Software-Engineering Process Simulation (SEPS) model

NASA Technical Reports Server (NTRS)

Lin, C. Y.; Abdel-Hamid, T.; Sherif, J. S.

1992-01-01

The Software Engineering Process Simulation (SEPS) model is described which was developed at JPL. SEPS is a dynamic simulation model of the software project development process. It uses the feedback principles of system dynamics to simulate the dynamic interactions among various software life cycle development activities and management decision making processes. The model is designed to be a planning tool to examine tradeoffs of cost, schedule, and functionality, and to test the implications of different managerial policies on a project's outcome. Furthermore, SEPS will enable software managers to gain a better understanding of the dynamics of software project development and perform postmodern assessments.

Team formation and breakup in multiagent systems

NASA Astrophysics Data System (ADS)

Rao, Venkatesh Guru

The goal of this dissertation is to pose and solve problems involving team formation and breakup in two specific multiagent domains: formation travel and space-based interferometric observatories. The methodology employed comprises elements drawn from control theory, scheduling theory and artificial intelligence (AI). The original contribution of the work comprises three elements. The first contribution, the partitioned state-space approach is a technique for formulating and solving co-ordinated motion problem using calculus of variations techniques. The approach is applied to obtain optimal two-agent formation travel trajectories on graphs. The second contribution is the class of MixTeam algorithms, a class of team dispatchers that extends classical dispatching by accommodating team formation and breakup and exploration/exploitation learning. The algorithms are applied to observation scheduling and constellation geometry design for interferometric space telescopes. The use of feedback control for team scheduling is also demonstrated with these algorithms. The third contribution is the analysis of the optimality properties of greedy, or myopic, decision-making for a simple class of team dispatching problems. This analysis represents a first step towards the complete analysis of complex team schedulers such as the MixTeam algorithms. The contributions represent an extension to the literature on team dynamics in control theory. The broad conclusions that emerge from this research are that greedy or myopic decision-making strategies for teams perform well when specific parameters in the domain are weakly affected by an agent's actions, and that intelligent systems require a closer integration of domain knowledge in decision-making functions.

Design of an Aircrew Scheduling Decision Aid for the 6916th Electronic Security Squadron.

DTIC Science & Technology

1987-06-01

Security Classification) Design of an Aircrew Scheduling Decision Aid for the 6916th Electronic Security Squadron 12. PERSONAL AUTHOR(S) Thomas J. Kopf...Because of the great number of possible scheduling alternatives, it is difficult to find an optimal solution to-the scheduling problem. Additionally...changes to the original schedule make it even more difficult to find an optimal solution. The emergence of capable microcompu- ters, decision support

Model for multi-stand management based on structural attributes of individual stands

Treesearch

G.W. Miller; J. Sullivan

1997-01-01

A growing interest in managing forest ecosystems calls for decision models that take into account attribute goals for large forest areas while continuing to recognize the individual stand as a basic unit of forest management. A dynamic, nonlinear forest management model is described that schedules silvicultural treatments for individual stands that are linked by multi-...

Automatic programming via iterated local search for dynamic job shop scheduling.

PubMed

Nguyen, Su; Zhang, Mengjie; Johnston, Mark; Tan, Kay Chen

2015-01-01

Dispatching rules have been commonly used in practice for making sequencing and scheduling decisions. Due to specific characteristics of each manufacturing system, there is no universal dispatching rule that can dominate in all situations. Therefore, it is important to design specialized dispatching rules to enhance the scheduling performance for each manufacturing environment. Evolutionary computation approaches such as tree-based genetic programming (TGP) and gene expression programming (GEP) have been proposed to facilitate the design task through automatic design of dispatching rules. However, these methods are still limited by their high computational cost and low exploitation ability. To overcome this problem, we develop a new approach to automatic programming via iterated local search (APRILS) for dynamic job shop scheduling. The key idea of APRILS is to perform multiple local searches started with programs modified from the best obtained programs so far. The experiments show that APRILS outperforms TGP and GEP in most simulation scenarios in terms of effectiveness and efficiency. The analysis also shows that programs generated by APRILS are more compact than those obtained by genetic programming. An investigation of the behavior of APRILS suggests that the good performance of APRILS comes from the balance between exploration and exploitation in its search mechanism.

A hybrid online scheduling mechanism with revision and progressive techniques for autonomous Earth observation satellite

NASA Astrophysics Data System (ADS)

Li, Guoliang; Xing, Lining; Chen, Yingwu

2017-11-01

The autonomicity of self-scheduling on Earth observation satellite and the increasing scale of satellite network attract much attention from researchers in the last decades. In reality, the limited onboard computational resource presents challenge for the online scheduling algorithm. This study considered online scheduling problem for a single autonomous Earth observation satellite within satellite network environment. It especially addressed that the urgent tasks arrive stochastically during the scheduling horizon. We described the problem and proposed a hybrid online scheduling mechanism with revision and progressive techniques to solve this problem. The mechanism includes two decision policies, a when-to-schedule policy combining periodic scheduling and critical cumulative number-based event-driven rescheduling, and a how-to-schedule policy combining progressive and revision approaches to accommodate two categories of task: normal tasks and urgent tasks. Thus, we developed two heuristic (re)scheduling algorithms and compared them with other generally used techniques. Computational experiments indicated that the into-scheduling percentage of urgent tasks in the proposed mechanism is much higher than that in periodic scheduling mechanism, and the specific performance is highly dependent on some mechanism-relevant and task-relevant factors. For the online scheduling, the modified weighted shortest imaging time first and dynamic profit system benefit heuristics outperformed the others on total profit and the percentage of successfully scheduled urgent tasks.

Completable scheduling: An integrated approach to planning and scheduling

NASA Technical Reports Server (NTRS)

Gervasio, Melinda T.; Dejong, Gerald F.

1992-01-01

The planning problem has traditionally been treated separately from the scheduling problem. However, as more realistic domains are tackled, it becomes evident that the problem of deciding on an ordered set of tasks to achieve a set of goals cannot be treated independently of the problem of actually allocating resources to the tasks. Doing so would result in losing the robustness and flexibility needed to deal with imperfectly modeled domains. Completable scheduling is an approach which integrates the two problems by allowing an a priori planning module to defer particular planning decisions, and consequently the associated scheduling decisions, until execution time. This allows a completable scheduling system to maximize plan flexibility by allowing runtime information to be taken into consideration when making planning and scheduling decision. Furthermore, through the criteria of achievability placed on deferred decision, a completable scheduling system is able to retain much of the goal-directedness and guarantees of achievement afforded by a priori planning. The completable scheduling approach is further enhanced by the use of contingent explanation-based learning, which enables a completable scheduling system to learn general completable plans from example and improve its performance through experience. Initial experimental results show that completable scheduling outperforms classical scheduling as well as pure reactive scheduling in a simple scheduling domain.

A Decision Tool that Combines Discrete Event Software Process Models with System Dynamics Pieces for Software Development Cost Estimation and Analysis

NASA Technical Reports Server (NTRS)

Mizell, Carolyn Barrett; Malone, Linda

2007-01-01

The development process for a large software development project is very complex and dependent on many variables that are dynamic and interrelated. Factors such as size, productivity and defect injection rates will have substantial impact on the project in terms of cost and schedule. These factors can be affected by the intricacies of the process itself as well as human behavior because the process is very labor intensive. The complex nature of the development process can be investigated with software development process models that utilize discrete event simulation to analyze the effects of process changes. The organizational environment and its effects on the workforce can be analyzed with system dynamics that utilizes continuous simulation. Each has unique strengths and the benefits of both types can be exploited by combining a system dynamics model and a discrete event process model. This paper will demonstrate how the two types of models can be combined to investigate the impacts of human resource interactions on productivity and ultimately on cost and schedule.

Workflow management in large distributed systems

NASA Astrophysics Data System (ADS)

Legrand, I.; Newman, H.; Voicu, R.; Dobre, C.; Grigoras, C.

2011-12-01

The MonALISA (Monitoring Agents using a Large Integrated Services Architecture) framework provides a distributed service system capable of controlling and optimizing large-scale, data-intensive applications. An essential part of managing large-scale, distributed data-processing facilities is a monitoring system for computing facilities, storage, networks, and the very large number of applications running on these systems in near realtime. All this monitoring information gathered for all the subsystems is essential for developing the required higher-level services—the components that provide decision support and some degree of automated decisions—and for maintaining and optimizing workflow in large-scale distributed systems. These management and global optimization functions are performed by higher-level agent-based services. We present several applications of MonALISA's higher-level services including optimized dynamic routing, control, data-transfer scheduling, distributed job scheduling, dynamic allocation of storage resource to running jobs and automated management of remote services among a large set of grid facilities.

An Examination of Virginia Elementary School Principals' Scheduling Decisions Regarding Opportunities for Students to Participate in Physical Activity during the School Day

ERIC Educational Resources Information Center

Greve, Andrew W.

2017-01-01

The principal is ultimately responsible for decisions regarding the master schedule at the elementary level of education (Canady & Rettig, 2013; Young, 2008), and these scheduling decisions are influenced by multiple factors (Benamati, 2010; Harris, 2013; Howard & Rakoz, 2009). Although principals have become increasingly aware of the need…

Toward interactive scheduling systems for managing medical resources.

PubMed

Oddi, A; Cesta, A

2000-10-01

Managers of medico-hospital facilities are facing two general problems when allocating resources to activities: (1) to find an agreement between several and contrasting requirements; (2) to manage dynamic and uncertain situations when constraints suddenly change over time due to medical needs. This paper describes the results of a research aimed at applying constraint-based scheduling techniques to the management of medical resources. A mixed-initiative problem solving approach is adopted in which a user and a decision support system interact to incrementally achieve a satisfactory solution to the problem. A running prototype is described called Interactive Scheduler which offers a set of functionalities for a mixed-initiative interaction to cope with the medical resource management. Interactive Scheduler is endowed with a representation schema used for describing the medical environment, a set of algorithms that address the specific problems of the domain, and an innovative interaction module that offers functionalities for the dialogue between the support system and its user. A particular contribution of this work is the explicit representation of constraint violations, and the definition of scheduling algorithms that aim at minimizing the amount of constraint violations in a solution.

Fair Energy Scheduling for Vehicle-to-Grid Networks Using Adaptive Dynamic Programming.

PubMed

Xie, Shengli; Zhong, Weifeng; Xie, Kan; Yu, Rong; Zhang, Yan

2016-08-01

Research on the smart grid is being given enormous supports worldwide due to its great significance in solving environmental and energy crises. Electric vehicles (EVs), which are powered by clean energy, are adopted increasingly year by year. It is predictable that the huge charge load caused by high EV penetration will have a considerable impact on the reliability of the smart grid. Therefore, fair energy scheduling for EV charge and discharge is proposed in this paper. By using the vehicle-to-grid technology, the scheduler controls the electricity loads of EVs considering fairness in the residential distribution network. We propose contribution-based fairness, in which EVs with high contributions have high priorities to obtain charge energy. The contribution value is defined by both the charge/discharge energy and the timing of the action. EVs can achieve higher contribution values when discharging during the load peak hours. However, charging during this time will decrease the contribution values seriously. We formulate the fair energy scheduling problem as an infinite-horizon Markov decision process. The methodology of adaptive dynamic programming is employed to maximize the long-term fairness by processing online network training. The numerical results illustrate that the proposed EV energy scheduling is able to mitigate and flatten the peak load in the distribution network. Furthermore, contribution-based fairness achieves a fast recovery of EV batteries that have deeply discharged and guarantee fairness in the full charge time of all EVs.

Realization of high quality production schedules: Structuring quality factors via iteration of user specification processes

NASA Technical Reports Server (NTRS)

Hamazaki, Takashi

1992-01-01

This paper describes an architecture for realizing high quality production schedules. Although quality is one of the most important aspects of production scheduling, it is difficult, even for a user, to specify precisely. However, it is also true that the decision as to whether a scheduler is good or bad can only be made by the user. This paper proposes the following: (1) the quality of a schedule can be represented in the form of quality factors, i.e. constraints and objectives of the domain, and their structure; (2) quality factors and their structure can be used for decision making at local decision points during the scheduling process; and (3) that they can be defined via iteration of user specification processes.

Scheduling unplanned surgery: a tool for improving dialogue about queue position on emergency theatre lists.

