Journal of Applied Mathematics and Decision Sciences

A.Y. Hlemskii

Projective modules in the classical and quantum functional analysis

经典与量子泛函分析中的投射模

经典与量子泛函分析中的射影模

We consider a single-stage multiproduct manufacturing facility producing several end-products for delivery to customers with a required customer lead-time. The end-products can be split in two classes: few products with high volume demands and a large number of products with low-volume demands. In order to reduce inventory costs, it seems efficient to produce the high-volume products according to an MTS policy and the low volume products according to an MTO policy. The purpose of this paper is to analyze and compare the impact of the scheduling policy on the overall inventory costs, under customer lead-time service level constraints. We consider two policies: the classical FIFO policy and a priority policy (PR) which gives priority to low volume products over high volume products. We show that for some range of parameters, the PR rule can significantly outperform the FIFO rule. In these ranges, the service level constraints are satisfied by the PR rule with much lower inventory costs.

Khaled Hadj Youssef

Christian van Delft

Yves Dallery

Analysis and Optimization of a Combined Make-to-Stock and Make-to-Order Multiproduct Manufacturing System

组合型按库存生产和按订单生产多产品制造系统的分析与优化

We show how it is possible to construct efficient duration dependent semi-Markov reliability models by considering recurrence time processes. We define generalized reliability indexes and we show how it is possible to compute them. Finally, we describe a possible application in the study of credit rating dynamics by considering the credit rating migration as a reliability problem.

Guglielmo D'Amico

Jacques Janssen

Raimondo Manca

Semi-Markov Reliability Models with Recurrence Times and Credit Rating Applications

半马尔可夫可靠性模型与复发时间和信用评级应用

For at least partially ordered three-way tables, it is well known how to arithmetically decompose Pearson's statistic into informative components that enable a close scrutiny of the data. Similarly well-known are smooth models for two-way tables from which score tests for homogeneity and independence can be derived. From these models, both the components of Pearson's and information about their distributions can be derived. Two advantages of specifying models are first that the score tests have weak optimality properties and second that identifying the appropriate model from within a class of possible models gives insights about the data. Here, smooth models for higher-order tables are given explicitly, as are the partitions of Pearson's into components. The asymptotic distributions of statistics related to the components are also addressed.

J. C. W. Rayner

Eric J. Beh

Components of Pearson's Statistic for at Least Partially Ordered -Way Contingency Tables

皮尔逊统计量在至少部分有序的多路列联表中的组成部分

Automated public health records provide the necessary data for rapid outbreak detection. An adaptive exponentially weighted moving average (EWMA) plan is developed for signalling unusually high incidence when monitoring a time series of nonhomogeneous daily disease counts. A Poisson transitional regression model is used to fit background/expected trend in counts and provides “one-day-ahead” forecasts of the next day's count. Departures of counts from their forecasts are monitored. The paper outlines an approach for improving early outbreak data signals by dynamically adjusting the exponential weights to be efficient at signalling local persistent high side changes. We emphasise outbreak signals in steady-state situations; that is, changes that occur after the EWMA statistic had run through several in-control counts.

R. S. Sparks

T. Keighley

D. Muscatello

Improving EWMA Plans for Detecting Unusual Increases in Poisson Counts

改进用于检测泊松计数异常增加的EWMA计划

Department of Management Sciences, City University of Hong Kong, Tat Chee Avenue, Kowloon, Hong Kong As a multidisciplinary field, financial engineering is becoming increasingly important in today’s economic and financial world, especially in areas such as portfolio management, asset valuation and prediction, fraud detection, and credit risk management. For example, in a credit risk context, the recently approved Basel II guidelines advise financial institutions to build comprehensible credit risk models in order to optimize their capital allocation policy. Computational methods are being intensively studied and applied to improve the quality of the financial decisions that need to be made. Until now, computational methods and models are central to the analysis of economic and financial decisions. However, more and more researchers have found that the financial environment is not ruled by mathematical distributions or statistical models. In such situations, some attempts have also been made to develop financial engineering models using some emerging intelligent computing approaches. For example, an artificial neural network (ANN) is a non-parametric estimation technique which does not make any distributional assumptions regarding the underlying asset. Instead, ANN approach develops a model using sets of unknown parameters and lets the optimization routine seek the best fitting parameters to obtain the desired results. That is, these emerging intelligent solutions can efficiently improve the decisions for financial engineering problems. Having agreed on this basic fact, the guest editors determined that the main purpose of this special issue is not to merely illustrate the superior performance of a new intelligent computational method, but also to demonstrate how it can be used effectively in a financial engineering environment to improve and facilitate financial decision making. For this purpose, this special issue presents some new progress in intelligent computational methods for financial engineering In particular, the special issue addresses how the emerging intelligent computational methods (e.g., ANN, support vector machines, evolutionary algorithm, and fuzzy models etc.) can be used to develop intelligent, easy-to-use and/or comprehensible computational systems (e.g., decision support systems, agent-based system, and web-based systems etc.), which is expected to trigger some thoughts and deepen further research. In this special issue, 12 papers were selected from 26 submissions related to intelligent computational methods for financial engineering from different countries and regions. The authors of

Publication Information	Publisher: Hindawi Publishing Corporation，Publishing cycle: ，Journal Type: journal，Open Access Journals: No
Basic data	Year of publication: 1997，Proportion of original research papers: ，Self Citation Rate:， Gold OA Rate:

Journal of Applied Mathematics and Decision Sciences

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Projective modules in the classical and quantum functional analysis

Projective modules in the classical and quantum functional analysis

Projective modules in the classical and quantum functional analysis

Projective modules in the classical and quantum functional analysis

Projective modules in the classical and quantum functional analysis

Analysis and Optimization of a Combined Make-to-Stock and Make-to-Order Multiproduct Manufacturing System

Semi-Markov Reliability Models with Recurrence Times and Credit Rating Applications

Components of Pearson's Statistic for at Least Partially Ordered -Way Contingency Tables

Improving EWMA Plans for Detecting Unusual Increases in Poisson Counts

Intelligent Computational Methods for Financial Engineering