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Background: Supply chain management (SCM) plays a fundamental role in the progress and success of organizations and has continuously evolved to better adapt to today's complex business environments. Consequently, the issue of supplier evaluation and selection (SES), which is one of the most critical decisions in SCM, has gained special significance and has been examined from various perspectives. The concept of green and resilient (gresilient) SCM has emerged in response to recent concerns about environmentally friendly production and operations, as well as organizations' ability to cope with crises and disasters. In the rapidly growing construction industry, applying gresilient principles can ensure green operations and help overcome future challenges. Methods: This study focuses on gresilient SES in a real-world construction case study, proposing a streamlined FUCOM (S-FUCOM) approach. The proposed method streamlines traditional FUCOM processes to solve decision-making problems in deterministic and uncertain environments. Several numerical examples are provided to illustrate its applicability. Results: the case study results identify air emissions, environmental management systems, and restorative capacity as the most critical gresilient SES criteria. Conclusions: The third supplier emerged as the top performer based on decision-making indicators. Finally, a sensitivity analysis was conducted across 20 scenarios, demonstrating that S-FUCOM is robust and provides stable results. [ABSTRACT FROM AUTHOR]

Hospitals are the most important and costly component of the healthcare system. Therefore, hospital performance evaluation (HPE) is an important issue for the managers of these centres. This paper presents a new approach for HPE that can be used to calculate the efficiency, effectiveness, and productivity of hospitals simultaneously. Efficiency refers to the ratio of inputs and outputs, effectiveness refers to the extent to which outputs align with predetermined goals, and productivity refers to the sum of both efficiency and effectiveness. To this end, a Data Envelopment Analysis (DEA) model is developed to simultaneously measure the efficiency, effectiveness, and productivity (DEA-EEP) of hospitals. DEA is a linear programming technique that in its traditional form, calculates the performance of similar decision-making units (DMUs) that have both inputs and outputs. In this study, the inputs are the number of health workers, the number of other staff, and the number of patient beds; while the outputs are the bed occupancy rate and the bed turnover rate. A target value is set for each output to measure the effectiveness of hospitals. The advantage of the developed model is the ability to provide a solution for non-productive units so that they can improve their performance by changing their inputs and outputs. In the case study, data of 11 hospitals in Tehran were evaluated for a 3-year period. Based on the results, some hospitals experienced an upward trend in the period, but the efficiency, effectiveness, and productivity scores of most hospitals fluctuated and did not have a growing trend. This indicates that although most hospitals sought to improve the quality of their services, they needed to take more serious steps.

Modern technologies have changed human life and created a generation of customers who have different needs compared to the past. Considering Industry 4.0 and its drivers, the implementation of digital banking (DB) has faced various challenges that are caused by emerging trends. Both Industry 4.0 and DB are contemporary concepts, and decision-makers are often faced with uncertainties in their decisions regarding the implementation of DB and its indicators. For this purpose, a novel multi-criteria group decision-making approach has been developed utilizing the best–worst method (BWM) and α-cut analysis as well as trapezoidal fuzzy numbers (TFNs). By reviewing the literature and using experts' opinions, the DB implementation criteria are determined, and considering an uncertain environment, the criteria are prioritized using the proposed method. Then, the available DB models and alternatives are examined based on the decision criteria and the importance of each criterion. This research contributes to the existing literature by identifying and prioritizing the criteria necessary for the successful implementation of DB, taking into account emerging trends and technological advances driven by Industry 4.0. Subsequently, the study prioritizes the prevalent models of DB based on these criteria. This study proposes a decision-support framework for dealing with ambiguity, lack of information, insufficient knowledge, and uncertainty in decision-making. The framework uses TFNs to account for imprecision and doubt in decision-makers' preferences. Additionally, the study presents a fuzzy multi-criteria group decision-making approach that enables a group of experts to arrive at more reliable results. The proposed approach can help improve the quality of decision-making in complex and uncertain situations. The results of this research show that human resources, rules and regulations, and customer satisfaction are the most important criteria for implementing DB. In addition, the open, blockchain, and social banking models are the crucial models that significantly cover the implementation criteria for DB. [ABSTRACT FROM AUTHOR]