PubMed

Fitzgerald, Janna; Lum, Martin; Dadich, Ann

2006-05-01

Theatre use is heavily influenced by the presentation and scheduling of emergency cases for unplanned surgery. This research guided the development of a triage standard for scheduling emergency surgery in New South Wales public hospitals and aimed to contribute to a better understanding of decision-making practices. An emergency-surgery survey asked questions about urgency of a set of clinical conditions and appropriate time frames for patients to receive surgical treatment for these conditions. Surveys were distributed via 71 NSW public hospitals. A total of 198 decision makers responded: surgeons (42.8%), anaesthetists (24.7%), and nurses (32.5%). Principal component analysis was applied to reduce the data to three urgency classifications, and analysis of variance was used to assess variance of opinions between professional groups. The data suggested that the parameters that distinguish the codes (1, very urgent; 2, semi-urgent; 3, least urgent) were not unequivocally apparent. Although there was a consistent approach to the "urgency 1" and "urgency 3" categories, there were significant differences between responses when determining "urgency 2". The data indicated that when making decisions, anaesthetists act as intermediaries between surgeons and nurses. There was significant disparity between individuals when respondents were asked to state an ideal time for the commencement of surgery and the maximum length of time that the surgery could wait. This presented a need for a risk assessment tool to be incorporated when developing a dynamic prototype triage instrument.

The temporal dynamics of ambivalence: changes in positive and negative affect in relation to consumption of an "emotionally charged" food.

PubMed

Hormes, Julia M; Rozin, Paul

2011-08-01

Ambivalence is thought to impact consumption of food, alcohol and drugs, possibly via influences on craving, with cravers often being simultaneously drawn toward and repelled from ingestion. So far, little is known about the temporal dynamics of ambivalence, especially as it varies in relationship to consumption. Participants (n=482, 56.8% female) completed the Positive and Negative Affect Schedule prior to, immediately and 30 min after the opportunity to eat a bar of chocolate. Affective ambivalence was calculated based on the relative strengths of and discrepancy between ratings of positive and negative affect. Ambivalence peaked prior to a decision about consumption and subsequently decreased, whether or not the decision was in favor of or against consuming. Decreasing ambivalence was driven by a drop in positive affect over time; positivity decreased more rapidly in those who consumed chocolate. Findings represent a first step in characterizing the dynamics of ambivalence in interactions with a target stimulus. Copyright © 2011 Elsevier Ltd. All rights reserved.

Re-scheduling as a tool for the power management on board a spacecraft

NASA Technical Reports Server (NTRS)

Albasheer, Omar; Momoh, James A.

1995-01-01

The scheduling of events on board a spacecraft is based on forecast energy levels. The real time values of energy may not coincide with the forecast values; consequently, a dynamic revising to the allocation of power is needed. The re-scheduling is also needed for other reasons on board a spacecraft like the addition of new event which must be scheduled, or a failure of an event due to many different contingencies. This need of rescheduling is very important to the survivability of the spacecraft. In this presentation, a re-scheduling tool will be presented as a part of an overall scheme for the power management on board a spacecraft from the allocation of energy point of view. The overall scheme is based on the optimal use of energy available on board a spacecraft using expert systems combined with linear optimization techniques. The system will be able to schedule maximum number of events utilizing most energy available. The outcome is more events scheduled to share the operation cost of that spacecraft. The system will also be able to re-schedule in case of a contingency with minimal time and minimal disturbance of the original schedule. The end product is a fully integrated planning system capable of producing the right decisions in short time with less human error. The overall system will be presented with the re-scheduling algorithm discussed in detail, then the tests and results will be presented for validations.

Forest management and economics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Buongiorno, J.; Gilless, J.K.

1987-01-01

This volume provides a survey of quantitative methods, guiding the reader through formulation and analysis of models that address forest management problems. The authors use simple mathematics, graphics, and short computer programs to explain each method. Emphasizing applications, they discuss linear, integer, dynamic, and goal programming; simulation; network modeling; and econometrics, as these relate to problems of determining economic harvest schedules in even-aged and uneven-aged forests, the evaluation of forest policies, multiple-objective decision making, and more.

Sleep pattern and decision-making in physicians from mobile emergency care service with 12-h work schedules.

PubMed

Castro, Eleni de Araújo Sales; de Almondes, Katie Moraes

2018-06-01

Shift work schedules are biological standpoint worse because compel the body to anticipate periods of wakefulness and sleep and thus eventually cause a disruption of biological rhythms. The objective of this study is to evaluate the sleep pattern and decision-making in physicians working in mobile units of emergency attention undergoing day shift and rotating shift. The study included 26 physicians. The instruments utilized were a sociodemographic questionnaire, the Pittsburgh Sleep Quality Index, the Sleep Habits Questionnaire, the Epworth Sleepiness Scale and Chronotype Identification Questionnaire of Horne-Ostberg, the Iowa Gambling Task (IGT) and hypothetical scenarios of decision-making created according to the Policy-Capturing Technique. For inclusion and exclusion criteria, the participants answered the Chalder Fatigue Scale, the Beck Anxiety Inventory, the Beck Depression Inventory and the Inventory of Stress Symptoms for adults of Lipp. It was found good sleep quality for physicians on day shift schedule and bad sleep quality for physicians on rotating shift schedule. The IGT measure showed no impairment in decision-making, but the hypothetical scenarios revealed impairment decision-making during the shift for both schedules. Good sleep quality was related to a better performance in decision-making. Good sleep quality seems to influence a better performance in decision-making.

Management of Temporal Constraints for Factory Scheduling.

DTIC Science & Technology

1987-06-01

consistency of scheduling decisions were implemented in both the ISIS [Fox 84] and SOJA [LePape 85a] scheduling systems. More recent work with the...kinds of time propagation systems: the symbolic and the numeric ones. Symbolic systems combine relationships with a temporal logic a la Allen [Allen 81...maintains consistency by narrowing time windows associated with activities as decisions are made, and SOJA [LePape 85b] guarantees a schedule’s

A hybrid flowshop scheduling model considering dedicated machines and lot-splitting for the solar cell industry

NASA Astrophysics Data System (ADS)

Wang, Li-Chih; Chen, Yin-Yann; Chen, Tzu-Li; Cheng, Chen-Yang; Chang, Chin-Wei

2014-10-01

This paper studies a solar cell industry scheduling problem, which is similar to traditional hybrid flowshop scheduling (HFS). In a typical HFS problem, the allocation of machine resources for each order should be scheduled in advance. However, the challenge in solar cell manufacturing is the number of machines that can be adjusted dynamically to complete the job. An optimal production scheduling model is developed to explore these issues, considering the practical characteristics, such as hybrid flowshop, parallel machine system, dedicated machines, sequence independent job setup times and sequence dependent job setup times. The objective of this model is to minimise the makespan and to decide the processing sequence of the orders/lots in each stage, lot-splitting decisions for the orders and the number of machines used to satisfy the demands in each stage. From the experimental results, lot-splitting has significant effect on shortening the makespan, and the improvement effect is influenced by the processing time and the setup time of orders. Therefore, the threshold point to improve the makespan can be identified. In addition, the model also indicates that more lot-splitting approaches, that is, the flexibility of allocating orders/lots to machines is larger, will result in a better scheduling performance.

Multi-criteria evaluation methods in the production scheduling

NASA Astrophysics Data System (ADS)

Kalinowski, K.; Krenczyk, D.; Paprocka, I.; Kempa, W.; Grabowik, C.

2016-08-01

The paper presents a discussion on the practical application of different methods of multi-criteria evaluation in the process of scheduling in manufacturing systems. Among the methods two main groups are specified: methods based on the distance function (using metacriterion) and methods that create a Pareto set of possible solutions. The basic criteria used for scheduling were also described. The overall procedure of evaluation process in production scheduling was presented. It takes into account the actions in the whole scheduling process and human decision maker (HDM) participation. The specified HDM decisions are related to creating and editing a set of evaluation criteria, selection of multi-criteria evaluation method, interaction in the searching process, using informal criteria and making final changes in the schedule for implementation. According to need, process scheduling may be completely or partially automated. Full automatization is possible in case of metacriterion based objective function and if Pareto set is selected - the final decision has to be done by HDM.

Research on Production Scheduling System with Bottleneck Based on Multi-agent

NASA Astrophysics Data System (ADS)

Zhenqiang, Bao; Weiye, Wang; Peng, Wang; Pan, Quanke

Aimed at the imbalance problem of resource capacity in Production Scheduling System, this paper uses Production Scheduling System based on multi-agent which has been constructed, and combines the dynamic and autonomous of Agent; the bottleneck problem in the scheduling is solved dynamically. Firstly, this paper uses Bottleneck Resource Agent to find out the bottleneck resource in the production line, analyses the inherent mechanism of bottleneck, and describes the production scheduling process based on bottleneck resource. Bottleneck Decomposition Agent harmonizes the relationship of job's arrival time and transfer time in Bottleneck Resource Agent and Non-Bottleneck Resource Agents, therefore, the dynamic scheduling problem is simplified as the single machine scheduling of each resource which takes part in the scheduling. Finally, the dynamic real-time scheduling problem is effectively solved in Production Scheduling System.

Registration Review Schedules

EPA Pesticide Factsheets

This schedule indicates plans for completion of risk assessments, proposed interim decisions and interim decisions for pesticides in the Registration Review program, EPA reviews all registered pesticides at least every 15 years as required by FIFRA.

Automated Image Intelligence Adaptive Sensor Management System for High Altitude Long Endurance UAVs in a Dynamic and Anti-Access Area Denial Environment

NASA Astrophysics Data System (ADS)

Kim, Gi Young

The problem we investigate deals with an Image Intelligence (IMINT) sensor allocation schedule for High Altitude Long Endurance UAVs in a dynamic and Anti-Access Area Denial (A2AD) environment. The objective is to maximize the Situational Awareness (SA) of decision makers. The value of SA can be improved in two different ways. First, if a sensor allocated to an Areas of Interest (AOI) detects target activity, then the SA value will be increased. Second, the SA value increases if an AOI is monitored for a certain period of time, regardless of target detections. These values are functions of the sensor allocation time, sensor type and mode. Relatively few studies in the archival literature have been devoted to an analytic, detailed explanation of the target detection process, and AOI monitoring value dynamics. These two values are the fundamental criteria used to choose the most judicious sensor allocation schedule. This research presents mathematical expressions for target detection processes, and shows the monitoring value dynamics. Furthermore, the dynamics of target detection is the result of combined processes between belligerent behavior (target activity) and friendly behavior (sensor allocation). We investigate these combined processes and derive mathematical expressions for simplified cases. These closed form mathematical models can be used for Measures of Effectiveness (MOEs), i.e., target activity detection to evaluate sensor allocation schedules. We also verify these models with discrete event simulations which can also be used to describe more complex systems. We introduce several methodologies to achieve a judicious sensor allocation schedule focusing on the AOI monitoring value. The first methodology is a discrete time integer programming model which provides an optimal solution but is impractical for real world scenarios due to its computation time. Thus, it is necessary to trade off the quality of solution with computation time. The Myopic Greedy Procedure (MGP) is a heuristic which chooses the largest immediate unit time return at each decision epoch. This reduces computation time significantly, but the quality of the solution may be only 95% of optimal (for small size problems). Another alternative is a multi-start random constructive Hybrid Myopic Greedy Procedure (H-MGP), which incorporates stochastic variation in choosing an action at each stage, and repeats it a predetermined number of times (roughly 99.3% of optimal with 1000 repetitions). Finally, the One Stage Look Ahead (OSLA) procedure considers all the 'top choices' at each stage for a temporary time horizon and chooses the best action (roughly 98.8% of optimal with no repetition). Using OSLA procedure, we can have ameliorated solutions within a reasonable computation time. Other important issues discussed in this research are methodologies for the development of input parameters for real world applications.

A Dynamic Scheduling Method of Earth-Observing Satellites by Employing Rolling Horizon Strategy

PubMed Central

Dishan, Qiu; Chuan, He; Jin, Liu; Manhao, Ma

2013-01-01

Focused on the dynamic scheduling problem for earth-observing satellites (EOS), an integer programming model is constructed after analyzing the main constraints. The rolling horizon (RH) strategy is proposed according to the independent arriving time and deadline of the imaging tasks. This strategy is designed with a mixed triggering mode composed of periodical triggering and event triggering, and the scheduling horizon is decomposed into a series of static scheduling intervals. By optimizing the scheduling schemes in each interval, the dynamic scheduling of EOS is realized. We also propose three dynamic scheduling algorithms by the combination of the RH strategy and various heuristic algorithms. Finally, the scheduling results of different algorithms are compared and the presented methods in this paper are demonstrated to be efficient by extensive experiments. PMID:23690742

A dynamic scheduling method of Earth-observing satellites by employing rolling horizon strategy.

PubMed

Dishan, Qiu; Chuan, He; Jin, Liu; Manhao, Ma

2013-01-01

Focused on the dynamic scheduling problem for earth-observing satellites (EOS), an integer programming model is constructed after analyzing the main constraints. The rolling horizon (RH) strategy is proposed according to the independent arriving time and deadline of the imaging tasks. This strategy is designed with a mixed triggering mode composed of periodical triggering and event triggering, and the scheduling horizon is decomposed into a series of static scheduling intervals. By optimizing the scheduling schemes in each interval, the dynamic scheduling of EOS is realized. We also propose three dynamic scheduling algorithms by the combination of the RH strategy and various heuristic algorithms. Finally, the scheduling results of different algorithms are compared and the presented methods in this paper are demonstrated to be efficient by extensive experiments.

