We address the problem of the statistical analysis of a time series generated by complex dynamics with the diffusion entropy analysis (DEA) [N. Scafetta, P. Hamilton, and P. Grigolini, Fractals 9, 193 (2001)]. This method is based on the evaluation of the Shannon entropy of the diffusion process generated by the time series imagined as a physical source of fluctuations, rather than on the measu...

Data Envelopment Analysis (DEA) requires that the data for all inputs and outputs are known exactly. When some outputs and inputs are known decision variables, such as interval data and ordinal data, the DEA models becomes a nonlinear programming problem and is called imprecise DEA (IDEA). When data assume to be interval, decision making units (DMUs) can divide to three classes as follows: (I) ...

Abstract—Multi-component data envelopment analysis (MCDEA) is a popular technique for measuring aggregate performance of the decision making units (DMUs) along with their components. However, the conventional MC-DEA is limited to crisp input and output data which may not always be available in exact form. In real life problems, data may be imprecise or fuzzy. Therefore, in this paper, we propos...

Data Envelopment Analysis (DEA) is a technique used to compare efficiency in various sectors such as hospitals, chain stores, and dealerships. It represents a set of linear programming techniques and uses deter-ministic data (inputs and outputs), in stable conditions. The DEA technique cannot be used when there is data with indeterministic nature, or when there is an environment with dynamic co...

Data Envelopment Analysis (DEA) is a mathematical programming formulation based technique that provides an efficient frontier to suggest an estimate of the relative efficiency of each decision making unit (DMU) in a problem set. DEA is developed around the concept of evaluating the efficiency of a decision alternative based on its performance of creating outputs in means of input consumption. B...

This paper presents a technique for comparing the results of different assembly line balancing strategies by using Data Envelopment Analysis (DEA). Initially, several heuristics— which can be thought of as assembly line balancing strategies—were used to solve seven line-balancing problems. The resulting line balance solutions provided two pieces of information that were of particular interest: ...

Abstract: Performance measurement has received significant interest during the present industrial scenario. Researchers are emphasizing the development of newer exotic cutting edge tools and more effective methods that can be applied to solve organisational problems. Data Envelopment Analysis (DEA) model measure the efficiencies of a set of homogenous systems or decision making units (DMUs) by ...

Marketing has a tradition in conducting scientific research with cutting-edge techniques developed in management science, such as data envelopment analysis (DEA) (Charnes et al. 1985). Two decades ago, Kamakura, Ratchford, and Agrawal (1988) applied DEA to examine market efficiency and consumer welfare loss. In this review of three new books, my purpose is (1) to provide a background of DEA for...

BACKGROUND Based upon serology, >10 canine blood group systems have been reported. OBJECTIVE We surveyed dogs for dog erythrocyte antigen (DEA) 1 and 2 new blood types (Kai 1 and Kai 2), and some samples also were screened for Dal and DEA 3, 4, and 7. METHODS Blood samples provided by owners, breeders, animal blood banks, and clinical laboratories were typed for DEA 1 by an immunochromatogr...

In this paper, a new technique is proposed to optimize the conflicting parameters like low value of maximum side lobe level (SLL), narrow beam-width of the main beam and low value of maximum sideband radiation level (SRL) of time-modulated linear antenna arrays (TMLAAs). The method is based on minimizing a multi-objective fitness function by using single-objective differential evolution algorit...