157 resultados para Lead times


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We present a generic study of inventory costs in a factory stockroom that supplies component parts to an assembly line. Specifically, we are concerned with the increase in component inventories due to uncertainty in supplier lead-times, and the fact that several different components must be present before assembly can begin. It is assumed that the suppliers of the various components are independent, that the suppliers' operations are in statistical equilibrium, and that the same amount of each type of component is demanded by the assembly line each time a new assembly cycle is scheduled to begin. We use, as a measure of inventory cost, the expected time for which an order of components must be held in the stockroom from the time it is delivered until the time it is consumed by the assembly line. Our work reveals the effects of supplier lead-time variability, the number of different types of components, and their desired service levels, on the inventory cost. In addition, under the assumptions that inventory holding costs and the cost of delaying assembly are linear in time, we study optimal ordering policies and present an interesting characterization that is independent of the supplier lead-time distributions.

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In this paper, we use reinforcement learning (RL) as a tool to study price dynamics in an electronic retail market consisting of two competing sellers, and price sensitive and lead time sensitive customers. Sellers, offering identical products, compete on price to satisfy stochastically arriving demands (customers), and follow standard inventory control and replenishment policies to manage their inventories. In such a generalized setting, RL techniques have not previously been applied. We consider two representative cases: 1) no information case, were none of the sellers has any information about customer queue levels, inventory levels, or prices at the competitors; and 2) partial information case, where every seller has information about the customer queue levels and inventory levels of the competitors. Sellers employ automated pricing agents, or pricebots, which use RL-based pricing algorithms to reset the prices at random intervals based on factors such as number of back orders, inventory levels, and replenishment lead times, with the objective of maximizing discounted cumulative profit. In the no information case, we show that a seller who uses Q-learning outperforms a seller who uses derivative following (DF). In the partial information case, we model the problem as a Markovian game and use actor-critic based RL to learn dynamic prices. We believe our approach to solving these problems is a new and promising way of setting dynamic prices in multiseller environments with stochastic demands, price sensitive customers, and inventory replenishments.

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This study uses the European Centre for Medium-Range Weather Forecasts (ECMWF) model-generated high-resolution 10-day-long predictions for the Year of Tropical Convection (YOTC) 2008. Precipitation forecast skills of the model over the tropics are evaluated against the Tropical Rainfall Measuring Mission (TRMM) estimates. It has been shown that the model was able to capture the monthly to seasonal mean features of tropical convection reasonably. Northward propagation of convective bands over the Bay of Bengal was also forecasted realistically up to 5 days in advance, including the onset phase of the monsoon during the first half of June 2008. However, large errors exist in the daily datasets especially for longer lead times over smaller domains. For shorter lead times (less than 4-5 days), forecast errors are much smaller over the oceans than over land. Moreover, the rate of increase of errors with lead time is rapid over the oceans and is confined to the regions where observed precipitation shows large day-to-day variability. It has been shown that this rapid growth of errors over the oceans is related to the spatial pattern of near-surface air temperature. This is probably due to the one-way air-sea interaction in the atmosphere-only model used for forecasting. While the prescribed surface temperature over the oceans remain realistic at shorter lead times, the pattern and hence the gradient of the surface temperature is not altered with change in atmospheric parameters at longer lead times. It has also been shown that the ECMWF model had considerable difficulties in forecasting very low and very heavy intensity of precipitation over South Asia. The model has too few grids with ``zero'' precipitation and heavy (>40 mm day(-1)) precipitation. On the other hand, drizzle-like precipitation is too frequent in the model compared to that in the TRMM datasets. Further analysis shows that a major source of error in the ECMWF precipitation forecasts is the diurnal cycle over the South Asian monsoon region. The peak intensity of precipitation in the model forecasts over land (ocean) appear about 6 (9) h earlier than that in the observations. Moreover, the amplitude of the diurnal cycle is much higher in the model forecasts compared to that in the TRMM estimates. It has been seen that the phase error of the diurnal cycle increases with forecast lead time. The error in monthly mean 3-hourly precipitation forecasts is about 2-4 times of the error in the daily mean datasets. Thus, effort should be given to improve the phase and amplitude forecast of the diurnal cycle of precipitation from the model.

