Background: Determining the impact of executive dysfunction on reading defects in children with reading and learning disabilities can tremenddously help their treatment. In the recent decade, the role of executive functions has been considered very important and fundamental; following those considerations, therefore, the aim of this study is to determine the relationship between executive functions and problems with reading in children with specific learning disorders.
Recent studies on multivariate control charts are based on Hotelling's T 2 control chart. Due to the fact that the Bayesian control charts in a univariate can be effective on performance of control charts, this paper has proposed the multivariate Bayesian control chart based on economic and economic-statistical design. As finding distribution of Bayesian statistic is too difficult, the Monte Carlo method has been employed in order to determine design optimum parameters (sample size, sampling interval and control limit). Also, artificial bee colony (ABC) algorithm has been applied to search for the optimal design parameters. Ultimately, the performance of the proposed control chart and Hotelling's T 2 were compared for more in-depth investigation.
Due to the proper performance of Bayesian control chart in detecting process shifts, it recently has become the subject of interest. It has been proved that on Bayesian and traditional control charts, the economic and statistical performances of the variable sampling interval (VSI) scheme are superior to those of the fixed ratio sampling (FRS) strategy in detecting small to moderate shifts. This paper studies the VSI multivariate Bayesian control chart based on economic and economic-statistical designs. Since finding the distribution of Bayesian statistic is t complicated, we apply Monte Carlo method and we employ artificial bee colony (ABC) algorithm to obtain the optimal design parameters (sample size, sampling intervals, warning limit and control limit). In the end, this case study is compared with VSI Hotelling’s T2 control chart and it is shown that this approach is more desirable statistically and economically.
Supply chain management (SCM) has recently received considerable attention in business management literature. Many companies consider a well-designed SCM and implement it to their systems to increase the performance of production systems. Supplier selection is a fundamental aspect of SCM, which heavily contributes to the overall supply chain performance. SCM is a complicated decision-making problem including both quantitative and qualitative factors. In this paper, we try to determine criteria, indicated by experts for selection of suitable suppliers. The proposed study obtains weight of each criterion by Fuzzy Linear Goal Programming (FLGP) technique. We rank the suppliers by Fuzzy Quality Function Deployment (FQFD) method. The study is executed for a PETROCHEMICAL Co. to evaluate and select the best suppliers.
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