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Aiming at the fuzzification of a decision environment and the challenge of determining the weights associated with the interaction among decision-makers, this study offers an original method for (p,q)-rung probabilistic hesitant orthopair fuzzy multi-objective group decision-making, which is founded on the weight optimization principle. Firstly, the notion of a probabilistic hesitant fuzzy set is expanded to a (p,q)-rung. Secondly, the determination of subjective and objective weights is accomplished through the utilization of the Analytic Network Process (ANP) and the Entropy Method. According to the degree of deviation and dispersion of each weight, an optimal objective function is constructed, and the neural network is used to iteratively solve for the best scheme of the comprehensive weight. Subsequently, the Elimination Et Choice Translating Reality (ELECTRE) approach was refined and applied to decision-making in the (p,q)-rung probabilistic hesitant orthopair fuzzy environment. Finally, comparative analysis was used to demonstrate the new method's effectiveness and superiority. [ABSTRACT FROM AUTHOR]

We employ the DEMATEL-based analytic network process (D-ANP) to evaluate the weight of various factors on S&P 500 index futures. The general regression method is employed to prove the result. We then employed grey relational analysis (GRA) to examine predictive power of determinants suggested by 13 experts for fluctuations in S&P 500 index futures. This study yields a number of empirical results. (1) The explanatory power of macroeconomic factors for S&P 500 index futures outperforms that of technical indicators, as found in most of previous research papers; (2) The D-ANP revealed that five core factors (US dollar index, ISM manufacturing purchasing managers' index (PMI), interest rate, volatility index, and unemployment rate) affect fluctuations in S&P 500 index futures, of which the US dollar index is the most important; (3) A casual diagram shows that the US dollar index and interest rate have mutual effects, and the US dollar index unilaterally affects ISM manufacturing PMI, unemployment rate, and the volatility index; (4) Granger causality test results confirmed some similar results obtained via the D-ANP that the US dollar index, interest rate, and the PMI have major impacts on the S&P 500 index futures; (5) The general regression results confirmed that four of five factors selected via the D-ANP (US dollar index, interest rate, volatility index, and unemployment rate) have strong explanatory power in forecasting the rate of return on S&P 500 index futures; (6) The GRA revealed that the explanatory power of various factors selected via the D-ANP was better for S&P 500 than for Dow Jones Industrial Average (DJIA) and Nasdaq 100 index futures; (7) The explanatory power is better for S&P 500 Industrial than for S&P 500 transportation, utility, and financial index futures. [ABSTRACT FROM AUTHOR]

Finding reliable partners is the key to supply chain management. However, the symmetrical evaluation of enterprise trust is complex, so the decision-makers must understand its quantitative and qualitative characteristics in order to realize a reasonable evaluation. Based on the analysis of the causes and influencing factors of supply chain trust, this paper constructed four primary indexes and 16 secondary indexes to define enterprise trust, and used analytic network process (ANP) to evaluate and rank the indicators. Then, the paper constructed a supply chain directed weighted trust evolution network model based on complex network theory, integrated trust into the network with edge weights, and put forward the merit index of comprehensive node degree, weight, and efficiency to study the supply chain network evolution. The simulation results show that the node degree distribution in the trust evolution network conforms to the power-law distribution rule, and the trust evolution model of the complex network has obvious scale-free characteristics, which effectively avoid the situation that the node influence is too high due to the excessive strength of a single index. At the same time, it can quickly evaluate the node influence of the directed weighted complex network, and provide certain practical value for the node trust prediction of the supply chain network. [ABSTRACT FROM AUTHOR]

This Special Issue covers symmetric and asymmetric data that occur in real-life problems. We invited authors to submit their theoretical or experimental research to present engineering and economic problem solution models that deal with symmetry or asymmetry of different data types. The Special Issue gained interest in the research community and received many submissions. After rigorous scientific evaluation by editors and reviewers, seventeen papers were accepted and published. The authors proposed different solution models, mainly covering uncertain data in multi-criteria decision-making problems as complex tools to balance the symmetry between goals, risks, and constraints to cope with the complicated problems in engineering or management. Therefore, we invite researchers interested in the topics to read the papers provided in the Special Issue. [ABSTRACT FROM AUTHOR]

