Randomized Online Scheduling with Delivery Times

We study one of the most basic online scheduling models, online one machine scheduling with delivery times where jobs arrive over time. We provide the first randomized algorithm for this model, show that it is 1.55370-competitive and show that this analysis is tight. The best possible deterministic algorithm is 1.61803-competitive. Our algorithm is a distribution between two deterministic algorithms. We show that any such algorithm is no better than 1.5-competitive. To our knowledge, this is the first lower bound proof for a distribution between two deterministic algorithms.     

Context in the Risk Assessment of Digital Systems

As the use of digital computers for instrumentation and control of safety-critical systems has increased, there has been a growing debate over the issue of whether probabilistic risk assessment techniques can be applied to these systems. This debate has centered on the issue of whether software failures can be modeled probabilistically. This paper describes a context-based approach to software risk assessment that explicitly recognizes the fact that the behavior of software is not probabilistic. The source of the perceived uncertainty in its behavior results from both the input to the software as well as the application and environment in which the software is operating. Failures occur as the result of encountering some context for which the software was not properly designed, as opposed to the software simply failing randomly. The paper elaborates on the concept of error-forcing context as it applies to software. It also illustrates a methodology which utilizes event trees, fault trees, and the Dynamic Flowgraph Methodology (DFM) to identify error-forcing contexts for software in the form of fault tree prime implicants.     

Examining the link between social responsibility and decision styles

The paper examines the factors that influence socially responsible decision making by individuals. The study found four social responsibility styles: Playing it Safe, Weather The Storm, Problem to Solve, and Hope it Goes Away. These styles describe individuals on the basis of decision style, propensity for risk, and coping style. The styles explain why people with different values might come to the same decision in the same circumstances.     

Private Action for Public Good?: The Public Role of Voluntary Sector Organizations

Voluntary sector organizations claim to be private institutions acting for the public good. However, if the concept of public is disengaged from the state and connected instead to citizenship, VSOs can be shown to have both private and public origins, as well as private and public impacts. As citizens, VSOs are public organizations serving the public good through their purported representation of the people and civic leadership. The legitimacy of their assumption of these public roles remains a continuing challenge.     

Mixed Levels of Uncertainty in Complex Policy Models

The characterization and treatment of uncertainty poses special challenges when modeling indeterminate or complex coupled systems such as those involved in the interactions between human activity, climate and the ecosystem. Uncertainty about model structure may become as, or more important than, uncertainty about parameter values. When uncertainty grows so large that prediction or optimization no longer makes sense, it may still be possible to use the model as a behavioral test bed to examine the relative robustness of alternative observational and behavioral strategies. When models must be run into portions of their phase space that are not well understood, different submodels may become unreliable at different rates. A common example involves running a time stepped model far into the future. Several strategies can be used to deal with such situations. The probability of model failure can be reported as a function of time. Possible alternative surprises can be assigned probabilities, modeled separately, and combined. Finally, through the use of subjective judgments, one may be able to combine, and over time shift between models, moving from more detailed to progressively simpler order-of-magnitude models, and perhaps ultimately, on to simple bounding analysis.     

Combining Probability Distributions From Experts in Risk Analysis

This paper concerns the combination of experts' probability distributions in risk analysis, discussing a variety of combination methods and attempting to highlight the important conceptual and practical issues to be considered in designing a combination process in practice. The role of experts is important because their judgments can provide valuable information, particularly in view of the limited availability of hard data regarding many important uncertainties in risk analysis. Because uncertainties are represented in terms of probability distributions in probabilistic risk analysis (PRA), we consider expert information in terms of probability distributions. The motivation for the use of multiple experts is simply the desire to obtain as much information as possible. Combining experts' probability distributions summarizes the accumulated information for risk analysts and decision-makers. Procedures for combining probability distributions are often compartmentalized as mathematical aggregation methods or behavioral approaches, and we discuss both categories. However, an overall aggregation process could involve both mathematical and behavioral aspects, and no single process is best in all circumstances. An understanding of the pros and cons of different methods and the key issues to consider is valuable in the design of a combination process for a specific PRA. The output, a combined probability distribution, can ideally be viewed as representing a summary of the current state of expert opinion regarding the uncertainty of interest.     

