Acid Orange 7 (AO7) is one of the most common azo dyes; however, its strong bond makes them difficult to biologically degrade. We sought degrade AO7 dye using CeO2 as a promising alternative photocatalyst. powders were synthesized with monoethanolamine (MEA), diethanolamine (DEA), and triethanolamine (TEA) precipitant by solvothermal process combined calcination in air. Compared oxygen storage ...

The problem of finding the longest common subsequence (LCS) for a set of sequences is a very interesting and challenging problem in computer science. This problem is NPcomplete, but because of its importance, many heuristic algorithms have been proposed, such as Long Run algorithm and Expansion algorithm. However, the performance of many current heuristic algorithms deteriorates fast when the n...

In order to evaluate the performance of the enterprise effectively and reasonably, a performance evaluation model is proposed based on optimized DEA algorithm with decision making units. First, a second goal is set on the basis of classic DEA algorithm, and the only public weight is further determined to make the minimizing sum of changes between the efficiency of public weights and the classic...

The performance of the units is defined as the ratio of the weighted sum of outputs to the weighted sum of inputs. These weights can be determined by data envelopment analysis (DEA) models. The inputs and outputs of the related (Decision Making Unit) DMU are assessed by a set of the weights obtained via DEA for each DMU. In addition, the weights are not generally common, but rather, they are ve...

Data envelopment analysis (DEA) is a method for measuring the efficiency of peer decision making units (DMUs). Recently network DEA models been developed to examine the efficiency of DMUs with internal structures. The internal network structures range from a simple two-stage process to a complex system where multiple divisions are linked together with intermediate measures. In general, there ar...

DEA Classic models cannot be used for inaccurate and indeterminate data, and it is supposed that the data for all inputs and outputs are accurate and determinate. However, in real life situations uncertainty is more common. This article attempts to get the common weights for Decision-Making Units by developing DEA multi-objective models in the grey environment. First, we compute the privilege o...

Regulators of electricity distribution networks have typically applied Data Envelopment Analysis (DEA) to cross-section data for benchmarking purposes. However, the use of panel data to analyse the impact of regulatory policies on productivity change over time is less frequent. The main purpose of this paper is to construct a Malmquist productivity index to examine the recent productivity chang...

data envelopment analysis operates as a tool for appraising the relative efficiency of a set of homogenous decision making units. this methodology is applied widely in different contexts. regarding to its logic, dea allows each dmu to take its optimal weight in comparison with other dmus while a similar condition is considered for other units. this feature is a bilabial characteristic which opt...

Data Envelopment Analysis (DEA) is a technique for measuring the efficiency of a set of Decision Making Units (DMUs) with common data, but in general it is not practical. This paper presents a framework where DEA is used to measure overall profit efficiency with fuzzy data. Specifically, it is shown that as the inputs, outputs and price vectors are fuzzy numbers, the DMUs cannot be easily evalu...

It is assumed in the standard DEA model that the aggregate output (input) is a pure linear function of each output (input). This means, for example, that if DMU j1 generates twice as much of an output as does another DMU j2, then the former is credited with having created twice as much value. In many situations, however, linear pricing ðlryrjÞ may not adequately reflect differences in value cre...