λ 0 -measure is a special type of fuzzy measure. In the context of multi-attribute decision making (MADM), the measure can be used together with Choquet integral to model the interdependencies that usually present between the decision attributes. Unfortunately, the range of techniques available to estimate λ 0 -measure values is too limited i.e., only four techniques are available to this date. Besides, the review on literature shows that each of these existing techniques either requires some initial data from the decision-makers or misrepresents the actual interdependencies held by the attributes. Thus, an alternate unsupervised technique is needed for the estimation of λ 0 -measure values. This study has developed such a technique by integrating the idea of distance correlation and Shannon entropy. In this technique, the two inputs required to estimate λ 0 -measure values, namely, the interdependence degrees and fuzzy densities are determined by utilizing the distance correlation measures and entropy weights, respectively. An evaluation to rank the websites owned by five different hospitals located in Sabah, Malaysia, was conducted to illustrate the usage of the technique. A similar evaluation was also performed with a few selected MADM techniques for comparison purposes, where the proposed technique is found to have produced the most consistent ranking. From the literature perspective, this study has contributed an alternate unsupervised technique that can estimate λ 0 -measure values without necessitating any additional data from the decision-makers, and at the same time can better capture the interdependencies held by the attributes. [ABSTRACT FROM AUTHOR]

Reliability-Centred Maintenance (RCM) is a strategic process to improve the maintenance planning of companies which contributes to sustainable production. This method has been applied by numerous industries to achieve an efficient maintenance process, but many have not fully completed their goals. The reason for this failure is that RCM implementation is complex, and organisations need to have adequate preparations before they implement it. In the pre-implementation phase, it is necessary to know the number of Critical Success Factors (CSFs) as a critical measure for implementing the RCM method successfully. Therefore, it is important for practitioners to apply a symmetric mechanism involving fuzzy systems to achieve the desired RCM implementation. There are a limited number of studies that have observed these factors regarding the characteristics of oil and gas companies, especially in the pre-implementation phase. Addressing RCM pre-implementation issues is of high importance from the economic perspective of sustainability for oil and gas organisations. The objective of this study is to investigate significant items in RCM pre-implementation through a combination of quantitative and qualitative analyses. The Nominal Group Technique (NGT) method is applied by gaining the opinion of experts to determine the factors and prioritising them using mathematical modelling. A group of related experts from the oil and gas industry were initially interviewed and surveyed to determine the critical success factors. These identified factors were then analysed using quantitative analysis to identify the important degrees and scored using Fuzzy Analytic Network Process (FANP). Fifteen major factors affecting the criticality of successful RCM implementation have been identified and prioritised, based on their weights. The model proposed in this study could be used as a guideline for assessing CSFs in other countries. To apply the proposed model in different contexts, it needs to be modified according to the needs, policies, and perspectives of each country. [ABSTRACT FROM AUTHOR]

Under the double pressure of global energy consumption and climate change, nuclear power has become a low-carbon alternative energy source that could transform the energy structure of the globe. In the nuclear power industry, selecting suitable suppliers plays a significant role in improving the overall performance of nuclear power projects. Along with this symmetrical impact, this paper aims to develop a multistage decision-support framework to determine the optimal nuclear power equipment supplier, which is constructed in the context of Z-number information. Concretely, the Analytic Network Process (ANP) and Tomada de Decisão Iterativa Multicritério (TODIM) are extended by Z-numbers symmetrically—namely, Z-ANP and Z-TODIM. Z-ANP is first applied to analyze the symmetrical interdependence of criteria, so as to accurately determine the criterion weights. Further, the ranking of alternatives is obtained by Z-TODIM, which sufficiently considers the risk preference and psychological states of decision-makers. Finally, a practical case of nuclear-grade cable procurement in the Karachi 2-3 international nuclear power project is performed to illustrate the practicality of the proposed method, and its robustness and superiority are proven by comparing it with current representative approaches. [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]

