Abstract: Data Envelopment Analysis (DEA) is a technique for measuring the relative efficiency of Decision Making Units (DMUs) which produce similar products. Measures of both technical efficiency and service effectiveness for storable commodities are essentially the same. However, these measures for non-storable commodities, such as transport services, represent two distinct dimensions and a joint measurement of both or measurement with their impression mutual is necessary to fully capture the overall performance. In this paper, a Mixed Separate Data Envelopment Analysis (MSDEA) approach is introduced to analyze the overall performance of non-storable commodities. Then, the case of ten intercity car companies is described as the application of this novel approach. Moreover, when some observations are fuzzy, the efficiencies and effectiveness become fuzzy as well. For more extension, MSDEA approach with fuzzy observations called Fuzzy Mixed Separate Data Envelopment Analysis (FMSDEA) approach will be presented and illustrated with a numerical example.

Abstract: Performance measurement is an important part of management science and operation research. Data Envelopment Analysis is a powerful analytical tool that has been successfully applied for measuring and benchmarking the relative performance in a wide variety of activities. Data Envelopment Analysis assists decision makers to distinguish efficient and inefficient decision making units in a homogeneous group. Super-efficiency Data Envelopment Analysis models can be used in ranking the performance of efficient decision making units. In this paper, Data Envelopment Analysis is employed to present a mathematical model for evaluating the relative efficiency of gas stations of Iranian Oil products Company. Banker, Charnes and Cooper model is applied to determine the relative efficiency of the stations. Super efficiency model of Andersen and Petersen and Slack Based Measure of Super efficiency ranking method are used to determine the most efficient unit.

Abstract: This paper studies six types of double integrals and uses Maple for verification. The infinite series forms of these double integrals can be obtained using Taylor series expansions and integration term by term theorem. In addition, some examples are used to demonstrate the calculations.

Abstract: The expansion of HIV/ADIS epidemic has now become a burning issue globally. HIV infection has changed from a fatal condition to a manageable chronic illness mainly due to the development of antiretroviral therapy (ART). Even if ART treatment has shown significant clinical importance by meeting the goal of therapy, we are still facing a number of deaths due to certain socio-economic, demographic, behavioral risk and health factors. The aim of this study is for identifying determinant factors for the Survival of HIV/ADIS Infected Patients under the follow-up of antiretroviral therapy (ART) at Boru Meda and Dessie Referral Hospitals and Kombolcha Health Center. The data for this research were collected during the follow-up time from January 1, 2008 to December 31, 2011. Out of a population of HIV-patients who were taking antiretroviral therapy in the hospitals and health center in that period, 654 patients were selected based on simple random sampling technique for this study. The study subjects were people in the age range from 15 to 75 years. The Kaplan-Meier Method was employed to estimate survival; the Cox Proportional Hazards Regression Method was used to identify determinants of survival. After initiation of the antiretroviral treatment, HIV-positive patients the estimate median survival age was found to be 48 months (CI: 2.98-4.97 years). Living rural, order baseline age, not working due to illness, smaller CD4 count, weight, and lymphocyte count, HIV-TB co-infection developing and being in WHO clinical Stage IV were identified as a documented risk factors for shortened the survival experience of the HIV-patients who are in care of ART. The mortality among our patients was comparable to that reported from other low-income countries. Earlier initiation of ART may reduce the high mortality rates observed. Similar studies in the future need to consider predictors in addition to those considered in this study and the clinical advantage of ART that brings improvement on the clinical characteristics in the follow up period.

Abstract: Data envelopment analysis (DEA) is one of the most powerful non-parametric methods to assess the relative efficiency of each Decision making units (DMU’s). Its simplicity in computation and mathematical programming technique attracted many researchers and at the same time DEA is more sensitive to variables considered. It uses multiple inputs and outputs for efficiency analysis but does not provide any guidelines in choosing variables and hence researchers selected their own number of input and output variables using several methods. Usage of all the variables in DEA is not sensible, since irrelevant variables will reduce the efficiency power. Therefore, selection of appropriate or best set of variables for input and output is needed but it’s one of the crucial tasks in DEA. In the present paper, a new approach of selecting appropriate set of variables using genetic algorithm are discussed and applied to Indian banking sector.