Using Planning, Scheduling and Execution for Autonomous Mars Rover Operations

NASA Technical Reports Server (NTRS)

Estlin, Tara A.; Gaines, Daniel M.; Chouinard, Caroline M.; Fisher, Forest W.; Castano, Rebecca; Judd, Michele J.; Nesnas, Issa A.

2006-01-01

With each new rover mission to Mars, rovers are traveling significantly longer distances. This distance increase raises not only the opportunities for science data collection, but also amplifies the amount of environment and rover state uncertainty that must be handled in rover operations. This paper describes how planning, scheduling and execution techniques can be used onboard a rover to autonomously generate and execute rover activities and in particular to handle new science opportunities that have been identified dynamically. We also discuss some of the particular challenges we face in supporting autonomous rover decision-making. These include interaction with rover navigation and path-planning software and handling large amounts of uncertainty in state and resource estimations. Finally, we describe our experiences in testing this work using several Mars rover prototypes in a realistic environment.

A Mechanized Decision Support System for Academic Scheduling.

DTIC Science & Technology

1986-03-01

an operational system called software. The first step in the development phase is Design . Designers destribute software control by factoring the Data...SUBJECT TERMS (Continue on reverse if necessary and identify by block number) ELD GROUP SUB-GROUP Scheduling, Decision Support System , Software Design ...scheduling system . It will also examine software - design techniques to identify the most appropriate method- ology for this problem. " - Chapter 3 will

A collaborative scheduling model for the supply-hub with multiple suppliers and multiple manufacturers.

PubMed

Li, Guo; Lv, Fei; Guan, Xu

2014-01-01

This paper investigates a collaborative scheduling model in the assembly system, wherein multiple suppliers have to deliver their components to the multiple manufacturers under the operation of Supply-Hub. We first develop two different scenarios to examine the impact of Supply-Hub. One is that suppliers and manufacturers make their decisions separately, and the other is that the Supply-Hub makes joint decisions with collaborative scheduling. The results show that our scheduling model with the Supply-Hub is a NP-complete problem, therefore, we propose an auto-adapted differential evolution algorithm to solve this problem. Moreover, we illustrate that the performance of collaborative scheduling by the Supply-Hub is superior to separate decision made by each manufacturer and supplier. Furthermore, we also show that the algorithm proposed has good convergence and reliability, which can be applicable to more complicated supply chain environment.

A Collaborative Scheduling Model for the Supply-Hub with Multiple Suppliers and Multiple Manufacturers

PubMed Central

Lv, Fei; Guan, Xu

2014-01-01

This paper investigates a collaborative scheduling model in the assembly system, wherein multiple suppliers have to deliver their components to the multiple manufacturers under the operation of Supply-Hub. We first develop two different scenarios to examine the impact of Supply-Hub. One is that suppliers and manufacturers make their decisions separately, and the other is that the Supply-Hub makes joint decisions with collaborative scheduling. The results show that our scheduling model with the Supply-Hub is a NP-complete problem, therefore, we propose an auto-adapted differential evolution algorithm to solve this problem. Moreover, we illustrate that the performance of collaborative scheduling by the Supply-Hub is superior to separate decision made by each manufacturer and supplier. Furthermore, we also show that the algorithm proposed has good convergence and reliability, which can be applicable to more complicated supply chain environment. PMID:24892104

An intelligent value-driven scheduling system for Space Station Freedom with special emphasis on the electric power system

NASA Technical Reports Server (NTRS)

Krupp, Joseph C.

1991-01-01

The Electric Power Control System (EPCS) created by Decision-Science Applications, Inc. (DSA) for the Lewis Research Center is discussed. This system makes decisions on what to schedule and when to schedule it, including making choices among various options or ways of performing a task. The system is goal-directed and seeks to shape resource usage in an optimal manner using a value-driven approach. Discussed here are considerations governing what makes a good schedule, how to design a value function to find the best schedule, and how to design the algorithm that finds the schedule that maximizes this value function. Results are shown which demonstrate the usefulness of the techniques employed.

Focus of attention in an activity-based scheduler

NASA Technical Reports Server (NTRS)

Sadeh, Norman; Fox, Mark S.

1989-01-01

Earlier research in job shop scheduling has demonstrated the advantages of opportunistically combining order-based and resource-based scheduling techniques. An even more flexible approach is investigated where each activity is considered a decision point by itself. Heuristics to opportunistically select the next decision point on which to focus attention (i.e., variable ordering heuristics) and the next decision to be tried at this point (i.e., value ordering heuristics) are described that probabilistically account for both activity precedence and resource requirement interactions. Preliminary experimental results indicate that the variable ordering heuristic greatly increases search efficiency. While least constraining value ordering heuristics have been advocated in the literature, the experimental results suggest that other value ordering heuristics combined with our variable-ordering heuristic can produce much better schedules without significantly increasing search.

On the number of different dynamics in Boolean networks with deterministic update schedules.

PubMed

Aracena, J; Demongeot, J; Fanchon, E; Montalva, M

2013-04-01

Deterministic Boolean networks are a type of discrete dynamical systems widely used in the modeling of genetic networks. The dynamics of such systems is characterized by the local activation functions and the update schedule, i.e., the order in which the nodes are updated. In this paper, we address the problem of knowing the different dynamics of a Boolean network when the update schedule is changed. We begin by proving that the problem of the existence of a pair of update schedules with different dynamics is NP-complete. However, we show that certain structural properties of the interaction diagraph are sufficient for guaranteeing distinct dynamics of a network. In [1] the authors define equivalence classes which have the property that all the update schedules of a given class yield the same dynamics. In order to determine the dynamics associated to a network, we develop an algorithm to efficiently enumerate the above equivalence classes by selecting a representative update schedule for each class with a minimum number of blocks. Finally, we run this algorithm on the well known Arabidopsis thaliana network to determine the full spectrum of its different dynamics. Copyright © 2013 Elsevier Inc. All rights reserved.

Applications of dynamic scheduling technique to space related problems: Some case studies

NASA Astrophysics Data System (ADS)

Nakasuka, Shinichi; Ninomiya, Tetsujiro

1994-10-01

The paper discusses the applications of 'Dynamic Scheduling' technique, which has been invented for the scheduling of Flexible Manufacturing System, to two space related scheduling problems: operation scheduling of a future space transportation system, and resource allocation in a space system with limited resources such as space station or space shuttle.

Achieving full connectivity of sites in the multiperiod reserve network design problem

USGS Publications Warehouse

Jafari, Nahid; Nuse, Bryan L.; Moore, Clinton; Dilkina, Bistra; Hepinstall-Cymerman, Jeffrey

2017-01-01

The conservation reserve design problem is a challenge to solve because of the spatial and temporal nature of the problem, uncertainties in the decision process, and the possibility of alternative conservation actions for any given land parcel. Conservation agencies tasked with reserve design may benefit from a dynamic decision system that provides tactical guidance for short-term decision opportunities while maintaining focus on a long-term objective of assembling the best set of protected areas possible. To plan cost-effective conservation over time under time-varying action costs and budget, we propose a multi-period mixed integer programming model for the budget-constrained selection of fully connected sites. The objective is to maximize a summed conservation value over all network parcels at the end of the planning horizon. The originality of this work is in achieving full spatial connectivity of the selected sites during the schedule of conservation actions.

A Scheduling Algorithm for Cloud Computing System Based on the Driver of Dynamic Essential Path.

PubMed

Xie, Zhiqiang; Shao, Xia; Xin, Yu

2016-01-01

To solve the problem of task scheduling in the cloud computing system, this paper proposes a scheduling algorithm for cloud computing based on the driver of dynamic essential path (DDEP). This algorithm applies a predecessor-task layer priority strategy to solve the problem of constraint relations among task nodes. The strategy assigns different priority values to every task node based on the scheduling order of task node as affected by the constraint relations among task nodes, and the task node list is generated by the different priority value. To address the scheduling order problem in which task nodes have the same priority value, the dynamic essential long path strategy is proposed. This strategy computes the dynamic essential path of the pre-scheduling task nodes based on the actual computation cost and communication cost of task node in the scheduling process. The task node that has the longest dynamic essential path is scheduled first as the completion time of task graph is indirectly influenced by the finishing time of task nodes in the longest dynamic essential path. Finally, we demonstrate the proposed algorithm via simulation experiments using Matlab tools. The experimental results indicate that the proposed algorithm can effectively reduce the task Makespan in most cases and meet a high quality performance objective.

A Scheduling Algorithm for Cloud Computing System Based on the Driver of Dynamic Essential Path

PubMed Central

Xie, Zhiqiang; Shao, Xia; Xin, Yu

2016-01-01

To solve the problem of task scheduling in the cloud computing system, this paper proposes a scheduling algorithm for cloud computing based on the driver of dynamic essential path (DDEP). This algorithm applies a predecessor-task layer priority strategy to solve the problem of constraint relations among task nodes. The strategy assigns different priority values to every task node based on the scheduling order of task node as affected by the constraint relations among task nodes, and the task node list is generated by the different priority value. To address the scheduling order problem in which task nodes have the same priority value, the dynamic essential long path strategy is proposed. This strategy computes the dynamic essential path of the pre-scheduling task nodes based on the actual computation cost and communication cost of task node in the scheduling process. The task node that has the longest dynamic essential path is scheduled first as the completion time of task graph is indirectly influenced by the finishing time of task nodes in the longest dynamic essential path. Finally, we demonstrate the proposed algorithm via simulation experiments using Matlab tools. The experimental results indicate that the proposed algorithm can effectively reduce the task Makespan in most cases and meet a high quality performance objective. PMID:27490901

Decision support system for the operating room rescheduling problem.

PubMed

van Essen, J Theresia; Hurink, Johann L; Hartholt, Woutske; van den Akker, Bernd J

2012-12-01

Due to surgery duration variability and arrivals of emergency surgeries, the planned Operating Room (OR) schedule is disrupted throughout the day which may lead to a change in the start time of the elective surgeries. These changes may result in undesirable situations for patients, wards or other involved departments, and therefore, the OR schedule has to be adjusted. In this paper, we develop a decision support system (DSS) which assists the OR manager in this decision by providing the three best adjusted OR schedules. The system considers the preferences of all involved stakeholders and only evaluates the OR schedules that satisfy the imposed resource constraints. The decision rules used for this system are based on a thorough analysis of the OR rescheduling problem. We model this problem as an Integer Linear Program (ILP) which objective is to minimize the deviation from the preferences of the considered stakeholders. By applying this ILP to instances from practice, we determined that the given preferences mainly lead to (i) shifting a surgery and (ii) scheduling a break between two surgeries. By using these changes in the DSS, the performed simulation study shows that less surgeries are canceled and patients and wards are more satisfied, but also that the perceived workload of several departments increases to compensate this. The system can also be used to judge the acceptability of a proposed initial OR schedule.

Introduction of human papillomavirus (HPV) vaccination into national immunisation schedules in Europe: Results of the VENICE 2007 survey.

PubMed

King, L A; Lévy-Bruhl, D; O'Flanagan, D; Bacci, S; Lopalco, P L; Kudjawu, Y; Salmaso, S

2008-08-14

The European Union Member States are simultaneously considering introducing HPV vaccination into their national immunisation schedules. The Vaccine European New Integrated Collaboration Effort (VENICE) project aims to develop a collaborative European vaccination network. A survey was undertaken to describe the decision status and the decision-making process regarding the potential introduction of human papillomavirus (HPV) vaccination in to their national immunisation schedules. A web-based questionnaire was developed and completed online in 2007 by 28 countries participating in VENICE. As of 31 October 2007,five countries had decided to introduce HPV vaccination into the national immunisation schedule, while another seven had started the decision-making process with a recommendation favouring introduction. Varying target populations were selected by the five countries which had introduced the vaccination. Half of the surveyed countries had undertaken at least one ad hoc study to support the decision-making process. According to an update of the decision-status from January 2008, the number of countries which had made a decision or recommendation changed to 10 and 5 respectively. This survey demonstrates the rapidly evolving nature of HPV vaccine introduction in Europe and the existence of expertise and experience among EU Member States. The VENICE network is capable of following this process and supporting countries in making vaccine introduction decisions. A VENICE collaborative web-space is being developed as a European resource for the decision-making process for vaccine introduction.

Automated and dynamic scheduling for geodetic VLBI - A simulation study for AuScope and global networks

NASA Astrophysics Data System (ADS)

Iles, E. J.; McCallum, L.; Lovell, J. E. J.; McCallum, J. N.

