this paper estimates the determinants of inflation in iran using a linear and non- linear regression model over the period 1959-2008. in the model specification, the conventional variables (liquidity, production and exchange rate) as well as positive and negative oil revenue shocks, monetary disequilibrium, and demand gap are considered. the results show that nonlinear time series regression mo...

This paper examined the efficiency of multivariate linear regression (MLR) and artificial neural network (ANN) models in prediction of two major water quality parameters in a wastewater treatment plant. Biochemical oxygen demand (BOD) and chemical oxygen demand (COD) as well as indirect indicators of organic matters are representative parameters for sewer water quality. Performance of the ANN m...

In this paper, an purchasing inventory model for deteriorating items is developed with a linear, positive trend in demand, allowing inventory shortages and backlogging. It is assumed that the goods in the inventory deteriorate over time at a constant rate . Two models are developed for two operational policies. The first policy covers the case that the inventory model with linear demand for det...

Classical deterministic inventory models consider the demand rate to be either constant or time-dependent but independent from the stock status. However, for a certain type of inventory, the demand rate may be in-fluenced by the stock level. Also in many real-life problems, some products such as fruits, vegetables, phar-maceuticals and volatile liquids continuously deteriorate to evaporation, o...

responsibility in demand networks is one of the most important measures of performance. the concept of agility and flexibility in service and production. variety and changes in demand need more flexible network design that can cope with potential shortage and delay. this paper presents new mathematical model to optimize the design of demand network when there are highly variable demands. it als...