This paper propose a semi supervised clustering model TPC-IRBM(Two phase clustering-Integrated rule based model) for clustering large data set such as gene expression data. TPC-IRBM works in two phases to cluster the gene expression data set. The proposed model is based on rule based models CRT,C5,CHAID and QUEST. In the first phase of the model 30 % data(which may vary) is extracted to prepare...

Management performance measurement is a complex task since multiple inputs and multiple outputs are involved in the process. This study attempted to develop a comprehensive framework to encompass the basic concepts of Balance Scorecard (BSC) and data envelope analysis (DEA) to measure the management performance. BSC and DEA are complemental to each other. On one hand, BSC can provide appropriat...

Data envelopment analysis (DEA) mainly utilizes envelopment technology to replace production function in microeconomics. The input and output of decision making units (DMUs) are projected into the attributes to evaluate or measure their performance. However, if the inputs and outputs are linguistically termed or are fuzzy-numbered, conventional DEA can not easily measure the performance. Theref...

In original data envelopment analysis (DEA) models, the data for all inputs and outputs are known exactly. When some inputs and outputs are unknown decision variables, such as interval data, ordinal data, and ratio bounded data, the DEA model is called imprecise DEA (IDEA). In this paper, We develop an alternative approach based upon slacksbased measure of efficiency (SBM) for dealing with inte...

Dissociative electron attachment (DEA) is the major process where molecules are destroyed in low-energy plasmas. DEA cross sections are therefore important for a whole variety of applications but are both hard to measure or compute accurately. A method for estimating DEA cross sections based a simple resonance plus survival model is presented. Test results are presented for DEA of molecular oxy...

Operator allocation is one of the most important decisions that can influence productivity in the laborintensive manufacturing system. In this paper 10 operator allocation alternatives are identified with the assistance of computer simulation. To determine the best operator allocation, AHP/DEA and DEA Cross Efficiency are used. The results of both techniques are compared. Based on the results, ...

Data Envelopment Analysis (DEA) is a linear programming based technique that was developed to evaluate relative efficiency of nonprofit and public sector Decision Making Units (DMU's) that use multiple inputs to produce multiple outputs. In this study, DEA is evaluated and tested for use as a managerial audit tool to identify and measure inefficiencies among a set of DI'IU's. Based on three app...

Supplier selection problem (SSP) is a problem to select the best among suppliers based on input and output data of the suppliers. Since different uncontrollable and unpredictable parameters are affecting selection, choosing the best supplier is a complicated process. Data Envelopment Analysis (DEA) is a method for measuring efficiency and inefficiencies of Decision Making Units (DMUs). While, t...

This study proposes the Data Envelopment Analysis (DEA) ranking for resource allocation between Iran's Medical Universities based on a five years observation data (2004-2008). We compared the DEA ranking results with the traditional ranking approach applied by the Ministry of Health and Medical Education of Iran. Based on the DEA score the amount of budget is proposed for each university for th...

Data Envelopment Analysis models are based on linear programming problems (LPP) to determine the efficiency of Decision-Making Units (DMUs). This process can be computationally intense, as a LPP has to be run for each unit. Besides, a typical DEA LPP has a large number of redundant constraints concerning the inefficient DMUs. That results in degenerate LPPs and in some cases multiple efficient ...