Centralized Limited Resource Allocation in Data Envelopment Analysis with Stochastic Data

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.