Ranking DMUs by ideal points in the presence of fuzzy and ordinal data

Envelopment Analysis (DEA) is a very effective method to evaluate the relative efficiency of decision-making units (DMUs). DEA models divided all DMUs in two categories: efficient and inefficient DMUs, and don't able to discriminant between efficient DMUs. On the other hand, the observed values of the input and output data in real-life problems are sometimes imprecise or vague, such as interval data, ordinal data and fuzzy data. This paper develops a new ranking system under the condition of constant returns to scale (CRS) in the presence of imprecise data, In other words, in this paper, we reformulate the conventional ranking method by ideal point as an imprecise data envelopment analysis (DEA) problem, and propose a novel method for ranking the DMUs when the inputs and outputs are fuzzy and/or ordinal or vary in intervals. For this purpose we convert all data into interval data. In order to convert each fuzzy number into interval data we use the nearest weighted interval approximation of fuzzy numbers by applying the weighting function and also we convert each ordinal data into interval one. By this manner we could convert all data into interval data. The numerical example illustrates the process of ranking all the DMUs in the presence of fuzzy, ordinal and interval data

Spatial distribution of cancer in Kohgilooyeh and Boyerahmad province

Spatial distribution of cancer is one of the powerful tools in epidemiology of cancer. The present study is designed to understand the geographical distribution of most frequent types of cancer in K&B province. Methods: All registered cases of cancer are reviewed and duplicate cases were removed. The data was analyzed using Arcgis software. Results: Of all registered cases, 1273  remained for analysis of which 57% were residences of urban areas. Cities including  Sisakht, Yasuj and Dehdsasht were shown to have highest incidence rates among the Urban areas. Dena, Sepidar and Kohmare Khaleghi had the highest rates among the rural areas in the province. Skin cancer was the most common type of cancer which had the highest rates of incidence in Sisakht and Dehdasht and Dena and Sepidar among urban and rural areas respectively. Conclusion: The distribution of cancer was not even in the province. Attitude and consumption of wild and regional plants are introduced as the potential risk factors for such a spatial distribution of the common cancers I the province. The results of this study could be used for further analytical studies to understand the regional etiology of cancer in the province