Constrained multi-item inventory system with variable demands are considered. The demand rates of five selected - Cowbell, Milo, SMA, Cerelac and Golden Morn were modeled as Weibull, Normal Lognormal probability distributions respectively the aid chi-squared multinomial goodness-of-fit test. respective estimated location parameters: 491.55, 536.92, 10.5, 2.1926 5.3103 used basis probabilistic m...

Money demand determinants vary in every economy. There are many studies about Iran money demand function, which employed different variables and estimation methods. In this study, broad money (M2) is dependent variable and GDP, interest rate, exchange rate and household religious costs are descriptive variables. Household religious costs (urban and rural) are included in Iran money demand funct...

Market demand of the  perishable bakery  products are volatile. Hence, demand of such items are random variable. The most appealing demand distribution of such items is lognormal demand distribution. Using historical data, the parameters of lognormal distribution are obtained. But, there is a problem of overestimation or underestimation of the parameters. Fuzzy triangular numbers are used to ov...

Aggregate production planning (APP) determines the optimal production plan for the medium term planning horizon. The purpose of the APP is effective utilization of existing capacities through facing the fluctuations in demand. Recently, fuzzy approaches have been applied for APP focusing on vague nature of cost parameters. Considering the importance of coping with customer demand in different p...

nowadays, electricity is one of the most significant infrastructures required for economic development of countries. hence, predicting electricity demand is very important especially in industry as a major electricity-consuming sector. the majority of studies under the subject of electricity demand have been performed by econometrics and it is not possible to investigate the effect of different...

The grey system theory, which has been extensively used in many areas, is appropriate for forecasting. It is necessary to put forward new models or algorithms to improve its performance, especially for forecast accuracy. In the forecast process of grey model, the size of data sample and the number of variables can affect forecast accuracy. In this paper, we first put forward a new method to cho...