Assem A. Tharwat

Developing a Stochastic Input Oriented Data Envelopment Analysis (SIODEA) Model

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.

Modifications of Particle Swarm Optimization Techniques and Its Application on Stock Market: A Survey

Particle Swarm Optimization (PSO) has become popular choice for solving complex and intricate problems which are otherwise difficult to solve by traditional methods. The usage of the Particle Swarm Optimization technique in coping with Portfolio Selection problems is the most important applications of PSO to predict the stocks that have maximum profit with minimum risk, using some common indicators that give advice of buy and sell. This paper gives the reader the state of the art of the various modifications of the PSO and study whether had been applied over the stock market or not.

A particle swarm optimization algorithm for the continuous absolute p-center location problem with Euclidean distance

The p-center location problem is concerned with determining the location of p centers in a plane/space to serve n demand points having fixed locations. The continuous absolute p-center location problem attempts to locate facilities anywhere in a space/plane with Euclidean distance. The continuous Euclidean p-center location problem seeks to locate p facilities so that the maximum Euclidean distance to a set of n demand points is minimized. A particle swarm optimization (PSO) algorithm previously advised for the solution of the absolute p-center problem on a network has been extended to solve the absolute p-center problem on space/plan with Euclidean distance. In this paper we develop a PSO algorithm for the continuous absolute p-center location problem to minimize the maximum Euclidean distance from each customer to his/her nearest facility, called “PSO-ED”. This problem is proven to be NP-hard. We tested the proposed algorithm “PSO-ED” on a set of 2D and 3D problems and compared the results with a branch and bound algorithm. The numerical experiments show that PSO-ED algorithm can solve optimally location problems with Euclidean distance including up to 1,904,711 points.

Performance Evaluation of European Football Teams Using Data Envelopment Analysis

Todays competition has become intense not only in business but also in sports. Football is considered one of the most popular sports in the world over the last few decades and highly influential to the global sports industry. In this paper we evaluated the performance of fifty football European teams who have played in the Europa League and/or Champions League in the 2014/15 season while considering their performance in their respective national leagues. The data envelopment analysis (DEA) technique was adopted for this evaluation. DEA is a nonparametric method in operations research used to measure the relative efficiency of comparable institutions and also used for benchmarking in operations management. The analyses revealed that most teams were efficient when considering their performance in both the domestic and international leagues, while a smaller portion of these teams were efficient at the international level only.

Investigating Growth Indicators for Insurance Companies in UAE before recession (Comparative Study)

Insurance Companies provide coverage in the form of compensation resulting from loss, damages, injury, treatment or hardship in exchange for premium payments. Insurance as an industry involves pooling funds from many insured entities (known as exposures) to pay for the losses that some may incur. Insurance as a financial intermediary is a commercial enterprise and a major part of the financial services industry. The Growth of insurance companies usually measured through certain Indicators such as the increment percentage in: net profit, total premium written, shareholders equity, total assets, net underwriting income, and net investment. Insurance industry established in UAE at early 70th of the last century (the first insurance company was El Sharjah Company which established at 1970). Now (after almost 40 years) there are more than sixty insurance companies playing a crucial role in both the UAE financial market and society. In this article the net profit, and total premium written growth indicators will be investigated for a selected group of insurance companies in UAE. Using the descriptive statistical tools, the graphical presentations and the control chart, a comparative study is performed among the selected group of insurance company based on the discussed indicators to evaluate their financial performance during the period of study.