El-Demerdash, B. E., I. A. El-Khodary, and A. A. Tharwat., "An Algorithm for Evaluating the Performance of Higher Education Organizations in Egypt: Using a Stochastic DEA", The 8th International Conference on Data Envelopment Analysis, DEA2010, Beirut, Lebanon, June, 2010. Abstract

Data Envelopment Analysis (DEA) is a powerful quantitative tool that provides a means to obtain useful information about efficiency and performance of firms, organizations, and all sorts of functionally similar, relatively autonomous operating units which named Decision Making Units (DMU). Usually the investigated DMUs are characterized by a vector of multiple inputs and multiple outputs. Education was one of the earliest applications of DEA; it served to test and validate it as a tool for analysis and decision support. Education was an ideal introduction for DEA because it typically deals with comparisons of many similar and autonomous ‘non-profit’ entities described by inputs and outputs. The main concern in this paper is to develop an algorithm to help any educational organization for evaluating their performance, the developed algorithm based on the DEA model and working in a stochastic environment.

El-Demerdash, B. E., I. A. El-Khodary, and A. A. Tharwat, "Performance evaluation for Egyptian’s Computers and Information Faculties: Using a Stochastic Input Oriented Data Envelopment Analysis Model", International Journal of Computer Applications (IJCA), vol. 89, issue 5, pp. 36-42, 2014. Abstractperformance_evaluation_for_egyptians.pdf

Data Envelopment Analysis (DEA) is a great approach used for measuring relative efficiencies and performance of a collection of Decision Making Units (DMUs). These used in the various forms, such as hospitals, universities, air force, banks, courts, business firms, and others, including the performance of countries, regions, etc. One of the earliest applications of DEA called Education. It was an ideal introduction for DEA because it typically deals with comparisons of many similar and autonomous ‘non-profit’ entities described by inputs and outputs. Therefore, education served to test and validate DEA as a tool for analysis and decision support. Recently DEA has been extended to examine the efficiency of Higher Education operations. In this paper, a Stochastic Input Oriented Data Envelopment Analysis (SIODEA) Model is conducted for the comparison of evaluating the relative efficiency scores of Faculties of Computers and Information (FCIs) each with some of inputs are stochastic with normally distributed, recent inputs are deterministic and outputs.

El-Demerdash, B. E., I. A. El-Khodary, and A. A. Tharwat, "Developing a Stochastic Input Oriented Data Envelopment Analysis Model", International Journal of Advanced Computer Science and Applications (IJACSA), vol. 4, issue 4, pp. 40-44, 2013. Abstractdeveloping_a_stochastic_input_oriented_data.pdf

Data Envelopment Analysis (DEA) is a powerful quantitative tool that provides a means to obtain useful information about efficiency and performance of firms, organizations, and all sorts of functionally similar, relatively autonomous operating units, known as Decision Making Units (DMU). Usually the investigated DMUs are characterized by a vector of multiple inputs and multiple outputs. Unfortunately, not all inputs and/or outputs are deterministic; some could be stochastic. The main concern in this paper is to develop an algorithm to help any organization for evaluating their performance given that some inputs are stochastic. The developed algorithm is for a Stochastic Input Oriented Model based on the Chance Constrained Programming, where the stochastic inputs are normally distributed, while the remaining inputs and all outputs are deterministic.