In this article, we , rst survey the relationship between Lozano and Villa's Centralized resource Allocation (CRA) and Mar-Molinero's simpli, ed models. Then, we show how to obtain an opti-mal solution to the CRA model via the simpli, ed model. Moreover, we propose a novel model by simplifying phase II of Lozano and Villa's model. This proposed model determines a peer e, cient unit for each decision making unit (DMU) through some simple computations. The proposed simpli, ed models help us to clarify some ambiguities in the CRA method and propose some solutions to solve them. Considering the importance of target setting in the management, we formulate an-other new model such that by preserving the aim of the CRA model, also projects DMUs onto e, cient frontier according to desirable target as much as possible. The proposed model is illustrated by using a data set of earlier literature.

The performance and resources Allocation in large organizations such as banks, universities, and airports are one of the most important indicators in organizational management science. In this paper, by data envelopment analysis, which is a very powerful method of evaluating the efficiency of organizations, we analyze and review the performance and resource Allocation. The optimal Allocation of resources in organizations is considered to be the most important tool for implementing a long-term strategy and program for them, and the policies and objectives of the organization's plan are reflected in resources Allocation of the activities. Indeed, given the importance of future organizations' performance, managers, taking into account the efficiency of each unit, provide strategies for target setting and how to allocate resources, including human resources, financial costs, technological facilities, and so on. On the other hand, given that actual data in organizations are usually random and stochastic, this paper addresses methods for allocating resources with stochastic data. Also, in line with this research, we will devise strategies for allocating resources as well as confronting limited resources in stochastic data, which will result in a new model for data envelopment analysis. In this model, stochastic data are presented with probability distribution due to probability. One of the most valuable achievements in this paper is to resolve the problem of allocating appropriate and optimal limited resources with stochastic data. Finally, with numerical results, the advantages of the new model are shown in relation to the previous models with stochastic data.

In this article, Centralized resource Allocation (CRA) models based on the value efficiency in DEA and DEA-R are recommended. In general, if the input and output data of decision-making units are available, DEA models provide targets of units on the efficiency frontier in addition to the efficiency of units. However, if only a ratio of the input data to output data, or vice versa, is available, DEA models cannot determine the efficiency and target of units. In order to overcome this problem, DEA-R models are utilized. With a linear programming problem, Centralized resource Allocation models can achieve the projection of all decision-making units on the efficiency frontier. Therefore, in the present article, the projection of inefficient units in DEA and DEA-R is achieved using the CRA models based on the value efficiency (considering units that the manager defines as MPS). Finally, a case study is carried out for clothing companies of a specific brand.

Estimating the efficiency of interdependent parts in a company or evaluating related processes in a production system provides insights to improve production performance. In many real-world scenarios, there are situations where all DMUs fall under a Centralized decision maker that oversees them. This type of situation occurs when all the units belong to an organization (public or private) that provides the necessary resources to achieve the outputs. Network data envelopment analysis (NDEA) is able to consider the operation and interdependence of the processes in the components of a system to measure performance. Recent advances in network data envelopment analysis models enable decision-making units to learn about inefficient processes in the system. In this research, by using Centralized DEA models and NDEA models and according to different approaches regarding the use of intermediate products, standardization for the three-stage supply chain has been discussed. The model presented in this article has been used to evaluate the efficiency of the supply chain of 10 producers of Zamzam Company, and the obtained results have been compared with the deCentralized three-stage network model.

Introduction: Hospitals are regarded as the largest and most expensive operational units of the health system. Also, bed is one of the most valuable hospital resources. Due to the limited resources of the health system, paying attention to efficient resource Allocation is necessary. This study aimed to allocate common beds to hospitals to optimize their overall efficiency. Methods: This is a cross-sectional and applied study. 70 Iranian hospitals affiliated to social security organizations were examined. The required data were collected from the statistical yearbook of this organization (2016). A Centralized data envelopment analysis model with an input-orientation approach was used to assess the performance and bed reAllocation to hospitals. The input data consist of the number of active beds, and the output data consist of bed occupancy rate, average patient stay, and survival of patients in thousand. Hospitals were clustered by k‐ means clustering method for analysis. The data were analyzed by GAMS and SPSS softwares. Results: Hospitals were clustered into 4 groups of homogenous units. Based on this clustering, the number of hospitals in clusters 1 to 4 was 23, 2, 13, 32, and the overall efficiencies of them were 0. 703, 1, 0. 827, and 0. 732, respectively. Before bed reAllocation, 13 (18. 6%) hospitals were efficient. After bed reAllocation by Centralized data envelopment analysis, 31 (44. 3%) hospitals became efficient. Conclusion: It seems that the active bed factor can be one of the inputs influencing the overall efficiency of hospitals. However, in this regard, inclusive attention to other resources such as physicians and nurses will be necessary to achieve desirable hospital efficiency.

Cost efficiency measures the cost of resource by output production. While conventional cost efficiency models set targets separately for each DMU, There are cases where the Central decision making is seeking the above targets, and at the same tries to obtain the target of Min cost efficiency for the total consumption. In this paper we consider that there is a Centralized decision maker (DM). In such case, the DM has an interest in minimizing the cost efficiency of individual units at the same time it wants that total input consumption is reduced or output production is increase. We proposed new Centralized resource cost efficiency model measurement on the base of Farrell cost efficiency model and Centralized resource Allocation of Lozano and Villa model that will reduce resource Allocation total cost efficiency, however it is possible for some inputs to increase. The preferences and advantages of this model are present some examples.

This paper investigates the Centralized resource Allocation objects using cost, profit and revenue. In this case, the decision maker wants to resource Allocation with minimal total cost and maximal total profit. Indeed, in this case by using the minimal input and/or maximal output of all of units the Centralized resource Allocation with minimal cost and maximal profit and revenue in the presence of variable and uncertain prices in data envelopment analysis (DEA) is done. Then, the projection of the decision making units (DMUs) on cost and profit frontiers are determined. Also, the Centralized resource Allocation models with the minimal cost in the presence of uncertain prices in the cases of optimistic and pessimistic are proposed. As can be seen, the Centralized resource Allocation objects using the total cost and the total profit and revenue decreases (increases) the total cost (profit). Finally, using some examples the proposed models are investigated.