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We describe two stochastic network interdiction models for thwarting nuclear smuggling. In the first model, the smuggler travels through a transportation network on a path that maximizes the probability of evading detection, and the interdictor installs radiation sensors to minimize that evasion probability. The problem is stochastic because the smuggler's origin-destination pair is known only through a probability distribution at the time when the sensors are installed. In this model, the smuggler knows the locations of all sensors and the interdictor and the smuggler 'agree' on key network parameters, namely the probabilities the smuggler will be detected while traversing the arcs of the transportation network. Our second model differs in that the interdictor and smuggler can have differing perceptions of these network parameters. This model captures the case in which the smuggler is aware of only a subset of the sensor locations. For both models, we develop the important special case in which the sensors can only be installed at border crossings of a single country so that the resulting model is defined on a bipartite network. In this special case, a class of valid inequalities reduces the computation time for the identical-perceptions model. Keywords: Network interdiction, integer programming, stochastic programming, 1. Introduction We develop stochastic network interdiction models designed to locate radiation sensors, which detect gamma and neutron emissions from nuclear material, at critical border crossings in the Former Soviet [...]

The construction industry in the United States and other parts of the world has been facing several challenges, including a shortage of skilled workers. A review of the relevant body of knowledge indicates that one of the key reasons for this problem is the absence of human resource management strategies for construction workers at project, corporate, regional, or industry levels. This paper addresses the issues of workforce training and allocation on construction projects. It presents a framework to optimize the investment in, and to make the best use of, the available workforce with the intent to reduce project costs and improve schedule performance. A linear program model, entitled the Optimal Workforce investment Model, is built to provide an optimization-based framework for matching supply and demand of construction labor most efficiently through training, recruitment, and allocation. Given a project schedule or demand profile and the available pool of workers, the suggested model provides human resource managers a combined strategy for training the available workers and hiring additional workers. The input data to the proposed model consists of a certain available labor pool, cost figures for training workers in different skills, the cost of hiring workers, hourly labor wages, and estimates of affinities between the different considered skills. The objective of the model is to minimize labor costs while satisfying project labor demands. Results from application of the model to typical situations are presented, and recommendations for future developments are made. CE Database subject headings: Construction industry: Optimization: Training; Employees; Computer programming.

Bayesian forecasting models provide distributional estimates for random parameters, and relative to classical schemes, have the advantage that they can rapidly capture changes in nonstationary systems using limited historical data. Unlike deterministic optimization, stochastic programs explicitly incorporate distributions for random parameters in the model formulation, and thus have the advantage that the resulting solutions more fully hedge against future contingencies. In this paper, we exploit the strengths of Bayesian prediction and stochastic programming in a rolling-horizon approach that can be applied to solve real-world problems. We illustrate the methodology on an employee production scheduling problem with uncertain up-times of manufacturing equipment and uncertain production rates. Computational results indicate the value of our approach., 1. Introduction We consider a production planning problem in which a nominal weekday employee schedule is published at the beginning of each month in the face of uncertain production rates [...]

Given an undirected graph with positive weights on the edges we study a parametric biobjective graph clustering problem. We remove a subset of edges to break the graph into smaller pieces, that is, connected components, or clusters. We seek to maximize the number of clusters while minimizing the weight of the removed edges. We identify nested solutions that lie on the concave envelope of the efficient frontier, yielding a hierarchical family of clusters, in strongly polynomial time. We demonstrate the performance of our approach on a graph defined by the schedule of football teams within the National Collegiate Athletic Association, which has a known hierarchical structure, and on a set of synthetic graphs generated from a stochastic block model with embedded hierarchical structure. [ABSTRACT FROM AUTHOR]

Multiskilling is a workforce strategy that has been shown to reduce indirect labor costs, improve productivity, and reduce turnover. A multiskilled workforce is one in which the workers possess a range of skills that allow them to participate in more than one work process. In practice, they may work across craft boundaries. The success of multiskilling greatly relies on the foreman's ability to assign workers to appropriate tasks and to compose crews effectively. The foreman assigns tasks to workers according to their knowledge, capabilities, and experience on former projects. This research investigated the mechanics of allocating a multiskilled workforce and developed a linear programming model to help optimize the multiskilled workforce assignment and allocation process in a construction project, or between the projects of one company. It is concluded that the model will be most useful in conditions where full employment does not exist; however, it is also useful for short term allocation decisions. By running the model for various simulated scenarios, additional observations were made. For example, it is concluded that, for a capital project, the benefits of multiskilling are marginal beyond approximately a 20% concentration of multiskilled workers in a project workforce. Benefits to workers themselves become marginal after acquiring competency in two or three crafts. These observations have been confirmed by field experience. Extension of this model to allocation of multifunctional resources, such as construction equipment, should also be possible. DOI: 10.1061/(ASCE)0733-9364(2002)128:2(103) CE Database keywords: Construction industry; Personnel management; Optimization.

