Administrative days in acute care facilities: a queueing-analytic approach.

After acute care services are no longer required, a patient in an acute care hospital often must remain there while he or she awaits the provision of extended care services by a nursing home, through social support services, or by a home health care service. This waiting period is often referred to as "administrative days" because the time is spent in the acute facility not for medical reasons, but rather for administrative reasons. In this paper we use a queueing-analytic approach to describe the process by which patients await placement. We model the situation using a state-dependent placement rate for patients backed up in the acute care facility. We compare our model results with data collected from a convenience sample of 7 hospitals in New York State. We conclude with a discussion of the policy implications of our models.     

Optimal Sequencing of Servers in the Two-Station Series Queueing System

This paper deals with determining an optimal sequence of service stations in a series queueing system. Optimality is defined in terms of the total time spent waiting for service. Sequences are compared on the basis of the moments of their steady-state total waiting time. In addition, the rules of stochastic dominance are applied which allow comparison of sequences on the basis of their waiting time distributions. Analytical results in the sequencing of service stations in series queues have been limited to stations with constant or exponential service times. This study extends the investigation to service distributions with varying degrees of statistical regularity given by the family of Erlang distributions.Relationships are developed for predicting optimal sequences. Validation is accomplished by simulating a number of systems and comparing the waiting time distribution functions for each sequence. The relationships are shown to be good predictors and useful in the study and design of systems of servers in series.     

Location–Allocation of Multiple-Server Service Centers with Constrained Queues or Waiting Times

Recently, the authors have formulated new models for the location of congested facilities, so to maximize population covered by service with short queues or waiting time. In this paper, we present an extension of these models, which seeks to cover all population and includes server allocation to the facilities. This new model is intended for the design of service networks, including health and EMS services, banking or distributed ticket-selling services. As opposed to the previous Maximal Covering model, the model presented here is a Set Covering formulation, which locates the least number of facilities and allocates the minimum number of servers (clerks, tellers, machines) to them, so to minimize queuing effects. For a better understanding, a first model is presented, in which the number of servers allocated to each facility is fixed. We then formulate a Location Set Covering model with a variable (optimal) number of servers per service center (or facility). A new heuristic, with good performance on a 55-node network, is developed and tested.     

Output specification and performance measurement in fire services: An ordinal output variable approach

This paper investigates performance differences in fire services with an ordinal output variable. An output variable is constructed for fires in detached houses in Sweden. The ordered probit model is used in the estimation of a production function. Performance differences are found by using the “individual effects” method having panel data. However, here the dimensions are not time and cross-section, but instead cross-section and turn-outs for each fire service. The results show no performance differences between full-time and part-time firemen and indicate that “team spirit” is more important for performance than the actual number of firemen fighting a fire.     

The partial adjustment valuation approach with dynamic and variable speeds of adjustment to evaluating and measuring the business value of information technology

In this paper we develop the partial adjustment valuation approach in which the speeds of (partial) adjustment are assumed to be dynamic and variable, rather than fixed or constant, to assessing the value of information technology (IT). The speeds of adjustment are a function of a set of macroeconomic and/or microeconomic variables, observed and unobserved and, hence, become time-varying or dynamic and variable over time. The approach is illustrated by a practical application. The results imply that the constant speeds of adjustment may overestimate or underestimate the actual speeds of adjustment and, accordingly, may miscalculate the values of performance metrics. Thus, the partial adjustment valuation approach with dynamic and variable speeds of adjustment is more realistic and, more importantly, captures the changing patterns and trends of the adjustment speeds and the performance measures as well. As such, the partial adjustment valuation approach with constant speeds of adjustment fails to adequately explain the dynamic production process of a decision making unit. The empirical evidence also conflicts with the lopsided view that the productivity paradox does not exist in developed countries.     

