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In order to gain a competitive position within industry, in semiconductor fabs enormous efforts have been spent in developing different kinds of operational control strategies relating to work-in-process (WIP) and due date. This paper presents a framework to deal with shop floor control problems regarding WIP balance and due date control. The framework comprises four key components that are (1) Global...
Classic first and second-order response surface models (RSM) do not automatically observe monotonicity, while in many real problems, the researcher knows the response to be monotonic in some variables. This paper provides the constraints on coefficients that ensure monotonicity and offers some approaches for estimating monotonically constrained response surfaces.
Reliable simulation estimation builds on accurately specified input models. In the context of simulating tail events, knowledge on the tail of the input model is especially important, yet is often hard to obtain due to a lack of data. In this paper, we consider tail event estimation without any knowledge on the input tail, but rather only making a general assumption that it is convex. We focus on...
We present general principles for the design and analysis of unbiased Monte Carlo estimators for quantities such as α = g(E (X)), where E (X) denotes the expectation of a (possibly multidimensional) random variable X, and g(·) is a given deterministic function. Our estimators possess finite work-normalized variance under mild regularity conditions such as local twice differentiability of g(·) and...
Static network unreliability computation is an NP-hard problem, leading to the use of Monte Carlo techniques to estimate it. The latter, in turn, suffer from the rare event problem, in the frequent situation where the system's unreliability is a very small value. As a consequence, specific rare event event simulation techniques are relevant tools to provide this estimation. We focus here on a method...
Due to cost constraints, geological conditions are investigated using boreholes. However, this means conditions are never known exactly, particularly for deep and long tunnels, because uncertainties exist between neighboring boreholes. Simulation can deal with underlying uncertainty, and offers benefits to project planners in the development of better alternatives and optimization. This research developed...
This article presents Sequem, a fully sequential procedure for computing point estimators and confidence intervals (CIs) for extreme steady-state quantiles of a simulation output process. The method is an enhancement of the Sequest procedure proposed by Alexopoulos et al. in 2014 for estimating nonextreme steady-state quantiles. Sequem exploits a combination of batching, sectioning, and the maximum...
When simulating a complex stochastic system, the behavior of the output response depends on the input parameters estimated from finite real-world data, and the finiteness of data brings input uncertainty to the output response. The quantification of the impact of input uncertainty on output response has been extensively studied. However, most of the existing literature focuses on providing inferences...
The Bourgoyne and Young Model (BYM) is used to determine the rate of penetration in oil well drilling processes. To achieve this the model must be parameterized with coefficients that are estimated on the basis of prior experience. Since drilling is a physical process, measurement data may include noise and the model may naturally fail to represent it correctly. In this study the BYM coefficients...
This article outlines a method for automatically generating models of dynamic decision-making that both have strong predictive power and are interpretable in human terms. This is useful for designing empirically grounded agent-based simulations and for gaining direct insight into observed dynamic processes. We use an efficient model representation and a genetic algorithm-based estimation process to...
In this paper, we introduce a metropolitan traffic simulation with microscopic vehicle agents with approximated behavior near intersections. We simulate a metropolitan traffic flow for Tokyo and surrounding four prefectures with fine-grained traffic demand obtained from Tokyo Person Trip survey. Though this simulator has an ability to manage signal control, it is difficult to obtain the real signal...
Simulation used for the performance assessment of stochastic systems is usually driven by input models estimated from real-world data, which introduces both input and simulation uncertainty to the performance estimates. For many complex systems, because the components of input models are mutually dependent, an efficient estimation of dependence could improve the system performance assessment. Since...
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