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Perfect or even mediocre weather predictions over a long period are almost impossible because of the ultimate growth of a small initial error into a significant one. Even though the sensitivity of initial conditions limits the predictability in chaotic systems, an ensemble of prediction from different possible initial conditions and also a prediction algorithm capable of resolving the fine structure of the chaotic attractor can reduce the prediction uncertainty to some extent. All of the traditional chaotic prediction methods in hydrology are based on single optimum initial condition local models which can model the sudden divergence of the trajectories with different local functions. Conceptually, global models are ineffective in modeling the highly unstable structure of the chaotic attractor. This paper focuses on an ensemble prediction approach by reconstructing the phase space using different combinations of chaotic parameters, i.e., embedding dimension and delay time to quantify the uncertainty in initial conditions. The ensemble approach is implemented through a local learning wavelet network model with a global feed-forward neural network structure for the phase space prediction of chaotic streamflow series. Quantification of uncertainties in future predictions are done by creating an ensemble of predictions with wavelet network using a range of plausible embedding dimensions and delay times. The ensemble approach is proved to be 50% more efficient than the single prediction for both local approximation and wavelet network approaches. The wavelet network approach has proved to be 30%-50% more superior to the local approximation approach. Compared to the traditional local approximation approach with single initial condition, the total predictive uncertainty in the streamflow is reduced when modeled with ensemble wavelet networks for different lead times. Localization property of wavelets, utilizing different dilation and translation parameters, helps in capturing most of the statistical properties of the observed data. The need for taking into account all plausible initial conditions and also bringing together the characteristics of both local and global approaches to model the unstable yet ordered chaotic attractor of a hydrologic series is clearly demonstrated.

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In recent times antiferroelectric thin-film material compositions have been identified as one of the most significant thin films for development of devices such as high charge storage, charge couplers/decouplers, and high strain microelectromechanical systems. Thus, understanding the dielectric and electrical properties under an ac signal drive in these antiferroelectric thin-film compositions, such as lead zirconate thin films, and the effect of donor doping on them is very necessary. For this purpose, thin films of antiferroelectric lead zirconate and La-modified lead zirconate thin films with mole % concentrations of 0, 3, 5, and 9 have been deposited by pulsed excimer laser ablation. The dielectric and hysteresis properties have confirmed that with a gradual increase of the La content, the room-temperature antiferroelectric lead zirconate thin films can be modified into ferroelectric and paraelectric phases. ac electrical studies revealed that the polaronic related hopping conduction is responsible for the charge transport phenomenon in these films. With a La content of less than or equal to3 mole % in pure lead zirconate, the conductivity of the films has been reduced and followed by an increase of its conductivity for a greater than or equal to3% addition of La to lead zirconate thin films. The polaronic activation energies are also found to follow a similar trend as that of the conductivity.

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In a classic study, Kacser & Burns (1981, Genetics 97, 639-666) demonstrated that given certain plausible assumptions, the flux in a metabolic pathway was more or less indifferent to the activity of any of the enzymes in the pathway taken singly. It was inferred from this that the observed dominance of most wild-type alleles with respect to loss-of-function mutations did not require an adaptive, meaning selectionist, explanation. Cornish-Bowden (1987, J. theor. Biol. 125, 333-338) showed that the Kacser-Burns inference was not valid when substrate concentrations were large relative to the relevant Michaelis constants. We find that in a randomly constructed functional pathway, even when substrate levels are small, one can expect high values of control coefficients for metabolic flux in the presence of significant nonlinearities as exemplified by enzymes with Hill coefficients ranging from two to six, or by the existence of oscillatory loops. Under these conditions the flux can be quite sensitive to changes in enzyme activity as might be caused by inactivating one of the two alleles in a diploid. Therefore, the phenomenon of dominance cannot be a trivial ''default'' consequence of physiology but must be intimately linked to the manner in which metabolic networks have been moulded by natural selection.

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Hexagonal Cu-2 Te has been synthesised by mechanical alloying from elemental powders. The milling time required for the synthesis is longer than that reported for other tellurides. The mechanical grinding of the bulk Cu2Te obtained by the melting route does not change the structure. Prolonged milling as well as grinding beyond 40 h lead to a decrease in grain size to nanometer level. The cold compaction of milled or ground powders exhibit much smaller Seebeck coefficient (thermopower). However, cold compaction of samples milled for longer time (>150 h) lead to the thermopower values close to that of the bulk indicating significant improvement of rheological properties at room temperature for powders milled for long times.