• Few studies examine nursing home readiness for standardized infection reporting. • This study examined facilitators and challenges that influence NHSN enrollment. • Self-perceived capabilities were associated with shorter time to NHSN enrollment. • Most implementation challenges related to insufficient staff time and resources. • Nursing homes valued externally-facilitated implementation during NHSN enrollment. Standardized measurement of health care-associated infections is essential to improving nursing home (NH) resident safety, however voluntary enrollment of NHs in Centers for Disease Control and Prevention's National Healthcare Safety Network (NHSN) requires several steps. We sought to prospectively identify NH structural, process or staff characteristics that affect enrollment and data submission among a cohort of NHs receiving facilitated implementation. The evaluation employed a mixed methods approach. The meta-theoretical Consolidated Framework for Implementation Research was used to analyze reported facilitators and challenges. Primary and secondary outcomes were time to NHSN enrollment and data submission, respectively. Of 36 participating NHs, 27 (75%) completed NHSN enrollment and 21 (58%) submitted 1 or more months of infection data during the 8-month study period. Mean days to complete enrollment was 82 (standard deviation [SD] = 24, range = 51-139) and days to first data submission was 112 (SD = 45, range = 71-245). Characteristics of NH staff liaisons associated with shorter time to enrollment included infection prevention and control knowledge, personal confidence, and responsibility for infection prevention and control activities. Facility characteristics were not associated with outcomes. Time to NHSN enrollment and submission related more to characteristics of the person leading the process than to characteristics of the NH. External partnerships that provide real-time support and resources are important assets in promoting successful NH participation in NHSN. [ABSTRACT FROM AUTHOR]

Defined contribution (DC) pension plans have been gaining ground in the last 10–20 years as the preferred system for many countries and other agencies, both private and public. The central question for a DC plan is how to invest in order to reach the participant's retirement goals. Given the financial illiteracy of the general population, it is common to offer a default policy for members who do not actively make investment choices. Using data from the Chilean system, we discuss an investment model with fixed contribution rates and compare the results with the existing default policy under multiple objectives. Our results indicate that the Chilean default policy has good overall performance, but specific closed-loop policies have a higher probability of achieving desired retirement goals and can reduce the expected shortfall at retirement. [ABSTRACT FROM AUTHOR]

Background: Job satisfaction is influenced by factors that are interpersonal (between nurse and colleagues), intrapersonal (within the nurse) and extra-personal (external to the nurse). Aim: The primary objective of this study was to explore and describe factors influencing the job satisfaction of registered nurses in a particular private critical care unit. The second objective was to make recommendations to enhance the job satisfaction of registered nurses in this private critical care unit. Setting: The population consisted of registered nurses in a private critical care unit in the Eastern Cape. Methods: This study utilised a quantitative descriptive design. Self-administered questionnaires were distributed amongst registered nurses in the critical care unit. Data were analysed and illustrated through tables. Results: Altogether, 39 registered nurses took part in the study. The majority of the participants (82%; n = 32) indicated that they enjoyed working with their team members. In addition, it was apparent that the majority (79%; n = 30) felt that they were sufficiently trained. Staff members felt that they had management support and felt satisfied at their workplace. Areas of concern included salaries, leave, debriefing and recognition. Conclusion: The majority of the registered nurses in this private critical care unit were extremely satisfied with their job. However, there were areas where this could be improved. The high levels of satisfaction at this single critical care unit lead to the question whether this situation is common throughout the Eastern Cape, which opens the path for further research in this regard. [ABSTRACT FROM AUTHOR]

At the University of Southern California solar-access design research project, Barry Knowles and students have devised a solar envelope: the largest volumetric container over a land parcel that allows solar access to all adjacent neighbors within useful time constraints. (Author/MLF)

At the Shenandoah Solar Recreation Center in Georgia, solar energy is used not only for heating and cooling, but also for ice making. (Author/MLF)

An energy-efficient library in New Rochelle (New York) incorporates part of an old garage. The new library was developed closely with a master plan to become the central focus and cultural center intended to encourage revitalization of the decaying downtown. (Author/MLF)