supplier selection is a multi-criteria problem. this study proposes a hybrid model for supporting the suppliers’ selection and ranking. this research is a two-stage model designed to fully rank the suppliers where each supplier has multiple inputs and outputs. first, the supplier evaluation problem is formulated by data envelopment analysis (dea), since the regarded decision deals with uncertai...

The Winter Simulation Conference serves as the initial publication venue for many advances in ranking and selection (R&S), including the recently-developed R&S procedures that exploit high-performance parallel computing. We formulate a new stylized model for representing parallel R&S procedures, and we provide an overview of existing R&S procedures under the stylized model. We also discuss why ...

This chapter describes a method of feature selection and ranking based on human expert knowledge and training and testing of a neural network. Being computationally efficient, the method is less sensitive to round-off errors and noise in the data than the traditional methods of feature selection and ranking grounded on the sensitivity analysis. The method may lead to a significant reduction of ...

recently, farzipoor saen [journal of the operational research society, 60(11), 1575–1582 (2009)] proposed a method based on data envelopment analysis to identify optimistic efficient suppliers in the presence of nondiscretionary factors-imprecise data. this short communication aims at showing a computational error in computing the value of preference intensity parameter in farzipoor saen’s [1] ...

In today’s highly rival market, an effective supplier selection process is vital to the success of any manufacturing system. Selecting the appropriate supplier is always a difficult task because suppliers posses varied strengths and weaknesses that necessitate careful evaluations prior to suppliers’ ranking. This is a complex process with many subjective and objective factors to consider ...

The choice of suitable robots in manufacturing, to improve product quality and to increase productivity, is a complicated decision due to the increase in robot manufacturers and configurations. In this article, a novel approach is proposed to choose among alternatives, differently assessed by decision makers on different criteria, to make the final evaluation for decision-making. The approach i...

This paper regards the query keywords selection problem in source retrieval as learning a ranking model to choose the method of keywords extraction over suspicious document segments. Four basic methods are used in our ranking function: BM25, TFIDF, TF and EW. Then, a ranking model based on Ranking SVM is proposed to rank the query keywords group which is contributed to get the higher evaluation...