Abstract Data Envelopment Analysis (DEA) models give each decision making unit freedom to assign values the input-output weights maximising its efficiency score. However, there is no guarantee that optimal obtained from a DEA model are always positive which poses problem, in both theory and practice. This paper offers new linear programming deal with zero problem without restricting or placing ...

The classification of fuzzy uncertain data is considered one of the most challenging issues in data analysis. In spite of the significance of fuzzy data in mathematical programming, the development of the analytical methods of fuzzy data is slow. Therefore, the current study proposes a new fuzzy data classification method based on fuzzy data envelopment analysis (DEA) which can handle strea...

So far, many types of location models have been developed to find optimal spatial patterns according to different spatial metrics such as cost, coverage and availability.  The initial focus of these models is on the location availability of service providers and demand estimates, and some of these models are within the framework of multi-objective programming models.  After the advent of scienc...

  For efficiency evaluation of some of the Decision Making Units that have uncertain information, Rough Data Envelopment Analysis technique is used, which is derived from rough set theorem and Data Envelopment Analysis (DEA). In some situations rough data alter nonradially. To this end, this paper proposes additive rough–DEA model and illustrates the proposed model by a numerical example.