This paper proposes the macro model and micro model for the efficiency evaluation of data warehouses (DWH), and introduces Fuzzy Data Envelopment Analysis (FDEA) and Data Envelopment Analysis (DEA) to comprehensively assess DWH efficiency. FDEA can determine the efficiencies of data warehouses with multiple input / output variables, and also resolve the problem that standard DEA cannot handle w...

Data envelopment analysis (DEA) is a non-parametric technique to measure the efficiencies of a set of decision making units (DMUs) with common crisp inputs and outputs. In real-world problems, however, inputs and outputs typically have some levels of fuzziness. To analyze a DMU with fuzzy input/output data, previous studies provided the fuzzy DEA (FDEA) model and proposed an associated evaluati...

This study consists of three types of vendor selection models in supply chains and presents a decision making scheme for choosing appropriate method for supplier selection under certainty, uncertainty and probabilistic conditions. These models are, Data Envelopment Analysis (DEA), Fuzzy Data Envelopment Analysis (FDEA), and Chance Constraint Data Envelopment Analysis (CCDEA). In FDEA model we u...

This study examined the energy use pattern of poultry for egg production farms of Iran and ranked the selected farmers using fuzzy data envelopment analysis (FDEA) from the viewpoint of energy efficiency. Since data used in our study were not measured precisely, fuzzy forms of them could help us to reach the ideal situations. Hence, the conventional data envelopment analysis (DEA) was remod...

Data envelopment analysis (DEA) is a methodology for measuring the relative efficiencies of a set of decision making units (DMUs) that use multiple inputs to produce multiple outputs. Crisp input and output data are fundamentally indispensable in conventional DEA. However, the observed values of the input and output data in real-world problems are sometimes imprecise or vague. Many researchers ...

in this paper, by introducing two virtual decision-making units (dmus) called ideal dmu (idmu) and anti-ideal dmu (admu) with fuzzy inputs-outputs, the efficiency evaluation of dmus are done by fuzzy data envelopment analysis (fdea). therefore, we evaluate dmus from the perspective of the best and worst possible relative efficiency. for each dmu two efficiencies are calculated while inputs and ...

This paper presents a Genetic Algorithm Fuzzy Data Envelopment Analysis (GA-FDEA) model that caters for optimal selecting of economic indicators for the measurement of relative productivity and performance of financial institutions. Imprecise or uncertain data of financial institutions due to varying monetary policies and market risk were retrieved from Nigeria Stock Exchange Commission and eva...

This study intends to expand a set of proper performance evaluation indices which embraces strategies for sustaining top performance using SWOT analysis inside a balanced scorecard (BSC) outline for the large commercial bank branches in IRAN by operating a fuzzy Data Envelopment Analysis (FDEA). Through literature reviews and the banks’ experts and managers opinions and who have real practical ...

In this paper, by introducing two virtual decision-making units (DMUs) called ideal DMU (IDMU) and anti-ideal DMU (ADMU) with fuzzy inputs-outputs, the efficiency evaluation of DMUs are done by fuzzy data envelopment analysis (FDEA). Therefore, we evaluate DMUs from the perspective of the best and worst possible relative efficiency. For each DMU two efficiencies are calculated while inputs and ...