2018-02-01

As we move into the next era of geodetic VLBI, the scheduling process is one focus for improvement in terms of increased flexibility and the ability to react with changing conditions. A range of simulations were conducted to ascertain the impact of scheduling on geodetic results such as Earth Orientation Parameters (EOPs) and station coordinates. The potential capabilities of new automated scheduling modes were also simulated, using the so-called 'dynamic scheduling' technique. The primary aim was to improve efficiency for both cost and time without losing geodetic precision, particularly to maximise the uses of the Australian AuScope VLBI array. We show that short breaks in observation will not significantly degrade the results of a typical 24 h experiment, whereas simply shortening observing time degrades precision exponentially. We also confirm the new automated, dynamic scheduling mode is capable of producing the same standard of result as a traditional schedule, with close to real-time flexibility. Further, it is possible to use the dynamic scheduler to augment the 3 station Australian AuScope array and thereby attain EOPs of the current global precision with only intermittent contribution from 2 additional stations. We thus confirm automated, dynamic scheduling bears great potential for flexibility and automation in line with aims for future continuous VLBI operations.

A knowledge-based decision support system for payload scheduling

NASA Technical Reports Server (NTRS)

Floyd, Stephen; Ford, Donnie

1988-01-01

The role that artificial intelligence/expert systems technologies play in the development and implementation of effective decision support systems is illustrated. A recently developed prototype system for supporting the scheduling of subsystems and payloads/experiments for NASA's Space Station program is presented and serves to highlight various concepts. The potential integration of knowledge based systems and decision support systems which has been proposed in several recent articles and presentations is illustrated.

Decision-theoretic control of EUVE telescope scheduling

NASA Technical Reports Server (NTRS)

Hansson, Othar; Mayer, Andrew

1993-01-01

This paper describes a decision theoretic scheduler (DTS) designed to employ state-of-the-art probabilistic inference technology to speed the search for efficient solutions to constraint-satisfaction problems. Our approach involves assessing the performance of heuristic control strategies that are normally hard-coded into scheduling systems and using probabilistic inference to aggregate this information in light of the features of a given problem. The Bayesian Problem-Solver (BPS) introduced a similar approach to solving single agent and adversarial graph search patterns yielding orders-of-magnitude improvement over traditional techniques. Initial efforts suggest that similar improvements will be realizable when applied to typical constraint-satisfaction scheduling problems.

Experiments with a decision-theoretic scheduler

NASA Technical Reports Server (NTRS)

Hansson, Othar; Holt, Gerhard; Mayer, Andrew

1992-01-01

This paper describes DTS, a decision-theoretic scheduler designed to employ state-of-the-art probabilistic inference technology to speed the search for efficient solutions to constraint-satisfaction problems. Our approach involves assessing the performance of heuristic control strategies that are normally hard-coded into scheduling systems, and using probabilistic inference to aggregate this information in light of features of a given problem. BPS, the Bayesian Problem-Solver, introduced a similar approach to solving single-agent and adversarial graph search problems, yielding orders-of-magnitude improvement over traditional techniques. Initial efforts suggest that similar improvements will be realizable when applied to typical constraint-satisfaction scheduling problems.

Application of a hybrid generation/utility assessment heuristic to a class of scheduling problems

NASA Technical Reports Server (NTRS)

Heyward, Ann O.

1989-01-01

A two-stage heuristic solution approach for a class of multiobjective, n-job, 1-machine scheduling problems is described. Minimization of job-to-job interference for n jobs is sought. The first stage generates alternative schedule sequences by interchanging pairs of schedule elements. The set of alternative sequences can represent nodes of a decision tree; each node is reached via decision to interchange job elements. The second stage selects the parent node for the next generation of alternative sequences through automated paired comparison of objective performance for all current nodes. An application of the heuristic approach to communications satellite systems planning is presented.

Controller Strategies for Automation Tool Use under Varying Levels of Trajectory Prediction Uncertainty

NASA Technical Reports Server (NTRS)

Morey, Susan; Prevot, Thomas; Mercer, Joey; Martin, Lynne; Bienert, Nancy; Cabrall, Christopher; Hunt, Sarah; Homola, Jeffrey; Kraut, Joshua

2013-01-01

A human-in-the-loop simulation was conducted to examine the effects of varying levels of trajectory prediction uncertainty on air traffic controller workload and performance, as well as how strategies and the use of decision support tools change in response. This paper focuses on the strategies employed by two controllers from separate teams who worked in parallel but independently under identical conditions (airspace, arrival traffic, tools) with the goal of ensuring schedule conformance and safe separation for a dense arrival flow in en route airspace. Despite differences in strategy and methods, both controllers achieved high levels of schedule conformance and safe separation. Overall, results show that trajectory uncertainties introduced by wind and aircraft performance prediction errors do not affect the controllers' ability to manage traffic. Controller strategies were fairly robust to changes in error, though strategies were affected by the amount of delay to absorb (scheduled time of arrival minus estimated time of arrival). Using the results and observations, this paper proposes an ability to dynamically customize the display of information including delay time based on observed error to better accommodate different strategies and objectives.

Curriculum-Based Measurement of Reading Growth: Weekly versus Intermittent Progress Monitoring

ERIC Educational Resources Information Center

Jenkins, Joseph; Schulze, Margaret; Marti, Allison; Harbaugh, Allen G.

2017-01-01

We examined the idea that leaner schedules of progress monitoring (PM) can lighten assessment demands without undermining decision-making accuracy. Using curriculum-based measurement of reading, we compared effects on decision accuracy of 5 intermittent PM schedules relative to that of every-week PM. For participating students with high-incidence…

A dynamic scheduling algorithm for singe-arm two-cluster tools with flexible processing times

NASA Astrophysics Data System (ADS)

Li, Xin; Fung, Richard Y. K.

2018-02-01

This article presents a dynamic algorithm for job scheduling in two-cluster tools producing multi-type wafers with flexible processing times. Flexible processing times mean that the actual times for processing wafers should be within given time intervals. The objective of the work is to minimize the completion time of the newly inserted wafer. To deal with this issue, a two-cluster tool is decomposed into three reduced single-cluster tools (RCTs) in a series based on a decomposition approach proposed in this article. For each single-cluster tool, a dynamic scheduling algorithm based on temporal constraints is developed to schedule the newly inserted wafer. Three experiments have been carried out to test the dynamic scheduling algorithm proposed, comparing with the results the 'earliest starting time' heuristic (EST) adopted in previous literature. The results show that the dynamic algorithm proposed in this article is effective and practical.

Integrated Dynamic Process Planning and Scheduling in Flexible Manufacturing Systems via Autonomous Agents

NASA Astrophysics Data System (ADS)

Nejad, Hossein Tehrani Nik; Sugimura, Nobuhiro; Iwamura, Koji; Tanimizu, Yoshitaka

Process planning and scheduling are important manufacturing planning activities which deal with resource utilization and time span of manufacturing operations. The process plans and the schedules generated in the planning phase shall be modified in the execution phase due to the disturbances in the manufacturing systems. This paper deals with a multi-agent architecture of an integrated and dynamic system for process planning and scheduling for multi jobs. A negotiation protocol is discussed, in this paper, to generate the process plans and the schedules of the manufacturing resources and the individual jobs, dynamically and incrementally, based on the alternative manufacturing processes. The alternative manufacturing processes are presented by the process plan networks discussed in the previous paper, and the suitable process plans and schedules are searched and generated to cope with both the dynamic status and the disturbances of the manufacturing systems. We initiatively combine the heuristic search algorithms of the process plan networks with the negotiation protocols, in order to generate suitable process plans and schedules in the dynamic manufacturing environment. A simulation software has been developed to carry out case studies, aimed at verifying the performance of the proposed multi-agent architecture.

A novel LTE scheduling algorithm for green technology in smart grid.

PubMed

Hindia, Mohammad Nour; Reza, Ahmed Wasif; Noordin, Kamarul Ariffin; Chayon, Muhammad Hasibur Rashid

2015-01-01

Smart grid (SG) application is being used nowadays to meet the demand of increasing power consumption. SG application is considered as a perfect solution for combining renewable energy resources and electrical grid by means of creating a bidirectional communication channel between the two systems. In this paper, three SG applications applicable to renewable energy system, namely, distribution automation (DA), distributed energy system-storage (DER) and electrical vehicle (EV), are investigated in order to study their suitability in Long Term Evolution (LTE) network. To compensate the weakness in the existing scheduling algorithms, a novel bandwidth estimation and allocation technique and a new scheduling algorithm are proposed. The technique allocates available network resources based on application's priority, whereas the algorithm makes scheduling decision based on dynamic weighting factors of multi-criteria to satisfy the demands (delay, past average throughput and instantaneous transmission rate) of quality of service. Finally, the simulation results demonstrate that the proposed mechanism achieves higher throughput, lower delay and lower packet loss rate for DA and DER as well as provide a degree of service for EV. In terms of fairness, the proposed algorithm shows 3%, 7 % and 9% better performance compared to exponential rule (EXP-Rule), modified-largest weighted delay first (M-LWDF) and exponential/PF (EXP/PF), respectively.

A Novel LTE Scheduling Algorithm for Green Technology in Smart Grid

PubMed Central

Hindia, Mohammad Nour; Reza, Ahmed Wasif; Noordin, Kamarul Ariffin; Chayon, Muhammad Hasibur Rashid

2015-01-01

Smart grid (SG) application is being used nowadays to meet the demand of increasing power consumption. SG application is considered as a perfect solution for combining renewable energy resources and electrical grid by means of creating a bidirectional communication channel between the two systems. In this paper, three SG applications applicable to renewable energy system, namely, distribution automation (DA), distributed energy system-storage (DER) and electrical vehicle (EV), are investigated in order to study their suitability in Long Term Evolution (LTE) network. To compensate the weakness in the existing scheduling algorithms, a novel bandwidth estimation and allocation technique and a new scheduling algorithm are proposed. The technique allocates available network resources based on application’s priority, whereas the algorithm makes scheduling decision based on dynamic weighting factors of multi-criteria to satisfy the demands (delay, past average throughput and instantaneous transmission rate) of quality of service. Finally, the simulation results demonstrate that the proposed mechanism achieves higher throughput, lower delay and lower packet loss rate for DA and DER as well as provide a degree of service for EV. In terms of fairness, the proposed algorithm shows 3%, 7 % and 9% better performance compared to exponential rule (EXP-Rule), modified-largest weighted delay first (M-LWDF) and exponential/PF (EXP/PF), respectively. PMID:25830703

Advanced order management in ERM systems: the tic-tac-toe algorithm

NASA Astrophysics Data System (ADS)

Badell, Mariana; Fernandez, Elena; Puigjaner, Luis

2000-10-01

The concept behind improved enterprise resource planning systems (ERP) systems is the overall integration of the whole enterprise functionality into the management systems through financial links. Converting current software into real management decision tools requires crucial changes in the current approach to ERP systems. This evolution must be able to incorporate the technological achievements both properly and in time. The exploitation phase of plants needs an open web-based environment for collaborative business-engineering with on-line schedulers. Today's short lifecycles of products and processes require sharp and finely tuned management actions that must be guided by scheduling tools. Additionally, such actions must be able to keep track of money movements related to supply chain events. Thus, the necessary outputs require financial-production integration at the scheduling level as proposed in the new approach of enterprise management systems (ERM). Within this framework, the economical analysis of the due date policy and its optimization become essential to manage dynamically realistic and optimal delivery dates with price-time trade-off during the marketing activities. In this work we propose a scheduling tool with web-based interface conducted by autonomous agents when precise economic information relative to plant and business actions and their effects are provided. It aims to attain a better arrangement of the marketing and production events in order to face the bid/bargain process during e-commerce. Additionally, management systems require real time execution and an efficient transaction-oriented approach capable to dynamically adopt realistic and optimal actions to support marketing management. To this end the TicTacToe algorithm provides sequence optimization with acceptable tolerances in realistic time.

Relative Contributions of Planned Behaviour and Social Capital on Educational Continuation Decisions of Disadvantaged Students

ERIC Educational Resources Information Center

Edannur, Sreekala

2018-01-01

The present study is conducted to understand the relative contributions of planned behavior and social capital on educational continuation decisions of VIII standard students belonging to backward class in India. Scheduled Castes (SC), Scheduled Tribes (ST), and Other Backward Classes (OBC) are the three social groups dealt as backward classes in…

Dynamic Staffing and Rescheduling in Software Project Management: A Hybrid Approach.

PubMed

Ge, Yujia; Xu, Bin

2016-01-01

Resource allocation could be influenced by various dynamic elements, such as the skills of engineers and the growth of skills, which requires managers to find an effective and efficient tool to support their staffing decision-making processes. Rescheduling happens commonly and frequently during the project execution. Control options have to be made when new resources are added or tasks are changed. In this paper we propose a software project staffing model considering dynamic elements of staff productivity with a Genetic Algorithm (GA) and Hill Climbing (HC) based optimizer. Since a newly generated reschedule dramatically different from the initial schedule could cause an obvious shifting cost increase, our rescheduling strategies consider both efficiency and stability. The results of real world case studies and extensive simulation experiments show that our proposed method is effective and could achieve comparable performance to other heuristic algorithms in most cases.

