A simulation analysis of the impact of family configuration on virtual cellular manufacturing

Past research has shown that it is possible to simultaneously achieve the setup efficiencies of traditional cellular manufacturing systems and the routeing flexibility of a job shop by viewing cells not as permanent, physical structures, but as temporary, 'virtual' entities. This research demonstrates that the advantages of virtual manufacturing cells can be obtained over a range of part family configurations. In particular, virtual cellular manufacturing is robust to changes in the number and size of families being processed. Further, the research shows that the benefits can be obtained under setup conditions impartial to a family-oriented part environment.     

Multiobjective Decision-Tree Analysis1

Single-objective-based decision-tree analysis has been extensively and successfully used in numerous decision-making problems since its formal introduction by Howard Raiffa more than two decades ago. This paper extends the traditional methodology to incorporate multiple noncommensurate objective functions and use of the conditional expected value of the risk of extreme and catastrophic events. The proposed methodology considers the cases where (a) a finite number of actions are available at each decision node and (b) discrete or continuous states of nature can be presented at each chance node. The proposed extension of decision-tree analysis is introduced through an example problem that leads the reader step-by-step into the methodological procedure. The example problem builds on flood warning systems. Two noncommensurate objectives—the loss of lives and the loss of property (including monetary costs of the flood warning system)–are incorporated into the decision tree. In addition, two risk measures—the common expected value and the conditional expected value of extreme and catastrophic events—are quantified and are also incorporated into the decision-making process. Theoretical difficulties associated with the stage-wise calculation of conditional expected values are identified and certain simplifying assumptions are made for computational tractibility. In particular, it is revealed that decisions concerning experimentation have a very interesting impact on the noninferior solution set of options—a phenomenon that has no equivalence in the single-objective case.     

UNBIASED ESTIMATION OF PARAMETRIC FUNCTIONS IN SAMPLING FROM TWO ONE-TRUNCATION PARAMETER FAMILIES

We consider the problem of minimum variance unbiased estimation of a U-estimable function of two unknown truncation parameters based on independent random samples from two one-truncation parameter families. In particular, we obtain the UMVU estimator of the probability that Y > X.     

A comparative analysis of school-to-work transitions in the European Union1

The present paper describes some aspects of ‘school-to-work’ transition by analyzing the employment situation of individuals as a function of the time elapsed since the completion of education or training. Our perspective is interdisciplinary, comparative and dynamic, with special focus on the patterns in southern European countries. In the literature, most of the studies have had the basic approach of constructing indicators based on retrospective information on the time of first leaving continuous education, and current information on status and characteristics of the person's economic activity – expressing the status of activity as a function of the time elapsed since leaving continuous education. In this approach, essentially cross-sectional (though in part retrospective) information is interpreted as if it pertains to real cohorts. Much of this comparative analysis of school-to-work transitions in EU countries has been based on the EU Labour Force Survey, the 2000 round of which incorporated a special module to collect information on the subject. Our basic approach is to use the longitudinal data from the European Community Household Panel to identify, at the time of each wave, the person's most recently completed education and training, and study this in relation to the person's current employment situation and other characteristics as a function of the time elapsed since that completion. Hence, in form at least, our approach is similar to that of earlier studies based on the LFS, though there are considerable differences in substantive content and statistical methodology resulting from the use of different types of data. We also demonstrate how data from a panel survey may be cumulated over time to obtain a more adequate sample size.     

Intelligent Procedures for Intra‐Day Updating of Call Center Agent Schedules

For nearly all call centers, agent schedules are typically created several days or weeks before the time that agents report to work. After schedules are created, call center resource managers receive additional information that can affect forecasted workload and resource availability. In particular, there is significant evidence, both among practitioners and in the research literature, suggesting that actual call arrival volumes early in a scheduling period (typically an individual day or week) can provide valuable information about the call arrival pattern later in the same scheduling period. In this paper, we develop a flexible and powerful heuristic framework for managers to make intra‐day resource adjustment decisions that take into account updated call forecasts, updated agent requirements, existing agent schedules, agents' schedule flexibility, and associated incremental labor costs. We demonstrate the value of this methodology in managing the trade‐off between labor costs and service levels to best meet variable rates of demand for service, using data from an actual call center.     