The sustainable Supplier Evaluation and Selection and Order Allocation (SSOA) problem has received significant attention in supply chain management due to its potential to enhance a company's performance, improve customer satisfaction, and reduce costs. In this study, an integrated methodology is proposed to address the SSOA problem. The methodology combines multiple techniques to handle the uncertainties associated with supplier evaluation, including a new ranking method based on the concept of Radius of Gyration (ROG) for interval type-2 fuzzy sets. The methodology also incorporates both subjective weights obtained using the Simple Multi-Attribute Rating Technique (SMART) and expert preferences, and objective weights calculated using the Method based on the Removal Effects of Criteria (MEREC) method to determine the weights of evaluation criteria. Some criteria for sustainable development are used to evaluate supplier performance, resulting in type-2 fuzzy sets, which are evaluated using the Weighted Aggregated Sum Product Assessment (WASPAS) method. The ROG-based ranking method is employed to calculate the relative scores of suppliers. Finally, a multi-objective decision-making (MODM) mathematical model is presented to identify suitable suppliers and allocate their order quantities. The methodology is demonstrated in a sustainable SSOA problem and is shown to be efficient and effective, as the ROG-based ranking method allows for more accurate supplier performance evaluation, and the use of the criteria highlights the importance of sustainability in supplier selection and order allocation. The methodology's practicality is further supported by the analysis conducted in this study, which demonstrates the methodology's ability to handle the uncertainties associated with supplier evaluation and selection. The proposed methodology offers a comprehensive approach to the SSOA problem that can effectively handle the uncertainties in supplier evaluation and selection and promote sustainable practices in supply chain management. [ABSTRACT FROM AUTHOR]

Today, most of the issues and challenges faced by managers and decision makers are complex and multifaceted. More clearly, due to the developments of technologies, emerging trends in various industries, competitive markets, and rapid and transformative changes in the business environment, managers and decision makers have faced an uncertain environments and issues that cannot be resolved definitively. The use of multi-criteria decision-making (MCDM) methods as a practical and decision-supporting tool allows managers to examine decision-making issues in various organizations and industries based on various criteria, alternatives, and objectives and make decisions with greater reliability. The use of fuzzy techniques and concepts in MCDM methods and their mathematical relationships makes it possible to consider complexities and uncertainties in decisions related to various issues and it can lead to better and more realistic decisions. In this paper, the simplified best-worst method (SBWM), which is one of the methods based on pairwise comparisons, has been developed using triangular fuzzy numbers (TFNs) to propose a fuzzy extension of SBWM (F-SBWM). Triangular fuzzy numbers in different symmetric and asymmetric forms have widely been used in MCDM approaches and pairwise comparisons. It is noteworthy that symmetric numbers are used when we are using equal division of the domain due to an increased ambiguity and lack of information. The proposed approach as a simplified fuzzy MCDM method helps managers and decision makers in various industries to solve decision-making problems under uncertainty without the need for complex calculations, specialized skills, and software packages. To check the feasibility and applicability of the proposed approach, two numerical examples and a computational experiment with real data are presented, and the results are analyzed and discussed. Furthermore, to check the robustness of the results obtained from the proposed approach, sensitivity analysis and comparison of methods have been performed. [ABSTRACT FROM AUTHOR]