The development of the regional economy cannot be separated from the support of regional logistics, as the scientific decisions of regional logistics are helpful to promote the healthy development of the regional economy. The comprehensive evaluation of regional logistics competitiveness is the premise and foundation of regional logistics scientific decision-making; the evaluation index system, evaluation data, and index weight are the key links affecting a comprehensive evaluation. In order to improve the quality of a comprehensive evaluation, the study aims at addressing problems such as the evaluation index system of regional logistics competitiveness being complex and scattered, the normalized distribution of the evaluation data being extremely asymmetric and seriously deviating from the normal distribution, and the logic of calculating index weights by the analytic hierarchy process (AHP) not being accurate. To do this, a triangle model of regional logistics competitiveness is constructed based on Porter's diamond model, and the evaluation index system of regional logistics competitiveness is refined from the three dimensions of resource supply, logistics service, and market demand. Based on the concept of symmetry theory, a normalization method of segmental mapping with quartiles as multiple reference points is proposed, which improves the distribution rationality, symmetry, and distance discrimination of normalized data. The dynamic index scale is used to determine the scale of the analytic hierarchy process, and the evaluation matrix is constructed based on the importance level grading table; the index weights are directly solved without a consistency check, which improves the logical accuracy of a subjective evaluation. Based on the data of segment mapping, the comprehensive evaluation value of the evaluation object is calculated, and the competitiveness of regional logistics is compared and ranked, which improves the differentiation and consistency of the results. Through the comparative analysis of the calculation results, it was proven that the improvement of the data standardization method is necessary when the range is too large. The method in this paper can make the distribution of data standardization with a range too large closer to the normal distribution. It was found that the ranking of regional logistics competitiveness is highly consistent with the total social logistics, and that the total amount of regional logistics has an important reference value for the competitiveness of regional logistics. The ranking calculated by the indicators and methods in this paper has a certain reference value for regional logistics decision-making. [ABSTRACT FROM AUTHOR]

When solving a Multi-Criteria Decision-Making problem of any degree of complexity, many researchers rely on the analytic hierarchy process (AHP). To consider mutual connections between criteria and clusters at the same level and not only the hierarchical structure between criteria and subcriteria, researchers often upgrade from AHP to the Analytic Network Process (ANP), which also examines the interdependency of criteria. However, the ANP method requires a large number of pairwise comparisons. In the case of a complex decision-making problem, the authors of this paper suggest upgrading the AHP method with the graph theory and matrix approach (GTMA) for several reasons: (1) The new method is based on digraphs and permanent value computation, which does not require a hypothesis about interdependency; (2) in case of similar alternatives, the distinguishable coefficient of the new method is higher than those computed for AHP and ANP; (3) the new method allows decision makers to rank comparable alternatives and to combine structurally similar methods without increasing the number of comparisons and the understanding of the results. The developed method (AH-GTMA) is validated by a numerical example of a complex decision-making problem based on a symmetrical set of similar alternatives, a third party logistic provider (3PLP) selection problem. [ABSTRACT FROM AUTHOR]

Increasing the number of threats against software vulnerabilities and rapidly growing data breaches have become a key concern for both the IT industry and stakeholders. Developing secure software systems when there is a high demand for software products from individuals as well as the organizations is in itself a big challenge for the designers and developers. Meanwhile, adopting traditional and informal learnings to address security issues of software products has made it easier for cyber-criminals to expose software vulnerabilities. Hence, it is imperative for the security practitioners to employ a symmetric mechanism so as to achieve the desired level of software security. In this context, a decision-making approach is the most symmetrical technique to assess the security of software in security tactics perspective. Since the security tactics directly address the quality attribute concerns, this symmetric approach will be highly effective in making the software systems more secure. In this study, the authors have selected three main attributes and fifteen sub-attributes at level 1 and level 2, respectively, with ten different software of an institute as alternatives. Furthermore, this study uses a fuzzy-based symmetrical decision-making approach to assess the security of software with respect to tactics. Fuzzy Analytic Network Process (F-ANP) is applied to evaluate the weights of criteria and fuzzy-Symmetrical technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is used to determine impact of alternatives. The proposed symmetrical assessment in this study will be beneficial for both the designers and developers to categorize and prioritize the security attributes and understand the importance of security tactics during software development life cycle. [ABSTRACT FROM AUTHOR]