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Antiferroelectric lead zirconate (PZ) thin films were deposited by pulsed laser ablation on platinum-coated silicon substrates. Films showed a polycrystalline pervoskite structure upon annealing at 650 degrees C for 5-10 min. Dielectric properties were investigated as a function of temperature and frequency. The dielectric constant of PZ films was 220 at 100 kHz with a dissipation factor of 0.03. The electric field induced transformation from the antiferroelectric phase to the ferroelectric phase was observed through the polarization change, using a Sawyer-Tower circuit. The maximum polarization value obtained was 40 mu C/cm(2). The average fields to excite the ferroelectric state, and to reverse to the antiferroelectric state were 71 and 140 kV/cm, respectively. The field induced switching was also observed through double maxima in capacitance-voltage characteristics. Leakage current was studied in terms of current versus time and current versus voltage measurements. A leakage current density of 5x10(-7) A/cm(2) at 3 V, for a film of 0.7 mu m thickness, was noted at room temperature. The trap mechanism was investigated in detail in lead zirconate thin films based upon a space charge limited conduction mechanism. The films showed a backward switching time of less than 90 ns at room temperature.

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The dielectric constants of lead iron niobate (PFN) and 40% lead zinc niobate (PZN) added to lead iron niobate (PFN0.6-PZN(0.4)) have been measured as a function of pressure up to 6 GPa under isothermal conditions between room temperature and 348 K. The relaxer transition temperature measured at 1 kHz excitation frequency varies at a rate -24.5 K/GPa for PFN and at a rate of - 28.8 K/GPa for the PFN0.6-PZN(0.4) composition.

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Lead acid batteries are used in hybrid vehicles and telecommunications power supply. For reliable operation of these systems, an indication of state of charge of battery is essential. To determine the state of charge of battery, current integration method combined with open circuit voltage, is being implemented. To reduce the error in the current integration method the dependence of available capacity as a function of discharge current is determined. The current integration method is modified to incorporate this factor. The experimental setup built to obtain the discharge characterstics of the battery is presented.

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We study a zero sum differential game of mixed type where each player uses both control and stopping times. Under certain conditions we show that the value function for this problem exists and is the unique viscosity solution of the corresponding variational inequalities. We also show the existence of saddle point equilibrium for a special case of differential game.

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Direct precipitation of fine powders of lead zirconate titanate (PZT) in the complete range of solid solution, is investigated under hydrothermal conditions, starting from lead oxide and titania/zirconia mixed gels. The perovskite phase is formed in the temperature range of 165 – 340°C. Sequence of the hydrothermal reactions is studied by identifying the intermediate phases. The initial formation of PbO: TiO2 solid solution is followed by the reaction of the same with the remaining mixed gels giving rise to X-ray amorphous PZT phase. Further, through crystallite growth, the X-ray crystalline PZT is formed. This method can be extended for the preparation of PLZT powder as well. The resulting powders are sinterable to high density ceramics.

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The high-temperature paraelectric phase of dicalcium lead propionate, DCLP, at 363 ± 5 K is tetragonal, with a = 12.574 (6), c = 17.403 (9) Å, V = 2751.4 Å3, Z = 4 and corresponds to the space group P41212 (or P43212). The thermal expansion curve shows the transition somewhere between 328 and 343 K.

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Crystal growth of YIG from fluxes containing lead sulphate in place of lead oxide in the usual lead oxide-lead fluoride-boron oxide flux system has been tried. Lead sulphate decomposes during crystal growth giving lead oxide and sulphur trioxide. Due to the influence of sulphur trioxide in the system the yield of crystals almost doubles. There is no change either in the morphology of the crystals or their lattice parameter. It is possible that solubility of YIG is different in the new flux and the changed solubility causes the increase in yield of crystals.

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Lead acid batteries are used in hybrid vehicles and telecommunications power supply. For reliable operation of these systems, an indication of state of charge of battery is essential. To determine the state of charge of battery, current integration method combined with open circuit voltage, is being implemented. To reduce the error in the current integration method the dependence of available capacity as a function of discharge current is determined. The current integration method is modified to incorporate this factor. The experimental setup built to obtain the discharge characterstics of the battery is presented