Dynamic Staffing and Rescheduling in Software Project Management: A Hybrid Approach

PubMed Central

Ge, Yujia; Xu, Bin

2016-01-01

Resource allocation could be influenced by various dynamic elements, such as the skills of engineers and the growth of skills, which requires managers to find an effective and efficient tool to support their staffing decision-making processes. Rescheduling happens commonly and frequently during the project execution. Control options have to be made when new resources are added or tasks are changed. In this paper we propose a software project staffing model considering dynamic elements of staff productivity with a Genetic Algorithm (GA) and Hill Climbing (HC) based optimizer. Since a newly generated reschedule dramatically different from the initial schedule could cause an obvious shifting cost increase, our rescheduling strategies consider both efficiency and stability. The results of real world case studies and extensive simulation experiments show that our proposed method is effective and could achieve comparable performance to other heuristic algorithms in most cases. PMID:27285420

Power-based Shift Schedule for Pure Electric Vehicle with a Two-speed Automatic Transmission

NASA Astrophysics Data System (ADS)

Wang, Jiaqi; Liu, Yanfang; Liu, Qiang; Xu, Xiangyang

2016-11-01

This paper introduces a comprehensive shift schedule for a two-speed automatic transmission of pure electric vehicle. Considering about driving ability and efficiency performance of electric vehicles, the power-based shift schedule is proposed with three principles. This comprehensive shift schedule regards the vehicle current speed and motor load power as input parameters to satisfy the vehicle driving power demand with lowest energy consumption. A simulation model has been established to verify the dynamic and economic performance of comprehensive shift schedule. Compared with traditional dynamic and economic shift schedules, simulation results indicate that the power-based shift schedule is superior to traditional shift schedules.

Impaired flexible decision-making in Major Depressive Disorder.

PubMed

Cella, Matteo; Dymond, Simon; Cooper, Andy

2010-07-01

Depression is associated with dysfunctional affective states, neuropsychological impairment and altered sensitivity to reward and punishment. These impairments can influence complex decision-making in changing environments. The contingency shifting variant Iowa Gambling Task (IGT) was used to assess flexible decision-making performance in a group of medicated unipolar Major Depressive Disorder (MDD) patients (n=19) and a group of healthy control volunteers (n=20). The task comprised the standard IGT followed by a contingency-shift phase where decks progressively changed reward and punishment schedule. Patients with MDD showed impaired performance compared to controls during both the standard and the contingency-shift phases of the IGT. Analysis of the contingency-shift phase demonstrated that individuals with depression had difficulties perceiving when a previously bad contingency became good. The present findings have several limitations including small sample size, the possible confounding role of medication and absence of other neuropsychological tests (i.e., executive function). Depressed patients show impaired decision-making behaviour in static and dynamic environments. Altered sensitivity to reward and punishment is proposed as the mechanism responsible for the lack of advantageous choices and poor adjustment to a changing environment.

Applying dynamic priority scheduling scheme to static systems of pinwheel task model in power-aware scheduling.

PubMed

Seol, Ye-In; Kim, Young-Kuk

2014-01-01

Power-aware scheduling reduces CPU energy consumption in hard real-time systems through dynamic voltage scaling (DVS). In this paper, we deal with pinwheel task model which is known as static and predictable task model and could be applied to various embedded or ubiquitous systems. In pinwheel task model, each task's priority is static and its execution sequence could be predetermined. There have been many static approaches to power-aware scheduling in pinwheel task model. But, in this paper, we will show that the dynamic priority scheduling results in power-aware scheduling could be applied to pinwheel task model. This method is more effective than adopting the previous static priority scheduling methods in saving energy consumption and, for the system being still static, it is more tractable and applicable to small sized embedded or ubiquitous computing. Also, we introduce a novel power-aware scheduling algorithm which exploits all slacks under preemptive earliest-deadline first scheduling which is optimal in uniprocessor system. The dynamic priority method presented in this paper could be applied directly to static systems of pinwheel task model. The simulation results show that the proposed algorithm with the algorithmic complexity of O(n) reduces the energy consumption by 10-80% over the existing algorithms.

Applying Dynamic Priority Scheduling Scheme to Static Systems of Pinwheel Task Model in Power-Aware Scheduling

PubMed Central

2014-01-01

Power-aware scheduling reduces CPU energy consumption in hard real-time systems through dynamic voltage scaling (DVS). In this paper, we deal with pinwheel task model which is known as static and predictable task model and could be applied to various embedded or ubiquitous systems. In pinwheel task model, each task's priority is static and its execution sequence could be predetermined. There have been many static approaches to power-aware scheduling in pinwheel task model. But, in this paper, we will show that the dynamic priority scheduling results in power-aware scheduling could be applied to pinwheel task model. This method is more effective than adopting the previous static priority scheduling methods in saving energy consumption and, for the system being still static, it is more tractable and applicable to small sized embedded or ubiquitous computing. Also, we introduce a novel power-aware scheduling algorithm which exploits all slacks under preemptive earliest-deadline first scheduling which is optimal in uniprocessor system. The dynamic priority method presented in this paper could be applied directly to static systems of pinwheel task model. The simulation results show that the proposed algorithm with the algorithmic complexity of O(n) reduces the energy consumption by 10–80% over the existing algorithms. PMID:25121126

Intelligent Planning and Scheduling for Controlled Life Support Systems

NASA Technical Reports Server (NTRS)

Leon, V. Jorge

1996-01-01

Planning in Controlled Ecological Life Support Systems (CELSS) requires special look ahead capabilities due to the complex and long-term dynamic behavior of biological systems. This project characterizes the behavior of CELSS, identifies the requirements of intelligent planning systems for CELSS, proposes the decomposition of the planning task into short-term and long-term planning, and studies the crop scheduling problem as an initial approach to long-term planning. CELSS is studied in the realm of Chaos. The amount of biomass in the system is modeled using a bounded quadratic iterator. The results suggests that closed ecological systems can exhibit periodic behavior when imposed external or artificial control. The main characteristics of CELSS from the planning and scheduling perspective are discussed and requirements for planning systems are given. Crop scheduling problem is identified as an important component of the required long-term lookahead capabilities of a CELSS planner. The main characteristics of crop scheduling are described and a model is proposed to represent the problem. A surrogate measure of the probability of survival is developed. The measure reflects the absolute deviation of the vital reservoir levels from their nominal values. The solution space is generated using a probability distribution which captures both knowledge about the system and the current state of affairs at each decision epoch. This probability distribution is used in the context of an evolution paradigm. The concepts developed serve as the basis for the development of a simple crop scheduling tool which is used to demonstrate its usefulness in the design and operation of CELSS.

77 FR 23277 - Wekiva River System Advisory Management Committee Meetings (FY2012)

Federal Register 2010, 2011, 2012, 2013, 2014

2012-04-18

...: Notice of upcoming scheduled meetings. SUMMARY: This notice announces a schedule of upcoming meetings for... 5, 2012 (Recreation Hall). Time: All scheduled meetings will begin at 3 p.m. and will end by 5 p.m... public. Each scheduled meeting will result in decisions and steps that advance the Wekiva River System...

Multi-Satellite Scheduling Approach for Dynamic Areal Tasks Triggered by Emergent Disasters

NASA Astrophysics Data System (ADS)

Niu, X. N.; Zhai, X. J.; Tang, H.; Wu, L. X.

2016-06-01

The process of satellite mission scheduling, which plays a significant role in rapid response to emergent disasters, e.g. earthquake, is used to allocate the observation resources and execution time to a series of imaging tasks by maximizing one or more objectives while satisfying certain given constraints. In practice, the information obtained of disaster situation changes dynamically, which accordingly leads to the dynamic imaging requirement of users. We propose a satellite scheduling model to address dynamic imaging tasks triggered by emergent disasters. The goal of proposed model is to meet the emergency response requirements so as to make an imaging plan to acquire rapid and effective information of affected area. In the model, the reward of the schedule is maximized. To solve the model, we firstly present a dynamic segmenting algorithm to partition area targets. Then the dynamic heuristic algorithm embedding in a greedy criterion is designed to obtain the optimal solution. To evaluate the model, we conduct experimental simulations in the scene of Wenchuan Earthquake. The results show that the simulated imaging plan can schedule satellites to observe a wider scope of target area. We conclude that our satellite scheduling model can optimize the usage of satellite resources so as to obtain images in disaster response in a more timely and efficient manner.

How Home Health Nurses Plan Their Work Schedules: A Qualitative Descriptive Study.

PubMed

Irani, Elliane; Hirschman, Karen B; Cacchione, Pamela Z; Bowles, Kathryn H

2018-06-12

To describe how home health nurses plan their daily work schedules and what challenges they face during the planning process. Home health nurses are viewed as independent providers and value the nature of their work because of the flexibility and autonomy they hold in developing their work schedules. However, there is limited empirical evidence about how home health nurses plan their work schedules, including the factors they consider during the process and the challenges they face within the dynamic home health setting. Qualitative descriptive design. Semi-structured interviews were conducted with 20 registered nurses who had greater than 2 years of experience in home health and were employed by one of the three participating home health agencies in the mid-Atlantic region of the United States. Data were analyzed using conventional content analysis. Four themes emerged about planning work schedules and daily itineraries: identifying patient needs to prioritize visits accordingly, partnering with patients to accommodate their preferences, coordinating visit timing with other providers to avoid overwhelming patients, and working within agency standards to meet productivity requirements. Scheduling challenges included readjusting the schedule based on patient needs and staffing availability, anticipating longer visits, and maintaining continuity of care with patients. Home health nurses make autonomous decisions regarding their work schedules while considering specific patient and agency factors, and overcome challenges related to the unpredictable nature of providing care in a home health setting. Future research is needed to further explore nurse productivity in home health and improve home health work environments. Home health nurses plan their work schedules to provide high quality care that is patient-centered and timely. The findings also highlight organizational priorities to facilitate continuity of care and support nurses while alleviating the burnout associated with high productivity requirements. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Prediction based proactive thermal virtual machine scheduling in green clouds.

PubMed

Kinger, Supriya; Kumar, Rajesh; Sharma, Anju

2014-01-01

Cloud computing has rapidly emerged as a widely accepted computing paradigm, but the research on Cloud computing is still at an early stage. Cloud computing provides many advanced features but it still has some shortcomings such as relatively high operating cost and environmental hazards like increasing carbon footprints. These hazards can be reduced up to some extent by efficient scheduling of Cloud resources. Working temperature on which a machine is currently running can be taken as a criterion for Virtual Machine (VM) scheduling. This paper proposes a new proactive technique that considers current and maximum threshold temperature of Server Machines (SMs) before making scheduling decisions with the help of a temperature predictor, so that maximum temperature is never reached. Different workload scenarios have been taken into consideration. The results obtained show that the proposed system is better than existing systems of VM scheduling, which does not consider current temperature of nodes before making scheduling decisions. Thus, a reduction in need of cooling systems for a Cloud environment has been obtained and validated.

OGUPSA sensor scheduling architecture and algorithm

NASA Astrophysics Data System (ADS)

Zhang, Zhixiong; Hintz, Kenneth J.

1996-06-01

This paper introduces a new architecture for a sensor measurement scheduler as well as a dynamic sensor scheduling algorithm called the on-line, greedy, urgency-driven, preemptive scheduling algorithm (OGUPSA). OGUPSA incorporates a preemptive mechanism which uses three policies, (1) most-urgent-first (MUF), (2) earliest- completed-first (ECF), and (3) least-versatile-first (LVF). The three policies are used successively to dynamically allocate and schedule and distribute a set of arriving tasks among a set of sensors. OGUPSA also can detect the failure of a task to meet a deadline as well as generate an optimal schedule in the sense of minimum makespan for a group of tasks with the same priorities. A side benefit is OGUPSA's ability to improve dynamic load balance among all sensors while being a polynomial time algorithm. Results of a simulation are presented for a simple sensor system.

Young Children's Affective Decision-Making in a Gambling Task: Does Difficulty in Learning the Gain/Loss Schedule Matter?

ERIC Educational Resources Information Center

Gao, Shan; Wei, Yonggang; Bai, Junjie; Lin, Chongde; Li, Hong

2009-01-01

This research investigated the development of affective decision-making (ADM) during early childhood, in particular role of difficulty in learning a gain/loss schedule. In Experiment 1, we administrated the Children's Gambling Task (CGT) to 60 Chinese children aged 3 and 4, replicating the results obtained by Kerr and Zelazo [Kerr, A., & Zelazo,…

Evaluation of a software module for adaptive treatment planning and re-irradiation.