Studies related to transportation planning and development have been in the center of activities of many researchers in the past decades. Road congestions issues, economic problems, health problems and environmental problems are some examples of complex problems that can be caused by urban and public transportation in big cities. Evaluating urban and public transportation systems could help to reach effective solutions to overcome these issues. This article presents a short bibliographic review of some recent studies on Multi-Criteria Decision-Making (MCDM) approaches for evaluating urban and public transportation systems. To this aim, Scopus was chosen as the database for making a search on journal articles. Scopus is trusted by major institutions in the world, and all journals covered in this database are inspected for sufficiently high quality each year. The search was made on the journal articles from 2017 to 2022 (July). The analyses presented in this study show that the Analytic Hierarchy Process (AHP) method is the most used method, which has been applied to different studies in the field of urban and public transportation systems based on MCDM approaches. According to the analysis of the number of articles, Turkey is ranked 1st among different countries, and "Budapest University of Technology and Economics" (Hungary) is 1st in the ranking of institutions. Moreover, most of the articles have been published within the "social sciences" subject area. The recent trend in different studies on urban and public transportation systems shows the importance of using MCDM approaches in this field. Moreover, noticeable employment of fuzzy sets in several studies is a point that can shows the significant role of uncertainty in dealing with this type of problems. [ABSTRACT FROM AUTHOR]

The process of production, consumption, and final disposal of electrical and electronic equipment usually leads to harmful waste to the environment called e-waste. Eliminating and decreasing this type of waste could be considered as an essential goal for many enterprises working toward sustainable management systems. In this paper, we aim at introducing a new methodology for evaluation of sustainable e-waste management scenarios. The evaluation is defined as an MCDM (Multi-Criteria Decision-Making) problem, and the scenarios are the alternatives of the problem that need to be evaluated with respect to several sustainability criteria. An extended fuzzy SECA (Simultaneous Evaluation of Criteria and Alternatives) integrated with SMART (Simple Multi-Attribute Rating Technique), named F-SECA, is proposed to deal with the evaluation process. The α-cut approach is used to consider different levels of uncertainty and obtain interval values for assessment of criteria and alternatives. The proposed methodology helps us to make the evaluation with incorporation of subjective and objective data, opinions of multiple experts and uncertainty of information. We applied the methodology to evaluate sustainable e-waste management scenarios in a case. Through comparative and sensitivity analyses, the paper shows that the proposed methodology is efficient and gives reliable results. [ABSTRACT FROM AUTHOR]

One of the most essential topics for the present and future generations is sustainability. Today, because of threats made by traditional and old manufacturing practices, sustainability has become an essential topic in manufacturing companies. Attaining a sustainable manufacturing process requires making decisions about the strategies of manufacturing. In this paper, a novel integrated model is developed to evaluate sustainable manufacturing strategies. The proposed model is based upon two multi-criteria decision-making (MCDM) methods: WASPAS (Weighted Aggregated Sum Product ASsessment) and SECA (Simultaneous Evaluation of Criteria and Alternatives). Due to the uncertainty of evaluation process, we use interval type-2 fuzzy sets (IT2FSs). An example of evaluating sustainable manufacturing strategies is presented, and a sensitivity analysis is carried out for illustration of the developed approach and validation of it. The findings show the efficiency of the developed model, and based on the considered example, "Eco-efficiency" can be regarded as an effective strategy. [ABSTRACT FROM AUTHOR]

Construction site selection is a complex probleminvolving many alternatives and conflicting criteria with vague and imprecise evaluations. Fuzzymulti-criteria decision-making methods are the most effective tools to obtain optimum solutions under possibilistic uncertainty. In this paper, a novel interval hesitant fuzzy CODAS method is proposed and applied to a residential construction site selection problem. A comparative analysis with ordinary fuzzy CODAS method is applied for validating the proposed method. Also, a sensitivity analysis is conducted for the stability of the ranking results of the interval hesitant fuzzy CODAS method. The results of the analyses demonstrate the effectiveness of our proposed method. [ABSTRACT FROM AUTHOR]

