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A reasonable strategy is the key to control stocks in the random inventory system. Yet it is difficulty to design such strategy by analytical method because of the randomness of variables and complex and nonlinear relationship among them. This paper provides a random inventory model with no filling the missing. The model generates the random variables subjected to the distribution of requirement and arrival delay firstly based on Monte Carlo theory, and then utilizes the strategy of (s, S) to change the lower and upper order points, and takes the ordering point and ordering quantities as input variables, the total inventory costs as output variables. By simulation with computer and exhaustive method, it seeks the global optimal strategy. Simulation method presented in the paper avoids the affects of the randomness of variables, which is an effective method to solve random system problems.

The topography can be very important for passive microwave remote sensing of soil moisture due to its complex influence on the emitted brightness temperature observed by a satellite microwave radiometer. In this study, a methodology of using the first brightness Stokes parameter (i.e., the sum of vertical and horizontal polarization brightness temperature) observed by the Soil Moisture and Ocean Salinity (SMOS) was proposed to improve the soil moisture retrieval under complex topographic conditions. The applicability of the proposed method is validated using in-situ soil moisture measurements collected at four networks (Pali, Naqu, Maqu and Wudaoliang) on the Qinghai-Tibetan Plateau. The results over Pali, which is a typical mountainous area, showed that soil moisture retrievals using the first brightness Stokes parameter are in better agreement with the in-situ measurements (the correlation coefficient R >0.75 and unbiased root mean square error < 0.04 m 3 /m 3 ) compared with that using the single-polarization brightness temperature. At the other three networks with relatively flatter terrains, soil moisture retrievals using the first brightness Stokes parameter are found to be comparable to the single-polarization retrievals. On the contrary, the maximum bias of the retrieved soil moisture caused by topographic effects exceeds 0.1 m 3 /m 3 when using vertical or horizontal polarization alone, which is far beyond the expected accuracy (0.04 m 3 /m 3 ) of SMOS satellite. In the regions on the Qinghai-Tibetan Plateau where the vegetation effect can be ignored, soil moisture retrieved using horizontal polarization brightness temperature is generally underestimated, overestimated when using vertical polarization brightness temperature. It is reasonable due to the polarization rotation effect (depolarization) caused by the topographic effects. It is concluded that the proposed method for soil moisture retrieval