PubMed

Richter, Anne; Weick, Stefan; Krieger, Thomas; Exner, Florian; Kellner, Sonja; Polat, Bülent; Flentje, Michael

2017-12-28

The aim of this work is to validate the Dynamic Planning Module in terms of usability and acceptance in the treatment planning workflow. The Dynamic Planning Module was used for decision making whether a plan adaptation was necessary within one course of radiation therapy. The Module was also used for patients scheduled for re-irradiation to estimate the dose in the pretreated region and calculate the accumulated dose to critical organs at risk. During one year, 370 patients were scheduled for plan adaptation or re-irradiation. All patient cases were classified according to their treated body region. For a sub-group of 20 patients treated with RT for lung cancer, the dosimetric effect of plan adaptation during the main treatment course was evaluated in detail. Changes in tumor volume, frequency of re-planning and the time interval between treatment start and plan adaptation were assessed. The Dynamic Planning Tool was used in 20% of treated patients per year for both approaches nearly equally (42% plan adaptation and 58% re-irradiation). Most cases were assessed for the thoracic body region (51%) followed by pelvis (21%) and head and neck cases (10%). The sub-group evaluation showed that unintended plan adaptation was performed in 38% of the scheduled cases. A median time span between first day of treatment and necessity of adaptation of 17 days (range 4-35 days) was observed. PTV changed by 12 ± 12% on average (maximum change 42%). PTV decreased in 18 of 20 cases due to tumor shrinkage and increased in 2 of 20 cases. Re-planning resulted in a reduction of the mean lung dose of the ipsilateral side in 15 of 20 cases. The experience of one year showed high acceptance of the Dynamic Planning Module in our department for both physicians and medical physicists. The re-planning can potentially reduce the accumulated dose to the organs at risk and ensure a better target volume coverage. In the re-irradiation situation, the Dynamic Planning Tool was used to consider the pretreatment dose, to adapt the actual treatment schema more specifically and to review the accumulated dose.

The role of the production scheduling system in rescheduling

NASA Astrophysics Data System (ADS)

Kalinowski, K.; Grabowik, C.; Kempa, W.; Paprocka, I.

2015-11-01

The paper presents the rescheduling problem in the context of cooperation between production scheduling system (PSS) and other units in an integrated manufacturing environment - decision makers and software systems. The main aim is to discuss the PSS functionality for maximizing automation of the rescheduling process, reducing the response time and improving the quality of generated solutions. PSSs operate in the meeting of tactical and operational level of planning and control, and play an important role in the production preparation and control. On the basis of information about orders, technology and production system state (e.g. resources availability) they prepare and/or update a detailed plan of production flow - a schedule. All necessary data for scheduling and rescheduling are usually collected in other systems both from organizational and technical production preparation, e.g. ERP, PLM, MES, CAPP or others, as well as they are entered directly by the decision- makers/operators. Data acquired in this way are often incomplete and inconsistent. Therefore the existing rescheduling software works according to interactive method - rather support but does not replace the human decision maker in tasks planning. When rescheduling, due to the limited amount of time to make a decision this interaction is particularly important. An additional problem arises in data acquisition, in the process of data exchanging between systems or in the identification of new data sources and their processing. Different approaches to rescheduling were characterized, including those solutions, where all these operations are carried out by an autonomous system and those in which scheduling is performed only upon request from the outside, for the newly created scheduling data representing the current state of the production system.

Production scheduling and rescheduling with genetic algorithms.

PubMed

Bierwirth, C; Mattfeld, D C

1999-01-01

A general model for job shop scheduling is described which applies to static, dynamic and non-deterministic production environments. Next, a Genetic Algorithm is presented which solves the job shop scheduling problem. This algorithm is tested in a dynamic environment under different workload situations. Thereby, a highly efficient decoding procedure is proposed which strongly improves the quality of schedules. Finally, this technique is tested for scheduling and rescheduling in a non-deterministic environment. It is shown by experiment that conventional methods of production control are clearly outperformed at reasonable run-time costs.

Static-dynamic hybrid communication scheduling and control co-design for networked control systems.

PubMed

Wen, Shixi; Guo, Ge

2017-11-01

In this paper, the static-dynamic hybrid communication scheduling and control co-design is proposed for the networked control systems (NCSs) to solve the capacity limitation of the wireless communication network. The analytical most regular binary sequences (MRBSs) are used as the communication scheduling function for NCSs. When the communication conflicts yielded in the binary sequence MRBSs, a dynamic scheduling strategy is proposed to on-line reallocate the medium access status for each plant. Under such static-dynamic hybrid scheduling policy, plants in NCSs are described as the non-uniform sampled-control systems, whose controller have a group of controller gains and switch according to the sampling interval yielded by the binary sequence. A useful communication scheduling and control co-design framework is proposed for the NCSs to simultaneously decide the controller gains and the parameters used to generate the communication sequences MRBS. Numerical example and realistic example are respectively given to demonstrate the effectiveness of the proposed co-design method. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

77 FR 73678 - Robert M. Brodkin, D.P.M.; Decision and Order

Federal Register 2010, 2011, 2012, 2013, 2014

2012-12-11

... Demerol 50 mg/ml (meperidine, a schedule II narcotic); 1200 tablets of diazepam (a schedule IV benzodiazepine); 1500 tablets of hydrocodone/acetaminophen 10/500 mg and 1700 tablets of hydrocodone...); 200 tablets of propoxyphene (a schedule IV narcotic); and four bottles of testosterone cypionate 10 ml...

75 FR 65279 - Schedule for Rating Disabilities; AL Amyloidosis (Primary Amyloidosis)

Federal Register 2010, 2011, 2012, 2013, 2014

2010-10-22

... DEPARTMENT OF VETERANS AFFAIRS 38 CFR Part 4 RIN 2900-AN75 Schedule for Rating Disabilities; AL... document proposes to amend the Department of Veterans Affairs (VA) Schedule for Rating Disabilities (rating... establish criteria for disability evaluation to fully implement the decision by the Secretary of Veterans...

The CFE v. MHSAA Decision: A Case Study of Gender Equity in High School Athletic Scheduling and Policy Ramifications for the WIAA

ERIC Educational Resources Information Center

Bardo, David B.

2010-01-01

The Communities For Equity was a group of Michigan mothers who filed a Title IX discrimination suit against the Michigan High School Athletic Association due to its athletic scheduling practices. The 10-year court battle went all the way to the U.S. Supreme Court. This case study reviewed the policy decisions of the Wisconsin Interscholastic…

Management implications for the perioperative surgical home related to inpatient case cancellations and add-on case scheduling on the day of surgery.

PubMed

Epstein, Richard H; Dexter, Franklin

2015-07-01

The American Society of Anesthesiologists has embraced the concept of the Perioperative Surgical Home as a means through which anesthesiologists can add value to the health systems in which they practice. One key listed element of the Perioperative Surgical Home is to support "scheduling initiatives to reduce cancellations and increase efficiency." In this study, we explored the potential benefits of the Perioperative Surgical Home with respect to inpatient cancellations and add-on case scheduling. We evaluated 6 hypotheses related to the timing of inpatient cancellations and preoperative anesthesia evaluations. Inpatient cancellations were studied during 26 consecutive 4-week intervals between July 2012 and June 2014 at a tertiary care academic hospital. All timestamps related to scheduling, rescheduling, and cancellation activities were retrieved from the operating room (OR) case scheduling system. Timestamps when patients were seen by anesthesia residents were obtained from the preoperative evaluation system database. Batch mean methods were used to calculate means and SE. For cases cancelled, we determined whether, for "most" (>50%) cancellations, a subsequent procedure (of any type) was performed on the patient within 7 days of the cancellation. Comparisons with most and other fractions were assessed using the 1 group, 1-sided Student t test. We evaluated whether a few procedures were highly represented among the cancelled cases via the Herfindahl (Simpson's) index, comparing it with <0.15. The rate of scheduling activity was assessed by computing the number of OR scheduling office decisions in each 1-hour bin between 6:00 AM and 3:59 PM. These values were compared with ≥1 decision per hour at the study hospital. Data from 24,735 scheduled inpatient cases were assessed. Cases cancelled after 7 AM on the day before or at any time on the scheduled day of surgery accounted for 22.6% ± 0.5% (SE) of the scheduled minutes all scheduled cases, and 26.8% ± 0.4% of the case volume (i.e., number of cases). Most (83.1% ± 0.6%, P < 10) cases performed were evaluated on the day before surgery. Most (67.6% ± 1.6%, P < 10) minutes of cancelled cases were evaluated on the day before surgery. Most (62.3% ± 1.5%, P < 10) cases were seen earlier than 6:00 PM of the day before surgery. The Herfindahl index among cancelled procedures was 0.021 ± 0.001 (P < 10 compared not only to <0.15 but also to <0.05), showing large heterogeneity among the cancelled procedures. A subsequent procedure was not performed for most cancelled cases (50.6% ± 0.9% compared with >50%, P = 0.12), implying that the indication for the cancelled procedure no longer existed or the patient/family decided not to proceed with surgery. When only cancellations on the scheduled day of surgery were considered, the cancellation rate was 14.0% ± 0.3% of scheduled inpatient minutes and 11.8% ± 0.2% of scheduled inpatient cases. There were 0.59 ± 0.02 OR schedule decisions per hour per 10 ORs between 6:00 AM and 3:59 PM (P < 10, corresponding to ≥1 decision per hour at the 36 OR study hospital). The study hospital had a high inpatient cancellation rate, despite the fact that most patients whose cases were cancelled were seen by an anesthesia resident by 6:00 PM of the day before surgery. This finding suggests that further efforts to reduce the cancellations by seeing patients sooner on the day before surgery, or seeing even more patients the day before surgery, would not be an economically useful focus of the Perioperative Surgical Home. The wide heterogeneity among cancelled cases indicates that focusing on a few procedures would not materially affect the overall cancellation rate. The relatively low rate of subsequent performance of a procedure on patients whose cases had been cancelled suggests that trying to decrease the cancellation rate might be medically counterproductive. The hourly rate of decisions in the scheduling office during regular work hours on the day of surgery highlights the importance of decisions made at the OR control desk and scheduling office throughout the day to reduce the hours of overused OR time. These data suggest that efforts of the Perioperative Surgical Home related to inpatient cancellations should focus on management decision-making to mitigate the disruptions to the planned OR schedule caused by inpatient case cancellations and add-on cases, more so than on efforts to reduce inpatient cancellation rates.

Interleaved Observation Execution and Rescheduling on Earth Observing Systems

NASA Technical Reports Server (NTRS)

Khatib, Lina; Frank, Jeremy; Smith, David; Morris, Robert; Dungan, Jennifer

2003-01-01

Observation scheduling for Earth orbiting satellites solves the following problem: given a set of requests for images of the Earth, a set of instruments for acquiring those images distributed on a collecting of orbiting satellites, and a set of temporal and resource constraints, generate a set of assignments of instruments and viewing times to those requests that satisfy those constraints. Observation scheduling is often construed as a constrained optimization problem with the objective of maximizing the overall utility of the science data acquired. The utility of an image is typically based on the intrinsic importance of acquiring it (for example, its importance in meeting a mission or science campaign objective) as well as the expected value of the data given current viewing conditions (for example, if the image is occluded by clouds, its value is usually diminished). Currently, science observation scheduling for Earth Observing Systems is done on the ground, for periods covering a day or more. Schedules are uplinked to the satellites and are executed rigorously. An alternative to this scenario is to do some of the decision-making about what images are to be acquired on-board. The principal argument for this capability is that the desirability of making an observation can change dynamically, because of changes in meteorological conditions (e.g. cloud cover), unforeseen events such as fires, floods, or volcanic eruptions, or un-expected changes in satellite or ground station capability. Furthermore, since satellites can only communicate with the ground between 5% to 10% of the time, it may be infeasible to make the desired changes to the schedule on the ground, and uplink the revisions in time for the on-board system to execute them. Examples of scenarios that motivate an on-board capability for revising schedules include the following. First, if a desired visual scene is completely obscured by clouds, then there is little point in taking it. In this case, satellite resources, such as power and storage space can be better utilized taking another image that is higher quality. Second, if an unexpected but important event occurs (such as a fire, flood, or volcanic eruption), there may be good reason to take images of it, instead of expending satellite resources on some of the lower priority scheduled observations. Finally, if there is unexpected loss of capability, it may be impossible to carry out the schedule of planned observations. For example, if a ground station goes down temporarily, a satellite may not be able to free up enough storage space to continue with the remaining schedule of observations. This paper describes an approach for interleaving execution of observation schedules with dynamic schedule revision based on changes to the expected utility of the acquired images. We describe the problem in detail, formulate an algorithm for interleaving schedule revision and execution, and discuss refinements to the algorithm based on the need for search efficiency. We summarize with a brief discussion of the tests performed on the system.

Optimized maritime emergency resource allocation under dynamic demand.