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In the discrete form of multi-criteria decision-making (MCDM) problems, we are usually confronted with a decision-matrix formed from the information of some alternatives on some criteria. In this study, a new method is proposed for simultaneous evaluation of criteria and alternatives (SECA) in an MCDM problem. For making this type of evaluation, a multi-objective non-linear programming model is formulated. The model is based on maximization of the overall performance of alternatives with consideration of the variation information of decision-matrix within and between criteria. The standard deviation is used to measure the within-criterion, and the correlation is utilized to consider the between-criterion variation information. By solving the multi-objective model, we can determine the overall performance scores of alternatives and the objective weights of criteria simultaneously. To validate the proposed method, a numerical example is used, and three analyses are made. Firstly, we analyse the objective weights determined by the method, secondly, the stability of the performance scores and ranking results are examined, and finally, the ranking results of the proposed method are compared with those of some existing MCDM methods. The results of the analyses show that the proposed method is efficient to deal with MCDM problems. [ABSTRACT FROM AUTHOR]

Selection of appropriate subcontractors for outsourcing is very important for the success of construction projects. This can improve the overall quality of projects and promote the qualification and reputation of the main contractors. The evaluation of subcontractors can be made by some experts or decision-makers with respect to some criteria. If this process is done in different time periods, it can be defined as a dynamic multi-criteria group decision-making (MCGDM) problem. In this study, we propose a new fuzzy dynamic MCGDM approach based on the EDAS (Evaluation based on Distance from Average Solution) method for subcontractor evaluation. In the procedure of the proposed approach, the sets of alternatives, criteria and decision-makers can be changed at different time periods. Also, the proposed approach gives more weight to newer decision information for aggregating the overall performance of alternatives. A numerical example is used to illustrate the proposed approach and show the application of it in subcontractor evaluation. The results demonstrate that the proposed approach is efficient and useful in real-world decision-making problems. [ABSTRACT FROM AUTHOR]

In past years, the multi-attribute decision-making (MADM) approaches have been extensively applied by researchers to the supplier evaluation and selection problem. Many of these studies were performed in an uncertain environment described by fuzzy sets. This study provides a review of applications of MADM approaches for evaluation and selection of suppliers in a fuzzy environment. To this aim, a total of 339 publications were examined, including papers in peer-reviewed journals and reputable conferences and also some book chapters over the period of 2001 to 2016. These publications were extracted from many online databases and classified in some categories and subcategories according to the MADM approaches, and then they were analysed based on the frequency of approaches, number of citations, year of publication, country of origin and publishing journals. The results of this study show that the AHP and TOPSIS methods are the most popular approaches. Moreover, China and Taiwan are the top countries in terms of number of publications and number of citations, respectively. The top three journals with highest number of publications were:Expert Systems with Applications,International Journal of Production ResearchandThe International Journal of Advanced Manufacturing Technology. [ABSTRACT FROM PUBLISHER]

Integration of reverse logistics processes into supply chain network design can help to achieve a network that incorporates environmental factors as well as economic factors. In this study, a new integrated approach is proposed to address designing a multi-product, multi-period supply chain network with reverse logistics. The framework of the proposed approach includes green supplier evaluation and a mathematical model in an uncertain environment. To the best of our knowledge, integration of green supplier evaluation into the designing supply chain network with reverse logistics has not been considered in the literature. This integration can help to incorporate experts’ opinions about environmental impact of suppliers in the network design. Minimization of total cost and maximization of total greenness score of purchased raw materials/components are two objectives of the model. The fuzzy EDAS method is used to determine the greenness scores of suppliers. Also, demand of customers and capacity of suppliers are defined using fuzzy numbers and a fuzzy method is used to obtain trade-off solutions. The proposed approach is applied to designing the supply chain network of a home appliance company. The results show that the proposed approach is feasible and efficient to obtain solutions to design the supply chain network. [ABSTRACT FROM AUTHOR]