Acceptance of any new approach by the organizations depends upon the users' needs. Currently, reducing the cost and time invested in maintenance is a major challenge for the practitioners. Moreover, symmetrical and optimal maintenance is the need of the hour and it can be achieved by increasing the durability of software. Many attributes of the quality may affect the durability of the software and identification of durability attributes is a crucial task at the early stage of software development. Thus, it is a problem that contains multi-criteria within it. With the help of quantitative estimation, software durability may be assessed symmetrically and increased. In this row, the authors of this article have attempted to posit an effective technique to assess the durability of software. Based on empirical data through research, the presenters of this article suggest that fuzzy-based symmetrical method of Analytic Network Process (ANP) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) would be an accurate methodology for assessing the durability of software. For determining the efficacy of this assessment, the researchers took six alternative software of a University. The results, as presented in this paper, would serve as guidelines for the practitioners who aim at achieving the preferred software durability. [ABSTRACT FROM AUTHOR]

Selecting suppliers plays an important role in improving efficiency of supply chains. In the field of extraction of vegetable oil, one of the main submaterials is hexane solvent. Choosing a supplier of hexane solvent is a multicriteria decision-making task that decision-makers must have an understanding of the quantitative and qualitative elements for assessing the symmetrical impact of the criteria to reach the most accurate result. In this paper, the authors suggest a multicriteria decision-making (MCDM) model for N-hexane solvent (C6H14) supplier evaluation and selection for vegetable oil production. All criteria affecting to the hexane solvent supplier evaluation and selection process are defined by experts. Then, a fuzzy analytic hierarchy process (FAHP) multicriteria comparative analysis method has been applied for determining the weight of all criteria. Finally, the technique for order of preference by similarity to ideal solution (TOPSIS) was applied to select the optimal hexane solvent supplier. As a result, decision making unit 003 (DMU3) is the optimal supplier. The contribution of this research is to propose an MCDM model for hexane solvent supplier selection in the food industry. The work also proposed a useful guideline for supplier evaluation and selection processes in other industries. [ABSTRACT FROM AUTHOR]

The paper proposes a problem-solving approach in the area of underground mining, related to the evaluation and selection of the optimal mining method, employing fuzzy multiple-criteria optimization. The application of fuzzy logic to decision-making in multiple-criteria optimization is particularly useful in cases where not enough information is available about a given system, and where expert knowledge and experience are an important aspect. With a straightforward objective, multiple-criteria decision-making is used to rank various mining methods relative to a set of criteria and to select the optimal solution. The considered mining methods represent possible alternatives. In addition, various criteria and subcriteria that influence the selection of the best available solution are defined and analyzed. The final decision concerning the selection of the optimal mining method is made based on mathematical optimization calculations. The paper demonstrates the proposed approach as applied in a case study. [ABSTRACT FROM AUTHOR]

The selection of the optimal variety show hosts is a key to television stations. However, no study has a deal with this issue. In this paper, a hybrid multiple criteria decision-making (MCDM) model based on the fuzzy Delphi method, decision-making trial and evaluation laboratory (DEMATEL), analytic network process (ANP), and technique for order preference by similarity to ideal solution (TOPSIS) to choose optimal hosts of variety shows for television stations in the social media era was developed. The fuzzy Delphi method was taken as a screening tool for the selection criteria of variety show hosts. Then, DEMATEL was applied to verify the interdependencies between the perspectives. According to the interdependencies, ANP was employed to obtain weights. Finally, TOPSIS ranked the alternatives. The selection criteria were gathered from previous researches and discussions with senior executives of television stations. By the fuzzy Delphi method, 12 criteria were identified. Based on the past study and consultations with four senior executives, we classified 12 essential criteria into four perspectives to develop the hierarchy for the variety show host selection. Under the hierarchy base on four perspectives and 12 criteria, managers of television stations could select the optimal variety show hosts more effectively. The usability and efficiency of the proposed model were also considered by a case study. We offered a distinct contribution to the prior studies by providing a model in the variety show host selection field. In the context of social media competition, this study also added the selection criteria from Internet celebrities. [ABSTRACT FROM AUTHOR]

