Data Envelopment Analysis (DEA) as a non-parametric method for efficiency measurement allows decision making units (DMUs) to select the most advantageous weight factors in order to maximize their efficiency scores.  In most practical applications of DEA presented in the literature, the presented models assume that all inputs are fully desirable. However, in many real situations undesirable inpu...

Data envelopment analysis (DEA), which is used to determine the efficiency of a decision-making unit (DMU), is able to recognize the amount of input congestion. Moreover, the relative importance of inputs and outputs can be incorporated into DEA models by weight restrictions. These restrictions or a priori weights are introduced by the decision maker and lead to changes in models and efficiency...

Risk early-warning of natural disasters is a very intricate non-deterministic prediction, and it was difficult to resolve the conflicts and incompatibility of the risk structure. Risk early-warning factors of natural disasters were differentiated into essential attributes and external characters, and its workflow mode was established on risk early-warning structure with integrated Entropy and D...

Data Envelopment Analysis (DEA) is a powerful tool for measuring the relative efficiency for a set of Decision Making Units (DMUs) that transform multiple inputs into multiple outputs. In centralized decisionmaking systems, management normally imposes common resource constraints to maximize operating revenues and minimize operating expenses. In this study, we propose an alternative DEA model fo...

The basic DEA model experiences the weights flexibility problem which is resolved by the method of weight restrictions. The current research incorporating Decision Makers’ (DMs) preferences into weight restrictions is subject to serious limitations such as lacking a framework for dual role factors and not incorporating organizational hierarchy in decision-making. The proposed Genetic Algorithm ...

We provide an alternative framework for solving Data Envelopment Analysis (DEA) models which, in comparison with the standard Linear Programming (LP) based approach that solves one LP for each Decision Making Unit (DMU), delivers much more information. By projecting out all the variables which are common to all LP runs, we obtain a formula into which we can substitute the inputs and outputs of ...

Ranking alternatives is an important issue in multiple criteria decision analysis (MCDA); especially that different approaches produce different results. This paper proposes a measure of relative distance, which involves the calculation of the relative position of an alternative between the anti-ideal and the ideal for ranking. In this case, minimizing the distance to the ideal is equivalent to...

The inherent elasticity of dielectric elastomer actuators (DEAs) gives this technology great potential in energy efficient locomotion applications. In this work, a modular double cone DEA is developed with reduced manufacturing and maintenance time costs. This actuator can lift 45 g of mass (5 times its own weight) while producing a stroke of 10.4 mm (23.6% its height). The contribution of the ...

Abstract The objective of this work is to use multiple Data Envelopment Analysis (DEA)/Benefit the Doubt (BoD) approaches for readjustment and exploitation Human Development Index (HDI). HDI leading indicator vision “development as freedom”; it a Composite Index, wherein three dimensions (income, health, education), represented by four indicators, are aggregated. DEA-BoD used in were: tradition...