PubMed

Zhang, Wenfen; Yan, Xinping; Yang, Jiaqi

2017-01-01

Emergency resource is important for people evacuation and property rescue when accident occurs. The relief efforts could be promoted by a reasonable emergency resource allocation schedule in advance. As the marine environment is complicated and changeful, the place, type, severity of maritime accident is uncertain and stochastic, bringing about dynamic demand of emergency resource. Considering dynamic demand, how to make a reasonable emergency resource allocation schedule is challenging. The key problem is to determine the optimal stock of emergency resource for supplier centers to improve relief efforts. This paper studies the dynamic demand, and which is defined as a set. Then a maritime emergency resource allocation model with uncertain data is presented. Afterwards, a robust approach is developed and used to make sure that the resource allocation schedule performs well with dynamic demand. Finally, a case study shows that the proposed methodology is feasible in maritime emergency resource allocation. The findings could help emergency manager to schedule the emergency resource allocation more flexibly in terms of dynamic demand.

Optimized maritime emergency resource allocation under dynamic demand

PubMed Central

Yan, Xinping; Yang, Jiaqi

2017-01-01

Emergency resource is important for people evacuation and property rescue when accident occurs. The relief efforts could be promoted by a reasonable emergency resource allocation schedule in advance. As the marine environment is complicated and changeful, the place, type, severity of maritime accident is uncertain and stochastic, bringing about dynamic demand of emergency resource. Considering dynamic demand, how to make a reasonable emergency resource allocation schedule is challenging. The key problem is to determine the optimal stock of emergency resource for supplier centers to improve relief efforts. This paper studies the dynamic demand, and which is defined as a set. Then a maritime emergency resource allocation model with uncertain data is presented. Afterwards, a robust approach is developed and used to make sure that the resource allocation schedule performs well with dynamic demand. Finally, a case study shows that the proposed methodology is feasible in maritime emergency resource allocation. The findings could help emergency manager to schedule the emergency resource allocation more flexibly in terms of dynamic demand. PMID:29240792

Dynamic scheduling and planning parallel observations on large Radio Telescope Arrays with the Square Kilometre Array in mind

NASA Astrophysics Data System (ADS)

Buchner, Johannes

2011-12-01

Scheduling, the task of producing a time table for resources and tasks, is well-known to be a difficult problem the more resources are involved (a NP-hard problem). This is about to become an issue in Radio astronomy as observatories consisting of hundreds to thousands of telescopes are planned and operated. The Square Kilometre Array (SKA), which Australia and New Zealand bid to host, is aiming for scales where current approaches -- in construction, operation but also scheduling -- are insufficent. Although manual scheduling is common today, the problem is becoming complicated by the demand for (1) independent sub-arrays doing simultaneous observations, which requires the scheduler to plan parallel observations and (2) dynamic re-scheduling on changed conditions. Both of these requirements apply to the SKA, especially in the construction phase. We review the scheduling approaches taken in the astronomy literature, as well as investigate techniques from human schedulers and today's observatories. The scheduling problem is specified in general for scientific observations and in particular on radio telescope arrays. Also taken into account is the fact that the observatory may be oversubscribed, requiring the scheduling problem to be integrated with a planning process. We solve this long-term scheduling problem using a time-based encoding that works in the very general case of observation scheduling. This research then compares algorithms from various approaches, including fast heuristics from CPU scheduling, Linear Integer Programming and Genetic algorithms, Branch-and-Bound enumeration schemes. Measures include not only goodness of the solution, but also scalability and re-scheduling capabilities. In conclusion, we have identified a fast and good scheduling approach that allows (re-)scheduling difficult and changing problems by combining heuristics with a Genetic algorithm using block-wise mutation operations. We are able to explain and eradicate two problems in the literature: The inability of a GA to properly improve schedules and the generation of schedules with frequent interruptions. Finally, we demonstrate the scheduling framework for several operating telescopes: (1) Dynamic re-scheduling with the AUT Warkworth 12m telescope, (2) Scheduling for the Australian Mopra 22m telescope and scheduling for the Allen Telescope Array. Furthermore, we discuss the applicability of the presented scheduling framework to the Atacama Large Millimeter/submillimeter Array (ALMA, in construction) and the SKA. In particular, during the development phase of the SKA, this dynamic, scalable scheduling framework can accommodate changing conditions.

Computer Based Decision Support Tool for Helicopter Mission Planning in Disaster Relief and Military Operations (Outil informatique d’aide a la decision pour la planification des missions d’helicopteres dans des operations militaires et de secours en cas de catastrophe)

DTIC Science & Technology

2008-06-01

capacity planning; • Electrical generation capacity planning; • Machine scheduling; • Freight scheduling; • Dairy farm expansion planning...Support Systems and Multi Criteria Decision Analysis Products A.2.11.2.2.1 ELECTRE IS ELECTRE IS is a generalization of ELECTRE I. It is a...criteria, ELECTRE IS supports the user in the process of selecting one alternative or a subset of alternatives. The method consists of two parts

DECISION ANALYSIS OF INCINERATION COSTS IN SUPERFUND SITE REMEDIATION

EPA Science Inventory

This study examines the decision-making process of the remedial design (RD) phase of on-site incineration projects conducted at Superfund sites. Decisions made during RD affect the cost and schedule of remedial action (RA). Decision analysis techniques are used to determine the...

Use of Dynamic Models and Operational Architecture to Solve Complex Navy Challenges

NASA Technical Reports Server (NTRS)

Grande, Darby; Black, J. Todd; Freeman, Jared; Sorber, TIm; Serfaty, Daniel

2010-01-01

The United States Navy established 8 Maritime Operations Centers (MOC) to enhance the command and control of forces at the operational level of warfare. Each MOC is a headquarters manned by qualified joint operational-level staffs, and enabled by globally interoperable C41 systems. To assess and refine MOC staffing, equipment, and schedules, a dynamic software model was developed. The model leverages pre-existing operational process architecture, joint military task lists that define activities and their precedence relations, as well as Navy documents that specify manning and roles per activity. The software model serves as a "computational wind-tunnel" in which to test a MOC on a mission, and to refine its structure, staffing, processes, and schedules. More generally, the model supports resource allocation decisions concerning Doctrine, Organization, Training, Material, Leadership, Personnel and Facilities (DOTMLPF) at MOCs around the world. A rapid prototype effort efficiently produced this software in less than five months, using an integrated process team consisting of MOC military and civilian staff, modeling experts, and software developers. The work reported here was conducted for Commander, United States Fleet Forces Command in Norfolk, Virginia, code N5-0LW (Operational Level of War) that facilitates the identification, consolidation, and prioritization of MOC capabilities requirements, and implementation and delivery of MOC solutions.

Population-based learning of load balancing policies for a distributed computer system

NASA Technical Reports Server (NTRS)

Mehra, Pankaj; Wah, Benjamin W.

1993-01-01

Effective load-balancing policies use dynamic resource information to schedule tasks in a distributed computer system. We present a novel method for automatically learning such policies. At each site in our system, we use a comparator neural network to predict the relative speedup of an incoming task using only the resource-utilization patterns obtained prior to the task's arrival. Outputs of these comparator networks are broadcast periodically over the distributed system, and the resource schedulers at each site use these values to determine the best site for executing an incoming task. The delays incurred in propagating workload information and tasks from one site to another, as well as the dynamic and unpredictable nature of workloads in multiprogrammed multiprocessors, may cause the workload pattern at the time of execution to differ from patterns prevailing at the times of load-index computation and decision making. Our load-balancing policy accommodates this uncertainty by using certain tunable parameters. We present a population-based machine-learning algorithm that adjusts these parameters in order to achieve high average speedups with respect to local execution. Our results show that our load-balancing policy, when combined with the comparator neural network for workload characterization, is effective in exploiting idle resources in a distributed computer system.

10 CFR 2.334 - Implementing hearing schedule for proceeding.

Code of Federal Regulations, 2010 CFR

2010-01-01

... proceeding shall, based on information and projections provided by the parties and the NRC staff, take... issuance of its initial decision. (b) Modification of hearing schedule. A hearing schedule may not be modified except upon a finding of good cause by the presiding officer or the Commission. In making such a...

State Teacher Salary Schedules. Policy Analysis

ERIC Educational Resources Information Center

Griffith, Michael

2016-01-01

In the United States most teacher compensation issues are decided at the school district level. However, a group of states have chosen to play a role in teacher pay decisions by instituting statewide teacher salary schedules. Education Commission of the States has found that 17 states currently make use of teacher salary schedules. This education…

Prediction Based Proactive Thermal Virtual Machine Scheduling in Green Clouds

PubMed Central

Kinger, Supriya; Kumar, Rajesh; Sharma, Anju

2014-01-01

Cloud computing has rapidly emerged as a widely accepted computing paradigm, but the research on Cloud computing is still at an early stage. Cloud computing provides many advanced features but it still has some shortcomings such as relatively high operating cost and environmental hazards like increasing carbon footprints. These hazards can be reduced up to some extent by efficient scheduling of Cloud resources. Working temperature on which a machine is currently running can be taken as a criterion for Virtual Machine (VM) scheduling. This paper proposes a new proactive technique that considers current and maximum threshold temperature of Server Machines (SMs) before making scheduling decisions with the help of a temperature predictor, so that maximum temperature is never reached. Different workload scenarios have been taken into consideration. The results obtained show that the proposed system is better than existing systems of VM scheduling, which does not consider current temperature of nodes before making scheduling decisions. Thus, a reduction in need of cooling systems for a Cloud environment has been obtained and validated. PMID:24737962

Trajectory-Based Takeoff Time Predictions Applied to Tactical Departure Scheduling: Concept Description, System Design, and Initial Observations

NASA Technical Reports Server (NTRS)

Engelland, Shawn A.; Capps, Alan

2011-01-01

Current aircraft departure release times are based on manual estimates of aircraft takeoff times. Uncertainty in takeoff time estimates may result in missed opportunities to merge into constrained en route streams and lead to lost throughput. However, technology exists to improve takeoff time estimates by using the aircraft surface trajectory predictions that enable air traffic control tower (ATCT) decision support tools. NASA s Precision Departure Release Capability (PDRC) is designed to use automated surface trajectory-based takeoff time estimates to improve en route tactical departure scheduling. This is accomplished by integrating an ATCT decision support tool with an en route tactical departure scheduling decision support tool. The PDRC concept and prototype software have been developed, and an initial test was completed at air traffic control facilities in Dallas/Fort Worth. This paper describes the PDRC operational concept, system design, and initial observations.

Evolution of Query Optimization Methods

NASA Astrophysics Data System (ADS)

Hameurlain, Abdelkader; Morvan, Franck

Query optimization is the most critical phase in query processing. In this paper, we try to describe synthetically the evolution of query optimization methods from uniprocessor relational database systems to data Grid systems through parallel, distributed and data integration systems. We point out a set of parameters to characterize and compare query optimization methods, mainly: (i) size of the search space, (ii) type of method (static or dynamic), (iii) modification types of execution plans (re-optimization or re-scheduling), (iv) level of modification (intra-operator and/or inter-operator), (v) type of event (estimation errors, delay, user preferences), and (vi) nature of decision-making (centralized or decentralized control).

Healthcare4VideoStorm: Making Smart Decisions Based on Storm Metrics.

PubMed

Zhang, Weishan; Duan, Pengcheng; Chen, Xiufeng; Lu, Qinghua

2016-04-23

Storm-based stream processing is widely used for real-time large-scale distributed processing. Knowing the run-time status and ensuring performance is critical to providing expected dependability for some applications, e.g., continuous video processing for security surveillance. The existing scheduling strategies' granularity is too coarse to have good performance, and mainly considers network resources without computing resources while scheduling. In this paper, we propose Healthcare4Storm, a framework that finds Storm insights based on Storm metrics to gain knowledge from the health status of an application, finally ending up with smart scheduling decisions. It takes into account both network and computing resources and conducts scheduling at a fine-grained level using tuples instead of topologies. The comprehensive evaluation shows that the proposed framework has good performance and can improve the dependability of the Storm-based applications.

77 FR 35338 - Schedule of Fees Authorized

Federal Register 2010, 2011, 2012, 2013, 2014

2012-06-13

... registration program, to cover the cost of making import eligibility decisions, and to cover the cost of... establishes to cover the costs of ``making the decisions under this subchapter.'' This includes decisions on... for the cost of carrying out the registration program and making eligibility decisions, and to...

Optimal Sizing of Energy Storage for Community Microgrids Considering Building Thermal Dynamics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, Guodong; Li, Zhi; Starke, Michael R.