Forecasting model with asymmetric market response and its application to pricing of consumer package goods

This paper presents a dynamic forecasting model that accommodates asymmetric market responses to marketing mix variable—price promotion—by threshold models. As a threshold variable to generate a mechanism for different market responses, we use the counterpart to the concept of a price threshold applied to a representative consumer in a store. A Bayesian approach is taken for statistical modelling because of advantages that it offers over estimation and forecasting. The proposed model incorporates the lagged effects of a price variable. Thereby, myriad pricing strategies can be implemented in the time horizon. Their effectiveness can be evaluated using the predictive density. We intend to improve the forecasting performance over conventional linear time series models. Furthermore, we discuss efficient dynamic pricing in a store using strategic simulations under some scenarios suggested by an estimated structure of the models. Empirical studies illustrate the superior forecasting performance of our model against conventional linear models in terms of the root mean square error of the forecasts. Useful information for dynamic pricing is derived from its structural parameter estimates. This paper develops a dynamic forecasting model that accommodates asymmetric market responses to marketing mix variable—price promotion—by the threshold models. Copyright © 2005 John Wiley & Sons, Ltd.     

联合监测过程位置参数和尺度参数的非参数Shewhart控制图

用于检测生产服务过程的传统控制图多数都假定过程的分布是已知的。这些控制困经常是在正态分布的假设下构建的,然而在服务质量实时监控中数据往往是非正态的。在这种情况下,基于正态分布假设的控制图的结果是不可靠的。为了解决这个问题,通常考虑非参数方法,因为在过程分布未知情况下,非参数控制图比参数图更加稳健有效。本文提出一个新的基于Van der Waerden和Klotz检验的Lepage型非参数Shewhart控制图(称为LPN图)用于同时检测未知连续过程分布的位置参数和尺度参数。文中给出了LPN图在不同参数下的控制限。依据运行长度分布的均值,方差和分位数,分析了LPN图在过程受控和失控时的性能,并与其他一些现有的非参数控制图进行比较。基于蒙特卡洛的模拟结果表明,LPN图对非正态分布具有很好的稳健性,并且在不同的过程分布下对检测位置参数和尺度参数,尤其对检测尺度参数的漂移都具有很好的性能。最后通过监控出租车服务质量说明LPN图在实际中的应用。     

Location of Preventive Health Care Facilities

This paper is focused on the problem of locating preventive health care facilities. The aim is to maximize participation to prevention programs. We assume that distance is a major determinant of participation and people would go to the closest facility for preventive health care. Each facility is required to have more than a predetermined number of clients because of the direct relationship between volume and quality of preventive services. We provide a mathematical formulation and present alternative solution approaches for this new location problem. We report on computational performance of the proposed methods in locating public health centers in Fulton County, Georgia and mammography screening centers in Montreal, Quebec.     

Composition and deployment of e-Health services over Wireless Sensor Networks

Providing necessary background for provisioning of a new generation of enriched services over Wireless Sensor Networks is the main effort that the scientific community is currently carrying out. These services have improved a great number of aspects related to pervasive systems such as saving resources, efficiency, reliability, scalability and low power consumption. In this paper, $\mu$SMS middleware, using an event-based service model, is presented. This novel approach makes up the design requirements previously mentioned by implementing a dynamic memory kernel and a variable payload multiplexing mechanism for the information events in order to provide advanced services. The results obtained over real-world deployments, especially those related with provision of e-Health services, reflect a significant improvement over other similar proposals, such as the RUNES approach: 50% lower memory overhead, 53% lower software components load time and 12% lower event’s propagation time.     

Reliability analysis of complex communication systems

This paper deals with a first-come, first-served (FCFS) queueing model to analyze the asymptotic behavior of a heterogeneous finite-source communication system with a single processor. Each source and the processor are assumed to operate in independent random environments, allowing the arrival and service processes to be Markov-modulated ones. Each message is characterized by its own exponentially distributed source and processing time with parameter, depending on the state of the corresponding environment, that is, the arrival and service rates are subject to random fluctuations. Assuming that the arrival rates of the messages are many times greater than their service rates (“fast” arrival), it is shown that the time to the first system failure converges in distribution, under appropriate norming, to an exponentially distributed random variable. Some simple examples are considered to illustrate the effectiveness of the method proposed by comparing the approximate results to the exact ones. Supported by the Hungarian National Foundation for Scientific Research (grant No. OTKA T14974/95). Proceedings of the Seminar on Stability Problems for Stochastic Models, Vologda, Russia, 1998, Part II.     

