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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.

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]

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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]

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]