A New Era in Governmental Reform: Realizing Community

The good government models of the 1990s realized a focus that included reinventing, reengineer-ing, rethinking, quality, empowerment, and devolution of the organization. These organizational reform ideologies sought to increase involvement, improve productivity, manage performance, and drive results. One essential key that has been disregarded in these government models is the involvement of community in the decision-making process. This paper points to the importance of involving and empowering citizens in the decision-making process, particularly in regard to community justice based on the notion of restorative justice system. Community justice, a modern day reform movement with international proportions, is based on the principles of empowering community, repairing harm caused by a crime or disturbance, and reducing risk to the community.     

The Changing Nature of Internal Labor Markets

Research on Internal Labor Markets (ILMs) has had enormous influence on social sciences since the seminal work by Peter Doeringer and Michael Piore, thirty years ago.This article discusses the past and current contribution of the ILM concept to the development of labor economics, organization theory and human resource management and argues that research on ILMs remains important, despite the changes occurred in the economy. Therefore, a renovated effort of theoretical and field studies is required and desirable in order to reach a better understanding of the efficiency and equity issues the knowledge economy poses to the employment relation. In fact, the emergence of a new employment contract, characterized by less sticky a relation between employer and employees asks for a major re-conceptualization of ILMs that cannot be limited to a diverse, more detailed classification, or to an update of their possible variants. Such re-conceptualizationcould be linked with the new organizational forms literature, i.e. with that body of research that models organizations as hybrids or networks.     

Performance Assessments of Nuclear Waste Repositories: A Dialogue on Their Value and Limitations

Performance Assessment (PA) is the use of mathematical models to simulate the long-term behavior of engineered and geologic barriers in a nuclear waste repository; methods of uncertainty analysis are used to assess effects of parametric and conceptual uncertainties associated with the model system upon the uncertainty in outcomes of the simulation. PA is required by the U.S. Environmental Protection Agency as part of its certification process for geologic repositories for nuclear waste. This paper is a dialogue to explore the value and limitations of PA. Two skeptics acknowledge the utility of PA in organizing the scientific investigations that are necessary for confident siting and licensing of a repository; however, they maintain that the PA process, at least as it is currently implemented, is an essentially unscientific process with shortcomings that may provide results of limited use in evaluating actual effects on public health and safety. Conceptual uncertainties in a PA analysis can be so great that results can be confidently applied only over short time ranges, the antithesis of the purpose behind long-term, geologic disposal. Two proponents of PA agree that performance assessment is unscientific, but only in the sense that PA is an engineering analysis that uses existing scientific knowledge to support public policy decisions, rather than an investigation intended to increase fundamental knowledge of nature; PA has different goals and constraints than a typical scientific study. The proponents describe an ideal, six-step process for conducting generalized PA, here called probabilistic systems analysis (PSA); they note that virtually all scientific content of a PA is introduced during the model-building steps of a PSA; they contend that a PA based on simple but scientifically acceptable mathematical models can provide useful and objective input to regulatory decision makers. The value of the results of any PA must lie between these two views and will depend on the level of knowledge of the site, the degree to which models capture actual physical and chemical processes, the time over which extrapolations are made, and the proper evaluation of health risks attending implementation of the repository. The challenge is in evaluating whether the quality of the PA matches the needs of decision makers charged with protecting the health and safety of the public.     

Evaluation of the Uncertainty in an Oral Reference Dose for Methylmercury Due to Interindividual Variability in Pharmacokinetics

An analysis of the uncertainty in guidelines for the ingestion of methylmercury (MeHg) due to human pharmacokinetic variability was conducted using a physiologically based pharmacokinetic (PBPK) model that describes MeHg kinetics in the pregnant human and fetus. Two alternative derivations of an ingestion guideline for MeHg were considered: the U.S. Environmental Protection Agency reference dose (RfD) of 0.1 g/kg/day derived from studies of an Iraqi grain poisoning episode, and the Agency for Toxic Substances and Disease Registry chronic oral minimal risk level (MRL) of 0.5 g/kg/day based on studies of a fish-eating population in the Seychelles Islands. Calculation of an ingestion guideline for MeHg from either of these epidemiological studies requires calculation of a dose conversion factor (DCF) relating a hair mercury concentration to a chronic MeHg ingestion rate. To evaluate the uncertainty in this DCF across the population of U.S. women of child-bearing age, Monte Carlo analyses were performed in which distributions for each of the parameters in the PBPK model were randomly sampled 1000 times. The 1st and 5th percentiles of the resulting distribution of DCFs were a factor of 1.8 and 1.5 below the median, respectively. This estimate of variability is consistent with, but somewhat less than, previous analyses performed with empirical, one-compartment pharmacokinetic models. The use of a consistent factor in both guidelines of 1.5 for pharmacokinetic variability in the DCF, and keeping all other aspects of the derivations unchanged, would result in an RfD of 0.2 g/kg/day and an MRL of 0.3 g/kg/day.     

