metal price is one of the most important parameters in the calculation of cut-off grade. The cut-off grade has the main role in determination of mine layout. Mine layout actuates mineable reserve, mine life and economic profitability. Not considering the uncertainty in metal prices can lead to a non-optimal layout. In this paper optimum underground mine layout is determined by expected utility theory with regard to metal price uncertainty. With the proposed approach metal price uncertainty is modeled by Monte Carlo simulation technique and decision maker will be gained probability of underground mine layouts. The utility function of underground mine layouts is defined and by the probability of them, expected utility is determined. Underground mine layout with the maximum expected utility is the optimum layout. Application of this approach in a hypothetical gold mine, in addition to considering metal price uncertainty, leads to 14% more mineable reserve and 18% higher net present value than normal design.

the relationship between the price of oil and the level of economic activity is a fundamental empirical issue in macroeconomics. In this research, by using a multivariate GARCH-in-Mean VAR, we try to investigate direct effects of uncertainty of oil price on macroeconomics of Iran by using annually data from 1965 to 2013. Results show that uncertainty about oil prices had a negative and significant effect on real output in our sample.

In this paper, a new revenue efficiency data envelopment analysis (RE-DEA) approach is considered for finding the most revenue efficient unit with price uncertainty in both optimistic and pessimistic perspectives. The optimistic and pessimistic perspectives use efficient frontier and inefficient frontier, respectively. An integrated model is introduced to find decision making units (DMUs) that can be a candidate for most revenue efficient unit, in both optimistic and pessimistic points. Consequently, the revenue efficiency of all DMUs is calculated with by solving one model. Then a mix integer programming (MIP) model is proposed for finding the most revenue efficient DMU with common set of weights. The proposed model ensures that just one unit has been revenue efficiency. To illustrate the applicability of the new approach, the model is utilized for data from 21 medical centers in Taiwan.

The process of increases global oil and food prices in recent years is concerned economists to examine the relationship between these variables. The main objective of this paper is to determine the impact of oil price on food prices index during the period 1990-2011 under uncertainty condition. For this purpose, first based on Alghalit (2010) empirical study and microeconomic foundations, the model has been designed between oil and food prices under uncertainty condition for Iranian Economy. Then, coefficients of this model are estimated by using the nonlinear least squares (NLS) econometric approach. The results indicated a positive but few impact of expected crude oil prices and it's uncertainty on the expected food price index that can be result the payment of government subsidies to the energy sector. So that with increase (decrease) 10 units (dollar) in the expected price of crude oil and its volatility, increases (decreases) the expected food price index respectively about 1.4 and 0.8 unit. According to the other results, with increase in supply and export of crude oil, expected food prices are decrease.

In restructured power systems, generation companies should offer a power - price curve to the market operator to participate the auction. The proposed bidding curve has a considerable impact on the unit profit, especially in pay as bid markets. The optimal bidding curve depends on the final market clearing price which is uncertain in the stage of bidding. This paper proposes a novel approach for optimal bidding strategy considering the probabilistic nature of forecasted market clearing price. Numerical examples show satisfactory results in comparison with previous approaches.