The assessment of Third-Party Logistics (3PL) provider becomes an important issue for enterprises trying to achieve operational efficiency and customer service improvement as well as capital expenditure and logistics costs reduction. It can be said that evaluation and selection of an appropriate 3PL provider is a kind of Multi-Criteria Decision-Making (MCDM) problem. Uncertainty is an unavoidable part of information in the decision-making process. Interval Type-2 Fuzzy Sets (IT2FSs) are very flexible to model the uncertainty of the MCDM problems. In this study, a new integrated approach based on the CRiteria Importance Through Inter-criteria Correlation (CRITIC) and Weighted Aggregated Sum Product ASsessment (WASPAS) methods is proposed to evaluate 3PL providers with IT2FSs. In the proposed approach, objective weights resulted from the CRITIC method are combined with subjective weights expressed by decision-makers (DMs) to determine more realistic weights for criteria. A computational study is performed to illustrate the proposed approach and the applicability of it. In addition, a sensitivity analysis is carried out using different sets of criteria weights to demonstrate the stability of the proposed approach. The results show the stability of ranking results and prove the efficiency of the proposed approach to handle MCDM problems with IT2FSs. [ABSTRACT FROM AUTHOR]

Evaluation based on Distance from Average Solution (EDAS) is a new multicriteria decision making (MCDM) method, which is based on the distances of alternatives from the average scores of attributes. Classical EDAS has been already extended by using ordinary fuzzy sets in case of vague and incomplete data. In this paper, we propose an interval-valued intuitionistic fuzzy EDAS method, which is based on the data belonging to membership, nonmembership, and hesitance degrees. A sensitivity analysis is also given to show how robust decisions are obtained through the proposed intuitionistic fuzzy EDAS. The proposed intuitionistic fuzzy EDAS method is applied to the evaluation of solid waste disposal site selection alternatives. The comparative and sensitivity analyses are also included. [ABSTRACT FROM PUBLISHER]

The redundancy allocation problem (RAP) has been studied for many different system structures, objective functions, and distribution assumptions. In this paper, we present a problem formulation and a solution methodology to maximize the system steady-state availability and minimize the system cost for the repairable series-parallel system designs. In the proposed approach, the components' time-to-failure (TTF) and time-to-repair (TTR) can follow any distribution such as the Gamma, Normal, Weibull, etc. We estimate an approximation of the steady-state availability of each subsystem in the series-parallel system with an individual meta-model. Design of experiment (DOE), simulation and the stepwise regression are used to build these meta-models. Face centred design, which is a type of central composite design is used to design experiments. According to a max-min approach, obtained meta-models are utilized for modelling the problem alongside the cost function of the system. We use the augmented "-constraint method to reformulate the problem and solve the model. An illustrative example which uses the Gamma distribution for TTF and TTR is explained to represent the performance of the proposed approach. The results of the example show that the proposed approach has a good performance to obtain Pareto (near-Pareto) optimal solutions (system configurations). [ABSTRACT FROM AUTHOR]

An effective way for managing and controlling a large number of inventory items or stock keeping units (SKUs) is the inventory classification. Traditional ABC analysis which based on only a single criterion is commonly used for classification of SKUs. However, we should consider inventory classification as a multi-criteria problem in practice. In this study, a new method of Evaluation based on Distance from Average Solution (EDAS) is introduced for multi-criteria inventory classification (MCIC) problems. In the proposed method, we use positive and negative distances from the average solution for appraising alternatives (SKUs). To represent performance of the proposed method inMCIC problems, we use a common example with 47 SKUs. Comparing the results of the proposed method with some existing methods shows the good performance of it in ABC classification. The proposed method can also be used for multi-criteria decision-making (MCDM) problems. A comparative analysis is also made for showing the validity and stability of the proposed method inMCDMproblems. We compare the proposed method with VIKOR, TOPSIS, SAWand COPRAS methods using an example. Seven sets of criteria weights and Spearman's correlation coefficient are used for this analysis. The results show that the proposed method is stable in different weights and well consistent with the other methods. [ABSTRACT FROM AUTHOR]