Frequency assignment in a SDMA satellite communication system with beam decentring feature

In satellite communication, Spatial Division Multiple Access (SDMA) has become one of the most promising techniques that can accommodate continuing increase in the number of users and traffic demands. The technology is based on radio resource sharing that separates communication channels in space. It relies on adaptive and dynamic beam-forming technology and well-designed algorithms for resource allocation among which frequency assignment is considered. This paper studies static Frequency Assignment Problem (FAP) in a satellite communication system involving a satellite and a number of users located in a service area. The objective is to maximize the number of users that the system can serve while maintaining the signal to interference plus noise ratio of each user under a predefined threshold. Traditionally, interference is treated as fixed (binary interferences or fixed minimal required separation between frequencies) . In this paper, the interference is cumulative and variable. To solve the problem, we work on both discrete and continuous optimizations. Integer linear programming formulations and greedy algorithms are proposed for solving the discrete frequency assignment problem. The solution is further improved by beam decentring algorithm which involves continuous adjustment of satellite beams and deals with non-linear change of interference.     

Generalized Fibonacci broadcasting: An efficient VOD scheme with user bandwidth limit

Broadcasting is attractive in delivering popular videos in video-on-demand service, because the server broadcast bandwidth is independent of the number of users. However, the required server bandwidth does depend on how much bandwidth each user can use, as well as on the user's initial waiting time. This paper addresses the issue of limiting the user bandwidth, and proposes a new broadcasting scheme, named Generalized Fibonacci Broadcasting (GFB). In terms of many performance graphs, we show that, for any given combination of the server bandwidth and user bandwidth, GFB can achieve the least waiting time among all the currently known fixed-delay broadcasting schemes. Furthermore, it is very easy to implement GFB. We also demonstrate that there is a trade-off between the user waiting time and the buffer requirement at the user.     

Risk-adjusted control charts for health care assessment

The recent Joint Commission on Accreditation of Healthcare Organization (JCAHO) requirement that hospital accreditation be based upon a Total Quality Management (TQM) approach has focused the attention of health care administrations on the use of techniques such as control charts. However, control charts are not typically adjusted for severity of illness. This adjustment is needed because, unlike industrial organizations, hospitals are not able to control all of their inputs and must accept variances in their patients. In this paper, we present a methodology for adjusting a health care organization's control charts to reflect their patient population's severity of illness during different time intervals. We then demonstrate that risk-adjusting expected patient outcomes can change our assessments of the relative quality of care offered by a health care organization in different time periods.     

An analysis of p-median location problem: Effects of backup service level and demand assignment policy

Any solution to facility location problems will consider determining the best suitable locations with respect to certain criteria. Among different types of location problems, involving emergency service system (ESSs) are one of the most widely studied in the literature, and solutions to these problems will mostly aim to minimize the mean response time to demands. In practice, however, a demand may not be served from its nearest facility if that facility is engaged in serving other demands. This makes it a requirement to assign backup services so as to improve response time and service quality. The level of backup service is a key, strategic-level planning factor, and must be taken into consideration carefully. Moreover, in emergency service operations conducted in congested demand regions, demand assignment policy is another important factor that affects the system performance. Models failing to adopt sufficient levels of backup service and realistic demand assignment policies may significantly deteriorate the system performance.Considering the classic p-median problem (pMP) location model, this paper investigates the effects of backup service level, demand assignment policy, demand density, and number of facilities and their locations on the solution performance in terms of multiple metrics. For this purpose, we adopt a combined optimization and simulation approach. We will first modify the classic pMP to account for distances to backup services. Next, we employ a discrete event simulation to evaluate the performance of location schemes obtained from the deterministic mathematical model. Our results provide insights for decision-makers while planning ESS operations.     

Approximate dynamic programming for capacity allocation in the service industry

We consider a problem where different classes of customers can book different types of service in advance and the service company has to respond immediately to the booking request confirming or rejecting it. The objective of the service company is to maximize profit made of class-type specific revenues, refunds for cancellations or no-shows as well as cost of overtime. For the calculation of the latter, information on the underlying appointment schedule is required. In contrast to most models in the literature we assume that the service time of clients is stochastic and that clients might be unpunctual. Throughout the paper we will relate the problem to capacity allocation in radiology services. The problem is modeled as a continuous-time Markov decision process and solved using simulation-based approximate dynamic programming (ADP) combined with a discrete event simulation of the service period. We employ an adapted heuristic ADP algorithm from the literature and investigate on the benefits of applying ADP to this type of problem. First, we study a simplified problem with deterministic service times and punctual arrival of clients and compare the solution from the ADP algorithm to the optimal solution. We find that the heuristic ADP algorithm performs very well in terms of objective function value, solution time, and memory requirements. Second, we study the problem with stochastic service times and unpunctuality. It is then shown that the resulting policy constitutes a large improvement over an “optimal” policy that is deduced using restrictive, simplifying assumptions.     