Shunting operation is risky and complex because of the nonlinear coupling effect of personnel, equipment, environment and management, which reflects symmetry, can easily cause shunting derailment accidents. Traditional railway safety risk assessment techniques seldom consider the nonlinear coupling relationships of hazard factors in the shunting process,. The Decision Making Trial and Evaluation Laboratory (DEMATEL) and Analytic Network Process (ANP), which are applicable to the coupling analysis of complex systems, have been used in many areas to overcome this shortcoming. Thus, this paper built a hybrid model, developed by integrating DEMATEL and ANP methodologies, to determine the multifarious interdependencies' relative strengths among the hazard factors and to assess the relative importance of the hazard factors with Super Decision (SD) software. By constructing the "frequency-consequence-vulnerability" three-dimensional risk parameter model, the risk magnitude of shunting derailment could be obtained through risk aggregation process. Finally, the model was applied to the risk assessment of shunting derailment in Huangyangcheng station, the results revealed that this model was effective and efficient, which could yield more reliable and realistic solutions to the shunting safety. [ABSTRACT FROM AUTHOR]

Improving the quality of research information systems is an important goal in the process of improving the performance of research management in Chinese universities. Since the evaluation of information system (IS) quality is a multicriteria decision problem, it is critical to identify the interrelationships among the dimensions and criteria, and decide on the important criteria for proposed improvement strategies. This paper suggests a hybrid multicriteria decision-making (MCDM) model for improving the quality of a research information system. First, a rough method combined with the decision-making trial and evaluation laboratory and analytical network process (rough DANP) model is used to improve the objectivity of expert judgements. Additionally, the rough DANP can be used to construct an influential network relationship map (INRM) between research information system components to derive the criterion weights. The complex proportional assessment of alternatives with rough numbers (COPRAS-R) is applied to evaluate the performance of the research information system. A Chinese university research information system is chosen to illustrate the usefulness of the proposed model. The results show that efficiency, effectiveness, and user frequency have the highest priorities for improvement. Selected management implications based on the actual case study are supplied. [ABSTRACT FROM AUTHOR]

The lack of information on the correlation between root causes and corresponding control criteria in the importance calculation of root causes of design problems results in less accurate determinations of core problems. Based on the interaction between customer needs, bad product parameters, and root causes, a hierarchical representation model of the design problem is established in this paper. A network layer of bad parameters, including various types of correlations, and a control layer, including technical feasibility and cost, are constructed. Then, a method based on the network analytic hierarchy process is proposed to rank the importance of root causes of the design problem and determine the core problems. Finally, a product design process based on the core problem solving is established to assist designers with improving design quality and efficiency. The design for the coolant flow distribution device in the lower chamber of a third-generation pressurized water reactor is employed as an example to demonstrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

The recent boom of various integrated decision-making methods has attracted many researchers to the field. The recent integrated Analytic Network Process and Decision Making Trial and Evaluation Laboratory (ANP–DEMATEL) methods were developed based on crisp numbers and fuzzy numbers. However, these numbers are incapable of dealing with the indeterminant and inconsistent information that exists in real-life problems. This paper proposes improvements to the integrated ANP–DEMATEL method by bringing together the neutrosophic numbers, the ANP method, and the DEMATEL method, which are later abbreviated to NS-DANP. The proposed NS-DANP method can handle the indeterminacy elements in the decision-making environment, as the single-valued neutrosophic numbers are used in the decision analysis. This proposed NS-DANP modification method includes linguistic variables representing the single-valued neutrosophic numbers (SVNNs), and also introduces the single-valued neutrosophic weighted averaging (SVNWA) aggregation operator to aggregate the decision makers' judgments instead of the typical averaging method. The applicability of the proposed method is illustrated by a case study of the coastal erosion problem along the Peninsular Malaysia coastline, where 12 factors were considered. Three experts of coastal erosion from different organizations were invited to elicit their linguistic judgments on the cause–effect of the coastal erosion. The seven-step decision approach was developed to acquire the weightage of each coastal erosion factor. The outcome of this study reveals that coastal development is the riskiest factor toward coastal erosion. The weight of factors and the cause–effect diagram could be very helpful for government and stakeholders to project a better mitigation plan for the coastal erosion problem. Comparative analysis is also provided to check the feasibility of the proposed method. [ABSTRACT FROM AUTHOR]