Evaluating the life cycle of buildings is a valuable tool for assessing sustainability and analyzing environmental consequences throughout the construction operations of buildings. In this study, in order to determine the importance of building life cycle evaluation indicators, a new combination method was used based on a quantitative-qualitative method (QQM) and a simplified best-worst method (SBWM). The SBWM method was used because it simplifies BWM calculations and does not require solving complex mathematical models. Reducing the time required to perform calculations and eliminating the need for complicated computer software are among the advantages of the proposed method. The QQM method has also been used due to its ability to evaluate quantitative and qualitative criteria simultaneously. The feasibility and applicability of the SBWM were examined using three numerical examples and a case study, and the results were evaluated. The results of the case study showed that the criteria of the estimated cost, comfort level, and basic floor area were, in order, the most important criteria among the others. The results of the numerical examples and the case study showed that the proposed method had a lower total deviation (TD) compared to the basic BWM. Sensitivity analysis results also confirmed that the proposed approach has a high degree of robustness for ranking and weighting criteria. [ABSTRACT FROM AUTHOR]

The weights of criteria in multi-criteria decision-making (MCDM) problems are essential elements that can significantly affect the results. Accordingly, researchers developed and presented several methods to determine criteria weights. Weighting methods could be objective, subjective, and integrated. This study introduces a new method, called MEREC (MEthod based on the Removal Effects of Criteria), to determine criteria' objective weights. This method uses a novel idea for weighting criteria. After systematically introducing the method, we present some computational analyses to confirm the efficiency of the MEREC. Firstly, an illustrative example demonstrates the procedure of the MEREC for calculation of the weights of criteria. Secondly, a comparative analysis is presented through an example for validation of the introduced method's results. Additionally, we perform a simulation-based analysis to verify the reliability of MEREC and the stability of its results. The data of the MCDM problems generated for making this analysis follow a prevalent symmetric distribution (normal distribution). We compare the results of the MEREC with some other objective weighting methods in this analysis, and the analysis of means (ANOM) for variances shows the stability of its results. The conducted analyses demonstrate that the MEREC is efficient to determine objective weights of criteria. [ABSTRACT FROM AUTHOR]

The construction industry is an important industry because of its effects on different aspects of human life experiences and circumstances. Environmental concerns have been considered in designing and planning processes of construction supply chains in the recent past. One of the most crucial problems in managing supply chains is the process of evaluation and selection of green suppliers. This process can be categorized as a multi-criteria decision-making (MCDM) problem. The aim of this study is to propose a novel and efficient methodology for evaluation of green construction suppliers with uncertain information. The framework of the proposed methodology is based on weighted aggregated sum product assessment (WASPAS) and the simple multi-attribute rating technique (SMART), and Fermatean fuzzy sets (FFSs) are used to deal with uncertainty of information. The methodology was applied to a green supplier evaluation and selection in the construction industry. Fifteen suppliers were chosen to be evaluated with respect to seven criteria including "estimated cost", "delivery efficiency", "product flexibility", "reputation and management level", "eco-design", and "green image pollution". Sensitivity and comparative analyses were also conducted to assess the efficiency and validity of the proposed methodology. The analyses showed that the results of the proposed methodology were stable and also congruent with those of some existing methods. [ABSTRACT FROM AUTHOR]

Determination of subjective weights, which are based on the opinions and preferences of decision-makers, is one of the most important matters in the process of multi-criteria decision-making (MCDM). Step-wise Weight Assessment Ratio Analysis (SWARA) is an efficient method for obtaining the subjective weights of criteria in the MCDM problems. On the other hand, decision-makers may express their opinions with a degree of uncertainty. Using the symmetric interval type-2 fuzzy sets enables us to not only capture the uncertainty of information flexibly but also to perform computations simply. In this paper, we propose an extended SWARA method with symmetric interval type-2 fuzzy sets to determine the weights of criteria based on the opinions of a group of decision-makers. The weights determined by the proposed approach involve the uncertainty of decision-makers’ preferences and the symmetric form of the weights makes them more interpretable. To show the procedure of the proposed approach, it is used to determine the importance of intellectual capital dimensions and components in a company. The results show that the proposed approach is efficient in determining the subjective weights of criteria and capturing the uncertainty of information. [ABSTRACT FROM AUTHOR]