具有第二次多选择服务的M[X]/G/1排队系统

本文研究成批到达的具有第二次多选择服务的单服务员排队系统．顾客的到达形成一广义泊松过程，不同批的顾客按先到先服务的规则，而同一批的顾客按随机次序接受服务．两次服务的服务时间都是一般分布且相互独立．本文采用补充变量法，求得在瞬态和稳态情况下系统队长的概率母函数，然后又计算出顾客的平均队长和平均等待时间．     

Quantile regression for index tracking and enhanced indexation

Quantile regression differs from traditional least-squares regression in that one constructs regression lines for the quantiles of the dependent variable in terms of the independent variable. In this paper we apply quantile regression to two problems in financial portfolio construction, index tracking and enhanced indexation. Index tracking is the problem of reproducing the performance of a stock market index, but without purchasing all of the stocks that make up the index. Enhanced indexation deals with the problem of out-performing the index. We present a mixed-integer linear programming formulation of these problems based on quantile regression. Our formulation includes transaction costs, a constraint limiting the number of stocks that can be in the portfolio and a limit on the total transaction cost that can be incurred. Numeric results are presented for eight test problems drawn from major world markets, where the largest of these test problems involves over 2000 stocks.     

Approximation and contamination bounds for probabilistic programs

In many applications of manufacturing and service industries, the quality of a process is characterized by the functional relationship between a response variable and one or more explanatory variables. Profile monitoring is for checking the stability of this relationship over time. In some situations, multiple profiles are required in order to model the quality of a product or process effectively. General multivariate linear profile monitoring is particularly useful in practice due to its simplicity and flexibility. However, in such situations, the existing parametric profile monitoring methods suffer from a drawback in that when the profile parameter dimensionality is large, the detection ability of the procedures commonly used T ²-type charting statistics is likely to decline substantially. Moreover, it is also challenging to isolate the type of profile parameter change in such high-dimensional circumstances. These issues actually inherit from those of the conventional multivariate control charts. To resolve these issues, this paper develops a new methodology for monitoring general multivariate linear profiles, including the regression coefficients and profile variation. After examining the connection between the parametric profile monitoring and multivariate statistical process control, we propose to apply a variable-selection-based multivariate control scheme to the transformations of estimated profile parameters. Our proposed control chart is capable of determining the shift direction automatically based on observed profile data. Thus, it offers a balanced protection against various profile shifts. Moreover, the proposed control chart provides an easy but quite effective diagnostic aid. A real-data example from the logistics service shows that it performs quite well in the application.     

Customer selection problem with profit from a sideline

This paper deals with the problem of selecting profitable orders to accept out of customers sequentially arriving at companies operating in service industries which provide specialized services designed to meet the various needs of their customers. When all the orders accepted up to a point of time are completed and delivered, the companies provide subsidiary services as a sideline in order to prevent their system from being idle, and to yield extra income, referred to as the profit from a sideline. Further, a cost is paid to search for customers, called the search cost. We discuss the admission control problem and pricing control problem in an identical framework. Properties of the optimal decision rule maximizing the total expected present discounted net profit gained over an infinite planning horizon are examined and clarified. It is shown that when the profit from the sideline is large, the optimal policies may not be monotone in the number of orders in the system.     

Simulation based analysis of patient arrival to health care systems and evaluation of an operations improvement scheme

Various demands of different patients over both medical resource and time domains in health care systems raise requests of strategies for balanced system capacity from an operations perspective. In this paper, a quantitative modeling technique with both patient arrival and associated treatment process integrated are used to characterize health care system performance and evaluate system efficiency. The patient arrival process is described as a dynamic random Poisson process and patient treatments are characterized as consumption processes of various health care resources over time with a view of the “product line” used. The waiting time of patients and usage of health care resources are proposed as system performance measures based on their means, variances, and confidence intervals. A simulation considering patients with several various diseases is given to find a mechanism of conflicting factors in decisions of balanced system capacity, and an operation scheme of “evenly balanced load for bottlenecks” is obtained based on analysis of simulation outputs. Simul8 provides the software environment for the simulation.