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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]

Orientation is increasingly in demand, especially today in the age of digital and recent technologies, with the disappearance of some jobs and the emergence of others, and with the variety of choices in front of the students who have led professionals to seek a new method and digital solution to help them solve these issues and achieve their personal and professional success. There are a lot of institutions and associations that are organized orientation sessions for students and try to fill the gaps in that area, but it is always a poor fit in the face of a lot of students. And to make an effective decision related to guidance, we need to consider several factors such as grades, preferences, interests, and personality characteristics... which gives a sharp vision of the student and helps to know which category he belongs to. The purpose of this paper is to present a review of studies on distinctive approaches used in the orientation field such as the K-Nearest-Neighbor Method (KNN), Naïve Bayes, Fuzzy logic, Fuzzy Analytic Hierarchy Process (FAHP), and the Internet of things (IoT) in order to discover the best approach which helps students to pick and succeed in their orientation. [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]

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]

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: In order to make the urban green electricity power a scientific, systematic and intuitive evaluation system, this paper briefly introduces the content and significance of green electricity, the research background, guidance significance and considerations of Strategic Environmental Assessment (SEA), the content and relationship between related factors of DPSIR framework model, the construction and correction of fuzzy complementary matrix and fuzzy consistent matrix. This paper applies the DPSIR framework model of Strategic Environmental Assessment to the evaluation of urban green electricity power. Based on applying fuzzy analytic hierarchy process (FAHP) method to determine the weight of each factor, this paper first establishes a more comprehensive and operational indicators evaluation system of urban green electricity power. [Copyright &y& Elsevier]

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]

This paper presents the multi-objective optimization in injection molding. The aim of this study is to determine the best alternative for the best moldability index and better alternatives which are close to the best alternative for an injected part in injection molding technology. Consideration of Taguchi and fuzzy analytic hierarchy process (FAHP) with technique for the order performance by its similarity to the ideal solution (TOPSIS) offers an efficient use approach to evaluate different objectives. Three common defects which reduce the final quality of the injected parts are short shot possibility, shrinkage rate and warpage. The selected material for injection is polypropylene. L18 orthogonal array of Taguchi is selected and for gaining accurate results, Finite Element Analysis (FEA) is applied. To validate the simulation result, the experiment is carried out for two circular flat plates with thickness of 1 mm. Finally, the highest moldability index is related to trial 2 for both simulation and experimental results. This study outcome shows instead of having one trial number which has the highest moldability index, there are 10 trial numbers with high moldability index between 0.6–1 for simulation results and 5 trial numbers with high moldability index between 0.6–1 for experimental results. It is clear, by using Taguchi with TOPSIS and FAHP if the best alternative is not possible to maintain, there are other alternatives which are very close to the best alternative with high moldability index. The main advantage of the proposed method is to increase the number of alternatives which in turn increases the moldability of the final product in injection molding. [ABSTRACT FROM AUTHOR]

Mobile terminals are often in the dynamic environment of heterogeneous networks. For some reasons, they need to switch between different networks, namely vertical handover. At this moment, it is a very crucial issue for the mobile terminal to select the best suitable one rapidly from all detected alternative networks on condition that the selection result can avoid the ping-pong effect as much as possible. This paper proposes a heterogeneous network selection algorithm based on the combination of network attribute and user preference. Taking full account of user preferences for each candidate network and the actual situation of heterogeneous networks, the algorithm combines three typical MADM methods, namely FAHP, Entropy and TOPSIS. We first use FAHP to calculate the subjective weights of network attributes and the subjective utility values of all alternatives for four typical traffic classes, and then use Entropy and TOPSIS to respectively get the objective weights of network attributes and the objective utility values of all alternatives. Finally, according to the comprehensive utility value of every candidate network and a threshold, the most appropriate network, whose comprehensive utility value is maximum and greater than the corresponding value of the current network of the mobile terminal, is selected to access. The proposed algorithm not only avoids the one-sided nature of a single algorithm, but also dynamically adjusts the proportion of each algorithm in the final result according to the actual requirements. Simulation results indicate that the proposed algorithm can accurately select the optimal access network, significantly reduce the number of vertical handovers and provide the required QoS and QoE in terms of the quantified benefit from vertical handoff, compared with three existing hybrid algorithms. [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]

