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Motivating Application (motivating + application)
Selected AbstractsSocial Optimal Location of Facilities with Fixed Servers, Stochastic Demand, and CongestionPRODUCTION AND OPERATIONS MANAGEMENT, Issue 6 2009Ignacio Castillo We consider two capacity choice scenarios for the optimal location of facilities with fixed servers, stochastic demand, and congestion. Motivating applications include virtual call centers, consisting of geographically dispersed centers, walk-in health clinics, motor vehicle inspection stations, automobile emissions testing stations, and internal service systems. The choice of locations for such facilities influences both the travel cost and waiting times of users. In contrast to most previous research, we explicitly embed both customer travel/connection and delay costs in the objective function and solve the location,allocation problem and choose facility capacities simultaneously. The choice of capacity for a facility that is viewed as a queueing system with Poisson arrivals and exponential service times could mean choosing a service rate for the servers (Scenario 1) or choosing the number of servers (Scenario 2). We express the optimal service rate in closed form in Scenario 1 and the (asymptotically) optimal number of servers in closed form in Scenario 2. This allows us to eliminate both the number of servers and the service rates from the optimization problems, leading to tractable mixed-integer nonlinear programs. Our computational results show that both problems can be solved efficiently using a Lagrangian relaxation optimization procedure. [source] On a class of switched, robustly stable, adaptive systemsINTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING, Issue 3 2001Felipe M. Pait Abstract A class of switched algorithms for adaptive control of siso linear systems is described. The systems considered are assumed to belong to one among a finite number of classes of admissible process models, and each class is robustly stabilizable by some linear time-invariant controller. The control used is chosen in real time by a tuner or supervisor, according to observations of suitably defined ,identification errors.' The method preserves the robustness properties of the linear control design in an adaptive context, thus extending earlier ideas in multiple-model adaptive control by presenting a more flexible and less conservative framework for considering such systems. One motivating application is fault-tolerant control. Copyright © 2001 John Wiley & Sons, Ltd. [source] Bayesian Hierarchical Functional Data Analysis Via Contaminated Informative PriorsBIOMETRICS, Issue 3 2009Bruno Scarpa Summary A variety of flexible approaches have been proposed for functional data analysis, allowing both the mean curve and the distribution about the mean to be unknown. Such methods are most useful when there is limited prior information. Motivated by applications to modeling of temperature curves in the menstrual cycle, this article proposes a flexible approach for incorporating prior information in semiparametric Bayesian analyses of hierarchical functional data. The proposed approach is based on specifying the distribution of functions as a mixture of a parametric hierarchical model and a nonparametric contamination. The parametric component is chosen based on prior knowledge, while the contamination is characterized as a functional Dirichlet process. In the motivating application, the contamination component allows unanticipated curve shapes in unhealthy menstrual cycles. Methods are developed for posterior computation, and the approach is applied to data from a European fecundability study. [source] Principles and applications of control in quantum systemsINTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL, Issue 15 2005Hideo Mabuchi Abstract We describe in this article some key themes that emerged during a Caltech/AFOSR Workshop on ,Principles and Applications of Control in Quantum Systems' (PRACQSYS), held 21,24 August 2004 at the California Institute of Technology. This workshop brought together engineers, physicists and applied mathematicians to construct an overview of new challenges that arise when applying constitutive methods of control theory to nanoscale systems whose behaviour is manifestly quantum. Its primary conclusions were that the number of experimentally accessible quantum control systems is steadily growing (with a variety of motivating applications), that appropriate formal perspectives enable straightforward application of the essential ideas of classical control to quantum systems, and that quantum control motivates extensive study of model classes that have previously received scant consideration. Copyright © 2005 John Wiley & Sons, Ltd. [source] | ||||||||||