Challenges to the Acceptance of Probabilistic Risk Analysis

This paper discusses a number of the key challenges to the acceptance and application of probabilistic risk analysis (PRA). Those challenges include: (a) the extensive reliance on subjective judgment in PRA, requiring the development of guidance for the use of PRA in risk-informed regulation, and possibly the development of robust or reference prior distributions to minimize the reliance on judgment; and (b) the treatment of human performance in PRA, including not only human error per se but also management and organizational factors more broadly. All of these areas are seen as presenting interesting research challenges at the interface between engineering and other disciplines.     

Total System Performance Assessment for Waste Disposal Using a Logic Tree Approach

The Electric Power Research Institute (EPRI) has sponsored the development of a model to assess the long-term, overall performance of the candidate spent fuel and high-level radioactive waste (HLW) disposal facility at Yucca Mountain, Nevada. The model simulates the processes that lead to HLW container corrosion, HLW mobilization from the spent fuel, and transport by groundwater, and contaminated groundwater usage by future hypothetical individuals leading to radiation doses to those individuals. The model must incorporate a multitude of complex, coupled processes across a variety of technical disciplines. Furthermore, because of the very long time frames involved in the modeling effort (10⁴ years), the relative lack of directly applicable data, and many uncertainties and variabilities in those data, a probabilistic approach to model development was necessary. The developers of the model chose a logic tree approach to represent uncertainties in both conceptual models and model parameter values. The developers felt the logic tree approach was the most appropriate. This paper discusses the value and use of logic trees applied to assessing the uncertainties in HLW disposal, the components of the model, and a few of the results of that model. The paper concludes with a comparison of logic trees and Monte Carlo approaches.     

A Survey of Approaches for Assessing and Managing the Risk of Extremes

In this paper, we review methods for assessing and managing the risk of extreme events, where extreme events are defined to be rare, severe, and outside the normal range of experience of the system in question. First, we discuss several systematic approaches for identifying possible extreme events. We then discuss some issues related to risk assessment of extreme events, including what type of output is needed (e.g., a single probability vs. a probability distribution), and alternatives to the probabilistic approach. Next, we present a number of probabilistic methods. These include: guidelines for eliciting informative probability distributions from experts; maximum entropy distributions; extreme value theory; other approaches for constructing prior distributions (such as reference or noninformative priors); the use of modeling and decomposition to estimate the probability (or distribution) of interest; and bounding methods. Finally, we briefly discuss several approaches for managing the risk of extreme events, and conclude with recommendations and directions for future research.     

The Elevation of the Elite: Historical Trends and Complicity of the Masses

A small group of citizens wields significant influence in the corporate, political, and military realms of American society. This group is known in the literature as the elite. Looking at the disparity between the elite and the masses of society in terms of education, wealth, and political power, one might surmise a conspiracy against fundamental democratic principles of equality, justice, and economic fair play. This article addresses non-conspiratorial cultural-contextual factors of history, social structure, media, psychology, education, and the marketplace contributing to the elites existence. It is concluded that non-conspiratorial factors play a primary role in their rise to global influence.     

Public or Private? Public Corporations,Companies and the Decline of the Middle Ground

In the era of New Public Management in the Anglo-Saxon countries, governments have become infatuated with things private and disparaging of things public. This dramatic attitudinal shift has been reflected in the importation of private sector business method into so much of what government does, and in the championing of privatization in its various forms as a way of reducing the size and importance of public sectors. The change represents a retreat from the more traditional acceptance that a valuable social purpose was served by middle ground structures and activities located in the outer parts of these public sectors, i.e., between the highly politicised cores of government systems and the highly commercialised institutions of private enterprise. In particular, this article argues that the form of the public (or government, statutory or crown) corporation epitomised such social value, and that the state-owned company which is now so often replacing it represents an abandoning of social value.     