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]

Robots with vastly different capabilities and specifications are available for a wide range of applications. Selection of a robot for a specific application has become more complicated due to increase in the complexity, advanced features and facilities that are continuously being incorporated into the robots by different manufacturers. The aim of this paper is to present an integrated approach for the optimal selection of robots by considering both objective and subjective criteria. The approach utilizes Fuzzy Delphi Method (FDM), Fuzzy Analytical Hierarchical Process (FAHP), Fuzzy modified TOPSIS or Fuzzy VIKOR and Brown–Gibson model for robot selection. FDM is used to select the list of important objective and subjective criteria based on the decision makers’ opinion. Fuzzy AHP method is then used to find out the weight of each criterion (both objective and subjective). Fuzzy modified TOPSIS or Fuzzy VIKOR method is then used to rank the alternatives based on objective and subjective factors. The rankings obtained are used to calculate the robot selection index based on Brown–Gibson model. The proposed methodology is illustrated with a case study related to selection of robot for teaching purpose. It is found that the highest ranked alternative based on Fuzzy VIKOR is closest to the ideal solution. [ABSTRACT FROM AUTHOR]

Most previous research studies on the general factors related to the adoption of mobile services have used multiple regression methods (the technology acceptance mode or structural equation modeling) and some have used MCDM tools. However, these studies still have some shortcomings, so they cannot provide the enough precise information about these factors and their weightings. This information is needed by firms so that they can allocate their limited resources to the most important factors and draw appropriate strategies to improve the content and quality of their mobile services. This study reviewed the literature and constructed a three-layer hierarchical table of the factors that affect consumers' adoption of mobile services. A pair-wise questionnaire was then designed and distributed to managers who are familiar with the mobile services of Chunghwa Telecom, a leading telecommunication company. From the data collected, the weight of each factor was directly calculated, using the fuzzy analytic hierarchy process (FAHP). The paper analyzes the importance of factors and three implications are also discussed. Hopefully, this knowledge will enable firms to better utilize their limited resources, by devising management strategies based on the weights of these factors, and therefore, to meet consumer demand at lower cost and with greater efficiency. [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]

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: Enterprise’ immune system can help enterprise prevent and eliminate enterprises’ viruses so that enterprises continuously adapt to the environment. This paper uses immunology theory and artificial immune engineering theory, on the basis of previous research, to discuss enterprise immunity, and build evaluation index system of enterprise immunity. Then, we bring out an Evaluation Model of enterprise immunity based on D-S Evidence Theory. FAHP is used to structure and rate the criteria. The information from multiple data sources is combined using Dempstere-Shafer evidence theory. We illustrate our approach by application on the evaluation of Enterprise Immunity. [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]

Our paper determines the best competitive strategy that can be implemented by existing and potential air cargo carriers in the Turkish Air Cargo Industry with the operationalization of Istanbul Airport (IGA) and reveals the competitiveness level of the industry for four bases. We look at the competitiveness levels by analyzing the competitive environment of the industry nationally and internationally both before and post IGA (estimated). We use fuzzy TOPSIS (FTOPSIS) based on the Fuzzy AHP (FAHP) to handle vagueness, which is inherent in the nature of new competition conditions integrating the framework of Porter's five forces analysis. In our study, we use the five forces as our main criteria (with a total of 19 sub-criteria) and the competitive strategies as our alternatives. Our results reveal that the cost-focused strategy is the best competitive strategy that can be implemented by existing and potential carriers in the industry. Another significant result underscores the fact that IGA increases the competitiveness level of the Turkish Air Cargo Industry both nationally and internationally to a fairly high level. Also, the threat of potential competitors is first among the five forces in the industry's new conditions. Our study fills the gap in the literature on the effects of major structural changes in an air cargo industry on the competition among carriers. • The study determines the best competition strategy that can be implemented by carriers. • The study reveals the competitiveness level of Turkish air cargo industry before and post IGA. • The study uses FTOPSIS based on FAHP (FAHP) integrating the framework of Porter's five forces. • The results reveal that the cost-focused strategy is the best competitive strategy. • IGA increases the competitiveness level of the industry to fairly high level. [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]