# Browsing by Subject "Uncertainty (Information theory)"

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Item Effects of expectancy violations on uncertainty in interpersonal interactions(Texas Tech University, 1989-05) White, Cindy HagemeierShow more Not availableShow more Item Optimal draining of fluid networks with parameter uncertainty(2007-12) Buke, Burak, 1980-; Hasenbein, John J.; Morton, David P.Show more Fluid networks are useful tools for analyzing complex manufacturing environments especially in semiconductor wafer fabrication. The makespan of a fluid network is defined as the time to drain the system, when there is fluid present in the buffers initially. Based on this definition, the question of determining the allocation of resources so as to minimize the makespan of a fluid network is known as the makespan problem. In the deterministic version of the makespan problem, it is assumed that the parameters of the system, such as incoming rates, service rates and initial inventory, are known deterministically. The deterministic version of the makespan problem for reentrant lines and multiclass fluid networks has been investigated in the literature and an analytical solution for the problem is well-known. In this work, we provide another formulation for the deterministic makespan problem and prove that the problem can be solved for each station separately. Optimal solutions for the deterministic makespan problem have been used as a guide to develop heuristics methods to solve makespan scheduling problem in the job-shop context in the literature. This provides one motivation for further investigation of the fluid makespan problem. In this work our main focus is solving the makespan problem when the problem parameters are uncertain. This uncertainty may be caused by various factors such as the unpredictability of the arrival process or randomness in machine availability due to failures. In the presence of parameter uncertainty, the decision maker's goal is to optimally allocate the capacity in order to minimize the expected value of the makespan. We assume that the decision maker has distributional information about the parameters at the time of decision making. We consider two decision making schemes. In the first scheme, the controller sets the allocations before observing the parameters. After the initial allocations are set, they cannot be changed. In the second scheme, the controller is allowed a recourse action after a data collection process. It is shown that in terms of obtaining the optimal control, both schemes differ considerably from the deterministic version of the problem. We formulate both schemes using stochastic programming techniques. The first scheme is easier to analyze since the resulting model is convex. Unfortunately, under the second decision scheme, the objective function is non-convex. We develop a branch-and-bound methodology to solve the resulting stochastic non-convex program. Finally, we identify some special cases where the stochastic problem is analytically solvable. This work uses stochastic programming techniques to formulate and solve a problem arising in queueing networks. Stochastic programming and queueing systems are two major areas of Operations Research that deal with decision making under uncertainty. To the best of our knowledge, this dissertation is one of the first works that brings these two major areas together.Show more Item Simulation of dynamic systems with uncertain parameters(2004) Zhang, Fu; Longoria, Raul G.Show more Item Uncertainties in pressure coefficients derived from full and model scale data / $c by Fei Long.(Texas Tech University, 2004-08) Long, FeiShow more The purpose of this study is to build the uncertainties associated with the wind tunnel testing and full-scale to wind tunnel pressure coefficient extrapolation by comparing the model and full-scale pressure coefficients. Two types of comparisons were made: one is the comparison between the two models CSU & SLM, and the other is the comparison between the models and full-scale (WERFL). For each case, both the observed statistics (i.e., mean, standard deviation, maximum, and minimum Cp) and estimated mean extreme Cp are analyzed. Two methods are used to obtain the estimated mean hourly extreme pressure coefficients. For the first case, the uncertainties according to repeatability, model-building, use of different wind tunnels, and estimation techniques for pressure coefficients statistics (i.e., both observed statistics and estimated mean extreme Cp) were estimated. For the second case, the pressure coefficients statistics (i.e., both observed statistics and estimated mean extreme Cp) of model and full-scale records achieved for a comparison. Individual tap time series as well as the area average and moving average time series were used to establish the uncertainties. The best-fit (Palisade Corporation, 1993) program is used to obtain best-fit probability density function and summary statistics for the error terms of all observed statistics comparison.Show more