Multinational alliances: A note on the perception of technology executives

Multinational alliances in the 1980s came into vogue as one of the prominent instruments of corporate strategies. In the process of forging alliances, especially in the technologyintensive firms, senior technology executives such as directors of R & D often play a vital advisory role. This short paper reports the findings of survey of American technology executives. Among the findings two are noteworthy in the conceptualizations of multinational alliances: Alliances are viewed as a means to solving a firm's strategic problems, and as offering mutual learning opportunities, rather than win-win possibilities for firms entering the alliances.     

A Decision Theory Perspective on the Disposal of High-Level Radioactive Waste

In this paper the problem of high-level nuclear waste disposal is viewed as a five-stage, cascaded decision problem. The first four of these decisions having essentially been made, the work of recent years has been focused on the fifth stage, which concerns specifics of the repository design. The probabilistic performance assessment (PPA) work is viewed as the outcome prediction for this stage, and the site characterization work as the information gathering option. This brief examination of the proposed Yucca Mountain repository through a decision analysis framework resulted in three conclusions: (1) A decision theory approach to the process of selecting and characterizing Yucca Mountain would enhance public understanding of the issues and solutions to high-level waste management; (2) engineered systems are an attractive alternative to offset uncertainties in the containment capability of the natural setting and should receive greater emphasis in the design of the repository; and (3) a strategy of waste management should be adopted, as opposed to waste disposal, as it allows for incremental confirmation and confidence building of a permanent solution to the high-level waste problem.     

What Should Be the Implications of Uncertainty,Variability, and Inherent “Biases”/“Conservatism” for Risk Management Decision-Making?

This paper is a challenge from a pair of lifelong technical specialists in risk assessment for the risk-management community to better define social decision criteria for risk acceptance vs. risk control in relation to the issues of variability and uncertainty. To stimulate discussion, we offer a variety of straw man proposals about where we think variability and uncertainty are likely to matter for different types of social policy considerations in the context of a few different kinds of decisions. In particular, we draw on recent presentations of uncertainty and variability data that have been offered by EPA in the context of the consideration of revised ambient air quality standards under the Clean Air Act.     

Broadcast Routing with Minimum Wavelength Conversion in WDM Optical Networks

We consider dynamic routing of broadcast connections in WDM optical networks. Given the current network state, we want to find a minimum set of network nodes S such that a broadcast routing using only the nodes in S as wavelength conversion nodes can be found. This ensures that the average conversion delay from the source to all destinations is minimized. We refer to the problem as Broadcast Conversion Node Selection (BCNS) problem. We prove that BCNS has no polynomial-time approximation with performance ratio ln n for < 1 unless NPDTIME(n^{O(log log n)}) where n is the number of vertices in the input graph. We present a greedy approximation algorithm for BCNS that achieves approximation ratio 2+ln n. Simulation results show that the algorithm performs very well in practice, obtaining optimal solutions in most of the cases.     

On-Line Scheduling a Batch Processing System to Minimize Total Weighted Job Completion Time

Scheduling a batch processing system has been extensively studied in the last decade. A batch processing system is modelled as a machine that can process up to b jobs simultaneously as a batch. The scheduling problem involves assigning all n jobs to batches and determining the batch sequence in such a way that certain objective function of job completion times C _j is minimized. In this paper, we address the scheduling problem under the on-line setting in the sense that we construct our schedule irrevocably as time proceeds and do not know of the existence of any job that may arrive later. Our objective is to minimize the total weighted completion time w _j C _j. We provide a linear time on-line algorithm for the unrestrictive model (i.e., b n) and show that the algorithm is 10/3-competitive. For the restrictive model (i.e., b < n), we first consider the (off-line) problem of finding a maximum independent vertex set in an interval graph with cost constraint (MISCP), which is NP-hard. We give a dual fully polynomial time approximation scheme for MISCP, which leads us to a (4 + )-competitive on-line algorithm for any > 0 for the original on-line scheduling problem. These two on-line algorithms are the first deterministic algorithms of constant performance guarantees.