The state and civil society in disaster response: post-tsunami experiences in Tamil Nadu

This paper, based on the report "The State and Civil Society in Disaster Response: An Analysis of the Tamil Nadu Tsunami Experience," (Srinivasan, Nagaraj, & Venkatesh, 2005) is essentially an empirical analysis of state and civil society responses in Tamil Nadu (India) to the tsunami of December 26, 2004. It examines interventions by state and non-state agencies, as well as people's experiences in the relief and rehabilitation phases to identify factors influencing both positive and negative outcomes of the tsunami response. Issues related to vulnerability and exclusion, equity, transparency and accountability in different sectors of disaster intervention are explored to highlight themes revolving around reach and efficacy of relief and recovery processes. These analyses bring out some interesting lessons with regard to the importance of institutional autonomy, non-politicized decision-making, and synergetic state-civil society interfaces in fostering inclusive, transparent and accountable rehabilitation processes. The roles played by institutional responsiveness and flexibility in shaping an effective disaster response also emerge very clearly from this study of the Tamil Nadu experience. Another crucial finding points to the need for detailed, reliable and disaggregated geo-demographic and socioeconomic records as a resource base for informing relief and rehabilitation interventions. The study draws extensively from the experiences and insights of people affected by, and involved in tsunami response, and from secondary knowledge resources available on the disaster.     

An Analysis of Manufacturer‐Retailer Supply Chain Coordination in Cooperative Advertising*

In the literature of cooperative (co‐op) advertising, the focus of the research is on a relationship in which a manufacturer is the leader and retailers are followers. This relationship implies the dominance of the manufacturer over retailers. Recent market trends have shown a shift in power from manufacturers to retailers. Retailers, as a result, may now possess equal or even greater power than a manufacturer in some instances when it comes to retailing. Based on this new market phenomenon, we intend to explore the role of co‐op advertising in a manufacturer‐retailer supply chain through brand name investments, local advertising expenditures, and sharing rules of advertising expenses. Two co‐op advertising models are developed and compared. The first co‐op advertising model is based on the traditional leader‐follower relationship of a manufacturer and a retailer. The second model incorporates partnership into co‐op advertising coordination. Business examples and managerial implications of the models have been discussed. A cooperative bargaining technique is utilized to implement the partnership co‐op advertising model.     

Uncertainty Analysis Based on Probability Bounds (P-Box) Approach in Probabilistic Safety Assessment

A wide range of uncertainties will be introduced inevitably during the process of performing a safety assessment of engineering systems. The impact of all these uncertainties must be addressed if the analysis is to serve as a tool in the decision-making process. Uncertainties present in the components (input parameters of model or basic events) of model output are propagated to quantify its impact in the final results. There are several methods available in the literature, namely, method of moments, discrete probability analysis, Monte Carlo simulation, fuzzy arithmetic, and Dempster-Shafer theory. All the methods are different in terms of characterizing at the component level and also in propagating to the system level. All these methods have different desirable and undesirable features, making them more or less useful in different situations. In the probabilistic framework, which is most widely used, probability distribution is used to characterize uncertainty. However, in situations in which one cannot specify (1) parameter values for input distributions, (2) precise probability distributions (shape), and (3) dependencies between input parameters, these methods have limitations and are found to be not effective. In order to address some of these limitations, the article presents uncertainty analysis in the context of level-1 probabilistic safety assessment (PSA) based on a probability bounds (PB) approach. PB analysis combines probability theory and interval arithmetic to produce probability boxes (p-boxes), structures that allow the comprehensive propagation through calculation in a rigorous way. A practical case study is also carried out with the developed code based on the PB approach and compared with the two-phase Monte Carlo simulation results.