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Consider a tandem system of machines separated by infinitely large buffers. The machines process a continuous flow of products, possibly at different speeds. The life and repair times of the machines are assumed to be exponential. We claim that the overflow probability of each buffer has an exponential decay, and provide an algorithm to determine the exact decay rates in terms of the speeds and the failure and repair rates of the machines. These decay rates provide useful qualitative insight into the behavior of the flow line. In the derivation of the algorithm we use the theory of Large Deviations.
We apply the cross-entropy method to a network design problem with multi-type links and nodes, in which the network's reliability is to be maximized subject to a fixed budget. Numerical experiments illustrate the simplicity and effectiveness of the method.
The problem of counting the number of s-t paths in a graph is #Pcomplete. We provide an algorithm to estimate the solution stochastically, using sequential importance sampling. We show that the method works effectively for both graphs and digraphs. We also use the method to investigate the expected number of s-t paths in a random graph of size n and density d, and develop a model that shows how this quantity behaves when n and d are varied.
The spread of the human immunodeficiency virus (HIV) depends prominently on the migration of people between different regions. An important consequence of this population mobility is that HIV control strategies that are optimal in a regional sense may not be optimal in a national sense. We formulate various mathematical control problems for HIV spread in mobile heterosexual populations, and show how optimal regional control strategies can be obtained that minimize the national spread of HIV. We apply the cross-entropy method to solve these highly multi-modal and non-linear optimization problems. We demonstrate the effectiveness of the method via a range of experiments and illustrate how the form of the optimal control function depends on the mathematical model used for the HIV spread.
difference of renewal processes boundary crossing second-order approximations
Global likelihood maximization is an important aspect of many statistical analyses. Often the likelihood function is highly multi-extremal. This presents a significant challenge to standard search procedures, which often settle too quickly into an inferior local maximum. We present a new approach based on the cross-entropy (CE) method, and illustrate its use for the analysis of mixture models.
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