQUAL, CRITIC, ENTROPY, Analytical hierarchical process (AHP), and Fuzzy Analytical Hierarchical Process (FAHP) were used. Four MCDA processes, namely PROMETHEE Graphical Analysis for Interactive Assistance (GAIA), Weighted sum method (WSM), Weighted product method (WPM), and Technique for order preference by similarity to ideal solution (TOPSIS) were implemented for this investigation. The findings indicate that Coconut rated best and Soybean was regarded as the worst feedstock among those alternatives. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

In recent years, the market of textile and garment materials has been volatile, and the ongoing US-China trade war is creating good opportunities for other markets such as Vietnam, Bangladesh and Mexico to continue to expand their market share in the United States. Vietnam is expected to have great advantages thanks to cheap labor cost and strong production capacity. Raw material supplier selection in a volatile competitive environment is crucial for a company to succeed, and supplier selection is a complicate process in which decision-makers must consider multiple quantitative and qualitative features, along with their symmetrical impact, in order to achieve an optimal result. The purpose of selecting the right supplier is to improve competitiveness and product quality, while satisfying customer demand at a minimum production cost. The aim of this paper is to propose a multicriteria decision making model (MCDM) for garment and textile supplier selection. In the first stage, all criteria affecting this process are defined by using the supply chain operations reference model (SCOR) and experts' opinion. Incorporating hybrid fuzzy set theory into the analytical network process (ANP) model is the most effective tool for addressing complex problems of decision-making, which has a connection with various qualitative criteria; thus, the Fuzzy Analytical Hierarchy Process (FAHP) was applied for determining the weight of all potential suppliers, and the preference ranking organization method for enrichment of evaluations (PROMETHEE II) was used for ranking the supplier. The results of this research will assist researchers and decision makers in identifying, adapting and applying appropriate methods to identify the optimal material suppliers in the textile and garment industry. This research can also be used to support supplier selection decisions in other industries. [ABSTRACT FROM AUTHOR]

The period of industrialization and modernization has increased energy demands around the world. As with other countries, the Taiwanese government is trying to increase the proportion of renewable energy, especially solar energy resources. Thus, there are many solar power plants built in Taiwan. One of the most important components of a solar power plant is the solar panel. The solar panel supplier selection process is a complex and multi-faceted decision that can reduce the cost of purchasing equipment and supply this equipment on time. In this research, we propose fuzzy MCDM approach that includes fuzzy analytical hierarchy process model (FAHP) and data envelopment analysis (DEA) for evaluation and selection of solar panel supplier for a photovoltaic system design in Taiwan. The main objective of this work is to design a fuzzy MCDM approach for solar panel supplier selection based on qualitative and quantitative factors. In the first step of this research, FAHP is applied to define the priority of suppliers. The AHP combined with fuzzy logic (FAHP) can be used to rank suppliers; however, the disadvantages of the FAHP model is that input data, expressed in linguistic terms, depends on experience of experts and the number of suppliers is practically limited, because of the number of pairwise comparison matrices. Thus, we applied several DEA models for ranking potential suppliers in the final stages. As the result, decision making unit 1 (DMU 1) is the optimal solar panel supplier for photovoltaic system design in Taiwan. The contribution of this research is a new fuzzy MCDM for supplier selection under fuzzy environment conditions. This paper also lies in the evolution of a new approach that is flexible and practical to the decision maker. It provides a useful guideline for solar panel supplier selection in many countries as well as a guideline for supplier selection in other industries. [ABSTRACT FROM AUTHOR]

The application of multiple criteria decision-making methods (MCDM) is aimed at choosing the best alternative out of the number of available versions in the absence of the apparently dominant alternative. One of the two major components of multiple criteria decision-making methods is represented by the weights of the criteria describing the considered process. The weights of the criteria quantitatively express their significance and influence on the evaluation result. The criterion weights can be subjective, i.e., based on the estimates assigned by the experts, and the so-called objective, i.e., those which assess the structure of the data array at the time of evaluation. Several groups of experts, representing the opinions of various interested parties may take part in the evaluation of criteria. The evaluation data on the criterion weights also depend on the mathematical methods used for calculations and the estimation scales. In determining the objective weights, several methods, assessing various properties or characteristics of the data array’s structure, are usually employed. Therefore, the use of the procedures, improving the accuracy of the evaluation of the weights’ values and the integration of the obtained data into a single value, is often required. The present paper offers a new approach to more accurate evaluation of the criteria weights obtained by using various methods based on the idea of the Bayes hypothesis. The performed investigation shows that the suggested method is symmetrical and does not depend on the fact whether a priori or posterior values of the weights are recalculated. This result is the theoretical basis for practical use of the method of combining the weights obtained by various approaches as the geometric mean of various estimates. The ideas suggested by the authors have been repeatedly used in the investigation for combining the objective weights, for recalculating the criteria weights after obtaining the estimates of other groups of experts and for combining the subjective and the objective weights. The recalculated values of the weights of the criteria are used in the work for evaluating the quality of the distant courses taught to the students. [ABSTRACT FROM AUTHOR]