Manufacturing companies are facing rapid and unanticipated changes in their business environment. Most of these companies need to find new strategies to remain competitive in the market. Therefore, the main purpose of this study is to integrate the Fuzzy Analytical Network Process (ANP) and VIKOR methods to evaluate the green agile factors and sub-factors in the dairy companies in Iran. To find the green agile factors and sub-factors, this study used the expert's opinions and literature review. Data is collected from four dairy companies. The results of this study showed that the most important green agility factors are: trust-based relationship with suppliers, flexible production capacity, versatile workers, compliance with quality standards for a new product, and workers' willingness to learn. In addition, the results indicated that the green agility organization is one of the strategies that help companies to stay in the market. To validate the results, this study used four methods, including TOPSIS, ARAS, EDAS, and MABAC. The necessity of a reaction to the increasing customer choices, environmental concerns, and competitiveness among manufacturers across the globe has engaged the industry to embrace innovative manufacturing strategies. [ABSTRACT FROM AUTHOR]

One of the most significant competitive strategies for organizations is sustainable supply chain management (SSCM). The vital part in the administration of a sustainable supply chain is the sustainable supplier selection, which is a multi-criteria decision-making issue, including many conflicting criteria. The valuation and selection of sustainable suppliers are difficult problems due to vague, inconsistent and imprecise knowledge of decision makers. In the literature on supply chain management for measuring green performance, the requirement for methodological analysis of how sustainable variables affect each other, and how to consider vague, imprecise and inconsistent knowledge, is still unresolved. This research provides an incorporated multi-criteria decision-making procedure for sustainable supplier selection problems (SSSPs). An integrated framework is presented via interval-valued neutrosophic sets to deal with vague, imprecise and inconsistent information that exists usually in real world. The analytic network process (ANP) is employed to calculate weights of selected criteria by considering their interdependencies. For ranking alternatives and avoiding additional comparisons of analytic network processes, the technique for order preference by similarity to ideal solution (TOPSIS) is used. The proposed framework is turned to account for analyzing and selecting the optimal supplier. An actual case study of a dairy company in Egypt is examined within the proposed framework. Comparison with other existing methods is implemented to confirm the effectiveness and efficiency of the proposed approach. [ABSTRACT FROM AUTHOR]

In the market economy, competition is typically due to the difficulty in selecting the most suitable supplier, one that is capable to help a business to develop a profit to the highest value threshold and capable to meet sustainable development features. In addition, this research discusses a wide range of consequences from choosing an effective supplier, including reducing production cost, improving product quality, delivering the product on time, and responding flexibly to customer requirements. Therefore, the activities noted above are able to increase an enterprise’s competitiveness. It can be seen that selecting a supplier is complex in that decision-makers must have an understanding of the qualitative and quantitative features for assessing the symmetrical impact of the criteria to reach the most accurate result. In this research, the multi-criteria group decision-making (MCGDM) approach was proposed to solve supplier selection problems. The authors collected data from 25 potential suppliers, and the four main criteria within contain 15 sub-criteria to define the most effective supplier, which has viewed factors, including financial efficiency guarantee, quality of materials, ability to deliver on time, and the conditioned response to the environment to improve the efficiency of the industry supply chain. Initially, fuzzy analytic network process (ANP) is used to evaluate and rank these criteria, which are able to be utilized to clarify important criteria that directly affect the profitability of the business. Subsequently, data envelopment analysis (DEA) models, including the Charnes Cooper Rhodes model (CCR model), Banker Charnes Cooper model (BCC model), and slacks-based measure model (SBM model), were proposed to rank suppliers. The result of the model has proposed 7/25 suppliers, which have a condition response to the enterprises’ supply requirements. [ABSTRACT FROM AUTHOR]