One of the drawbacks of Data Envelopment Analysis (DEA) is the problem of lack of discrimination among efficient Decision Making Units (DMUs). A method for removing this difficulty is called changing reference set proposed by Jahanshahloo and et.al (2007). The method has some drawbacks. In this paper a modified method and new method to overcome this problems are suggested. The main advantage of...

this article will address the extension of super efficiency method to rank the non-extreme efficient decision making units. many methodologies have introduced methods that can rank efficient units, amongst which, the super efficiency method due to its ability to provide meaningful geometrical as well as economic analyses has a significant place. but the common problem with all the super efficie...

today’s world economy situation forces enterprise organizations toward more soft and flexible organization, management, and production processes. they need to explore the most suitable knowledge management (km) tool not only to identify gaps and overlaps but also to maintain and support innovation cross organizations. in this study, a multiple-experts-multiple-criteria decision making model is ...

this paper uses integrated data envelopment analysis (dea) models to rank all extreme and non-extreme efficient decision making units (dmus) and then applies integrated dea ranking method as a criterion to modify genetic algorithm (ga) for finding pareto optimal solutions of a multi objective programming (mop) problem. the researchers have used ranking method as a shortcut way to modify ga to d...

in models of data envelopment analysis (dea), an optimal set of input and output weights is generally as-sumed to represent the assessed decision making unit (dmu) in the best light in comparison to all the other dmus. these sets of weights are, typically, different for each of the participating dmus. thus, it is important to find a common set of weights (csw) across the set of dmus. in this pa...