207726898
Quick response policy with Bayesian information updates
Abstract In this paper we investigate the quick response (QR) policy with different Bayesian models. Under QR policy, a retailer can collect market information from the sales of a pre-seasonal product whose demand is closely related to a seasonal product’s demand. This information is then used to update the distribution for the seasonal product’s demand by a Bayesian approach. We study two information update models: one with the revision of an unknown mean, and the other with the revision of both an unknown mean and an unknown variance. The impacts of the information updates under both models are compared and discussed. We also identify the features of the pre-seasonal product which can bring more significant profit improvement. We conclude that an effective QR policy depends on a precise information update model as well as a selection of an appropriate pre-seasonal product as the observation target.
46474884
Explicit Efficient Frontier of a Continuous-Time Mean Variance Portfolio Selection Problem
In this work we consider a continuous-time mean-variance portfolio selection problem that is formulated as a bi-criteria optimization problem. The objective is to maximize the expected return and minimize the variance of the terminal wealth. By putting weights on the two criteria one obtains a single objective stochastic control problem which is however not in the standard form. We show that this non-standard problem can be “embedded” into a class of auxiliary stochastic linear-quadratic (LQ) problems. By solving the latter based on the recent development on stochastic LQ problems with indefinite control weighting matrices, we derive the efficient frontier in a closed form for the original mean-variance problem.
1850331
COCA: collaborative objects coordination architecture
Coordination policies vary from collaboration to collaboration and are even subject to evolution in different phases of the same collaboration. It is vital for collaborative systems to be flexible enough to accommodate changes to the coordination policies du ring development and the lifetime of the collaboration. Motivated by previous work of separating coordinati on and computation, we propose COCA as a generic framework for developing collaborative systems and modeling the coordination policies. Participants ex plicitly adopt roles, and coordination policies are specifie d in terms of roles in a logic-based specification langu age. Policies are interpreted at runtime at each collabo r ti n site by a COCA virtual machine. It is easy to chang e the coordination policies both during development and a t runtime.
1387834
An Efficient Algorithm for Pattern Discovery in Large Text Databases
17329223
Supereulerian planar graphs
We investigate the supereulerian graph problems within planar graphs, and we prove that if a 2-edge-connected planar graph G is at most three edges short of having two edge-disjoint spanning trees, then G is supereulerian except a few classes of graphs. This is applied to show the existence of spanning Eulerian subgraphs in planar graphs with small edge cut conditions. We also determine several extremal bounds for planar graphs to be supereulerian.
4669631
A new hierarchical control scheme for a class of cyclically repeated discrete-event systems
We extend the hierarchical control method in (Li et al., 2004) to a more generic setting which involves cyclically repeated processes. A hierarchical architecture is presented to facilitate control synthesis. Specifically, a conservative max-plus model for cyclically repeated processes is introduced on the upper level which provides an optimal online plan list. An enhanced min-plus algebra based scheme on the lower level not only handles unexpected events but, more importantly, addresses cooperation issues between sub-plants and different cycles. A rail traffic example is given to demonstrate the effectiveness of the proposed approach.
15275424
Blur identification based on kurtosis minimization
In this paper, we describe an algorithm for identifying a parametrically described blur based on kurtosis minimization. Using different choices for the parameters of the blur, the noisy blurred image is restored using Wiener filter. We use the kurtosis as a measurement of the quality of the restored image. From the set of the candidate deblurred images, the one with the minimum kurtosis is selected. The proposed technique is tested in a simulated experiment on a variety of blurs including atmospheric turbulence blurs, Gaussian blurs, and out-of-focus blurs. The proposed approach is also tested on real blurred images. Moreover, we test the performance when a wrong blur model is given. Our experiments show that the kurtosis minimization measurements match well with methods that maximize PSNR.