A hybrid analytical network process and fuzzy goal programming for supplier selection: A case study of auto part maker

The aim of this research is to present a hybrid model to select auto part suppliers. The proposed method of this paper uses factor analysis to find the most influencing factors on part maker selection and the results are validated using different statistical tests such as Cronbach's Alpha and Kaiser-Meyer.The hybrid model uses analytical network process to rank different part maker suppliers and fuzzy goal programming to choose the appropriate alternative among various choices. The implementation of the proposed model of this paper is used for a case study of real-world problem and the results are discussed

Applying Rough Set Theory and Grey Theory in Multi-attribute Decision Making Methods for the Evaluation and Selection of ERP Systems

Enterprise resource planning systems by facilitation and integration of organizations’ operations as well as leveraging the organization's operations and business activities has become an important competitive advantage for organizations. Although the appropriate choose of an ERP system can greatly contribute to the success of the organization, inappropriate selection of ERP also can lead to irreparable damages and costs. Therefore, in this study we have tried to use a multi-attribute decision-making model to evaluate and select the most appropriate ERP system. Since decision makers turn to “uncertain preferences” to evaluate the criteria and alternatives, applying Rough Set and the Gray Set theories in the context of multi-attribute decision-making models seems more logical and consistent. The findings indicate that the “total cost” a sub-criteria of product characteristics and “system technical capabilities” a sub-criteria of system requirements are the most significant criteria and the “A6” is the most significant alternative

Are Serum Procalcitonin and Interleukin-1 Beta Suitable Markers for Diagnosis of Acute Pyelonephritis in Children?

Rapid diagnosis of acute pyelonephritis is important because of its association with long-standing complications. This study was conducted to compare the reliability of serum procalcitonin (PCT) and interleukin-1 beta (IL-1β) with conventional laboratory parameters for diagnosis of acute pyelonephritis in children. Seventy nine children with urinary tract infection were divided into two groups based on the result of Tc-99m dimercaptosuccinic acid renal scan: acute pyelonephritis (n=33) and lower UTI (urinary tract infection) (n=46) groups. White blood cell (WBC) count, neutrophil count, erythrocyte sedimentation rate (ESR), serum C-reactive protein (CRP), PCT and IL-1β concentrations of both groups were measured and compared. WBC count, neutrophil count, ESR, serum CRP, PCT and IL-1β concentrations were higher in acute pyelonephritis patients than in the lower UTI group (P<0.05). The sensitivity and specificity of serum PCT and IL-1β for diagnosis of acute pyelonephritis were 31, 84.7% and 27.2, 90% respectively (using a cut-point value of 0.5 ng/ml for PCT and 6.9 pg/ml for IL-1β). The sensitivity of PCT and IL-1β for diagnosis of acute pyelonephritis was less than that of conventional markers such as ESR and CRP. This study revealed that serum PCT and IL-1β are not good biologic markers for differentiating acute pyelonephritis from lower UTI. It seems that conventional inflammatory markers such as ESR and CRP besides the clinical findings are more reliable for the diagnosis of acute pyelonephritis in children