This paper proposes an optimization model for the optimal sizing of energy storage in community microgrids considering the building thermal dynamics and customer comfort preference. The proposed model minimizes the annualized cost of the community microgrid, including energy storage investment, purchased energy cost, demand charge, energy storage degradation cost, voluntary load shedding cost and the cost associated with customer discomfort due to room temperature deviation. The decision variables are the power and energy capacity of invested energy storage. In particular, we assume the heating, ventilation and air-conditioning (HVAC) systems can be scheduled intelligently by the microgrid central controller while maintainingmore » the indoor temperature in the comfort range set by customers. For this purpose, the detailed thermal dynamic characteristics of buildings have been integrated into the optimization model. Numerical simulation shows significant cost reduction by the proposed model. The impacts of various costs on the optimal solution are investigated by sensitivity analysis.« less

The GBT Dynamic Scheduling System: A New Scheduling Paradigm

NASA Astrophysics Data System (ADS)

O'Neil, K.; Balser, D.; Bignell, C.; Clark, M.; Condon, J.; McCarty, M.; Marganian, P.; Shelton, A.; Braatz, J.; Harnett, J.; Maddalena, R.; Mello, M.; Sessoms, E.

2009-09-01

The Robert C. Byrd Green Bank Telescope (GBT) is implementing a new Dynamic Scheduling System (DSS) designed to maximize the observing efficiency of the telescope while ensuring that none of the flexibility and ease of use of the GBT is harmed and that the data quality of observations is not adversely affected. To accomplish this, the GBT DSS is implementing a dynamic scheduling system which schedules observers, rather than running scripts. The DSS works by breaking each project into one or more sessions which have associated observing criteria such as RA, Dec, and frequency. Potential observers may also enter dates when members of their team will not be available for either on-site or remote observing. The scheduling algorithm uses those data, along with the predicted weather, to determine the most efficient schedule for the GBT. The DSS provides all observers at least 24 hours notice of their upcoming observing. In the uncommon (< 20%) case where the actual weather does not match the predictions, a backup project, chosen from the database, is run instead. Here we give an overview of the GBT DSS project, including the ranking and scheduling algorithms for the sessions, the scheduling probabilities generation, the web framework for the system, and an overview of the results from the beta testing which were held from June - September, 2008.

Application of expert systems in project management decision aiding

NASA Technical Reports Server (NTRS)

Harris, Regina; Shaffer, Steven; Stokes, James; Goldstein, David

1987-01-01

The feasibility of developing an expert systems-based project management decision aid to enhance the performance of NASA project managers was assessed. The research effort included extensive literature reviews in the areas of project management, project management decision aiding, expert systems technology, and human-computer interface engineering. Literature reviews were augmented by focused interviews with NASA managers. Time estimation for project scheduling was identified as the target activity for decision augmentation, and a design was developed for an Integrated NASA System for Intelligent Time Estimation (INSITE). The proposed INSITE design was judged feasible with a low level of risk. A partial proof-of-concept experiment was performed and was successful. Specific conclusions drawn from the research and analyses are included. The INSITE concept is potentially applicable in any management sphere, commercial or government, where time estimation is required for project scheduling. As project scheduling is a nearly universal management activity, the range of possibilities is considerable. The INSITE concept also holds potential for enhancing other management tasks, especially in areas such as cost estimation, where estimation-by-analogy is already a proven method.

Compilation time analysis to minimize run-time overhead in preemptive scheduling on multiprocessors

NASA Astrophysics Data System (ADS)

Wauters, Piet; Lauwereins, Rudy; Peperstraete, J.

1994-10-01

This paper describes a scheduling method for hard real-time Digital Signal Processing (DSP) applications, implemented on a multi-processor. Due to the very high operating frequencies of DSP applications (typically hundreds of kHz) runtime overhead should be kept as small as possible. Because static scheduling introduces very little run-time overhead it is used as much as possible. Dynamic pre-emption of tasks is allowed if and only if it leads to better performance in spite of the extra run-time overhead. We essentially combine static scheduling with dynamic pre-emption using static priorities. Since we are dealing with hard real-time applications we must be able to guarantee at compile-time that all timing requirements will be satisfied at run-time. We will show that our method performs at least as good as any static scheduling method. It also reduces the total amount of dynamic pre-emptions compared with run time methods like deadline monotonic scheduling.

Constraint monitoring in TOSCA

NASA Technical Reports Server (NTRS)

Beck, Howard

1992-01-01

The Job-Shop Scheduling Problem (JSSP) deals with the allocation of resources over time to factory operations. Allocations are subject to various constraints (e.g., production precedence relationships, factory capacity constraints, and limits on the allowable number of machine setups) which must be satisfied for a schedule to be valid. The identification of constraint violations and the monitoring of constraint threats plays a vital role in schedule generation in terms of the following: (1) directing the scheduling process; and (2) informing scheduling decisions. This paper describes a general mechanism for identifying constraint violations and monitoring threats to the satisfaction of constraints throughout schedule generation.

Scheduler Design Criteria: Requirements and Considerations

NASA Technical Reports Server (NTRS)

Lee, Hanbong

2016-01-01

This presentation covers fundamental requirements and considerations for developing schedulers in airport operations. We first introduce performance and functional requirements for airport surface schedulers. Among various optimization problems in airport operations, we focus on airport surface scheduling problem, including runway and taxiway operations. We then describe a basic methodology for airport surface scheduling such as node-link network model and scheduling algorithms previously developed. Next, we explain how to design a mathematical formulation in more details, which consists of objectives, decision variables, and constraints. Lastly, we review other considerations, including optimization tools, computational performance, and performance metrics for evaluation.

143. GENERAL DYNAMICS SPACE SYSTEMS DIVISION SCHEDULE BOARD IN LUNCH ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

143. GENERAL DYNAMICS SPACE SYSTEMS DIVISION SCHEDULE BOARD IN LUNCH ROOM (120), LSB (BLDG. 770) - Vandenberg Air Force Base, Space Launch Complex 3, Launch Pad 3 West, Napa & Alden Roads, Lompoc, Santa Barbara County, CA

Automating Mission Scheduling for Space-Based Observatories

NASA Technical Reports Server (NTRS)

Pell, Barney; Muscettola, Nicola; Hansson, Othar; Mohan, Sunil

1998-01-01

In this paper we describe the use of our planning and scheduling framework, HSTS, to reduce the complexity of science mission planning. This work is part of an overall project to enable a small team of scientists to control the operations of a spacecraft. The present process is highly labor intensive. Users (scientists and operators) rely on a non-codified understanding of the different spacecraft subsystems and of their operating constraints. They use a variety of software tools to support their decision making process. This paper considers the types of decision making that need to be supported/automated, the nature of the domain constraints and the capabilities needed to address them successfully, and the nature of external software systems with which the core planning/scheduling engine needs to interact. HSTS has been applied to science scheduling for EUVE and Cassini and is being adapted to support autonomous spacecraft operations in the New Millennium initiative.

A framework for service enterprise workflow simulation with multi-agents cooperation

NASA Astrophysics Data System (ADS)

Tan, Wenan; Xu, Wei; Yang, Fujun; Xu, Lida; Jiang, Chuanqun

2013-11-01

Process dynamic modelling for service business is the key technique for Service-Oriented information systems and service business management, and the workflow model of business processes is the core part of service systems. Service business workflow simulation is the prevalent approach to be used for analysis of service business process dynamically. Generic method for service business workflow simulation is based on the discrete event queuing theory, which is lack of flexibility and scalability. In this paper, we propose a service workflow-oriented framework for the process simulation of service businesses using multi-agent cooperation to address the above issues. Social rationality of agent is introduced into the proposed framework. Adopting rationality as one social factor for decision-making strategies, a flexible scheduling for activity instances has been implemented. A system prototype has been developed to validate the proposed simulation framework through a business case study.

Risk assessment and adaptive runoff utilization in water resource system considering the complex relationship among water supply, electricity generation and environment

NASA Astrophysics Data System (ADS)

Zhou, J.; Zeng, X.; Mo, L.; Chen, L.; Jiang, Z.; Feng, Z.; Yuan, L.; He, Z.

2017-12-01

Generally, the adaptive utilization and regulation of runoff in the source region of China's southwest rivers is classified as a typical multi-objective collaborative optimization problem. There are grim competitions and incidence relation in the subsystems of water supply, electricity generation and environment, which leads to a series of complex problems represented by hydrological process variation, blocked electricity output and water environment risk. Mathematically, the difficulties of multi-objective collaborative optimization focus on the description of reciprocal relationships and the establishment of evolving model of adaptive systems. Thus, based on the theory of complex systems science, this project tries to carry out the research from the following aspects: the changing trend of coupled water resource, the covariant factor and driving mechanism, the dynamic evolution law of mutual feedback dynamic process in the supply-generation-environment coupled system, the environmental response and influence mechanism of coupled mutual feedback water resource system, the relationship between leading risk factor and multiple risk based on evolutionary stability and dynamic balance, the transfer mechanism of multiple risk response with the variation of the leading risk factor, the multidimensional coupled feedback system of multiple risk assessment index system and optimized decision theory. Based on the above-mentioned research results, the dynamic method balancing the efficiency of multiple objectives in the coupled feedback system and optimized regulation model of water resources is proposed, and the adaptive scheduling mode considering the internal characteristics and external response of coupled mutual feedback system of water resource is established. In this way, the project can make a contribution to the optimal scheduling theory and methodology of water resource management under uncertainty in the source region of Southwest River.

A parallel metaheuristic for large mixed-integer dynamic optimization problems, with applications in computational biology

PubMed Central

Henriques, David; González, Patricia; Doallo, Ramón; Saez-Rodriguez, Julio; Banga, Julio R.

2017-01-01

Background We consider a general class of global optimization problems dealing with nonlinear dynamic models. Although this class is relevant to many areas of science and engineering, here we are interested in applying this framework to the reverse engineering problem in computational systems biology, which yields very large mixed-integer dynamic optimization (MIDO) problems. In particular, we consider the framework of logic-based ordinary differential equations (ODEs). Methods We present saCeSS2, a parallel method for the solution of this class of problems. This method is based on an parallel cooperative scatter search metaheuristic, with new mechanisms of self-adaptation and specific extensions to handle large mixed-integer problems. We have paid special attention to the avoidance of convergence stagnation using adaptive cooperation strategies tailored to this class of problems. Results We illustrate its performance with a set of three very challenging case studies from the domain of dynamic modelling of cell signaling. The simpler case study considers a synthetic signaling pathway and has 84 continuous and 34 binary decision variables. A second case study considers the dynamic modeling of signaling in liver cancer using high-throughput data, and has 135 continuous and 109 binaries decision variables. The third case study is an extremely difficult problem related with breast cancer, involving 690 continuous and 138 binary decision variables. We report computational results obtained in different infrastructures, including a local cluster, a large supercomputer and a public cloud platform. Interestingly, the results show how the cooperation of individual parallel searches modifies the systemic properties of the sequential algorithm, achieving superlinear speedups compared to an individual search (e.g. speedups of 15 with 10 cores), and significantly improving (above a 60%) the performance with respect to a non-cooperative parallel scheme. The scalability of the method is also good (tests were performed using up to 300 cores). Conclusions These results demonstrate that saCeSS2 can be used to successfully reverse engineer large dynamic models of complex biological pathways. Further, these results open up new possibilities for other MIDO-based large-scale applications in the life sciences such as metabolic engineering, synthetic biology, drug scheduling. PMID:28813442

A parallel metaheuristic for large mixed-integer dynamic optimization problems, with applications in computational biology.

PubMed

Penas, David R; Henriques, David; González, Patricia; Doallo, Ramón; Saez-Rodriguez, Julio; Banga, Julio R

2017-01-01

We consider a general class of global optimization problems dealing with nonlinear dynamic models. Although this class is relevant to many areas of science and engineering, here we are interested in applying this framework to the reverse engineering problem in computational systems biology, which yields very large mixed-integer dynamic optimization (MIDO) problems. In particular, we consider the framework of logic-based ordinary differential equations (ODEs). We present saCeSS2, a parallel method for the solution of this class of problems. This method is based on an parallel cooperative scatter search metaheuristic, with new mechanisms of self-adaptation and specific extensions to handle large mixed-integer problems. We have paid special attention to the avoidance of convergence stagnation using adaptive cooperation strategies tailored to this class of problems. We illustrate its performance with a set of three very challenging case studies from the domain of dynamic modelling of cell signaling. The simpler case study considers a synthetic signaling pathway and has 84 continuous and 34 binary decision variables. A second case study considers the dynamic modeling of signaling in liver cancer using high-throughput data, and has 135 continuous and 109 binaries decision variables. The third case study is an extremely difficult problem related with breast cancer, involving 690 continuous and 138 binary decision variables. We report computational results obtained in different infrastructures, including a local cluster, a large supercomputer and a public cloud platform. Interestingly, the results show how the cooperation of individual parallel searches modifies the systemic properties of the sequential algorithm, achieving superlinear speedups compared to an individual search (e.g. speedups of 15 with 10 cores), and significantly improving (above a 60%) the performance with respect to a non-cooperative parallel scheme. The scalability of the method is also good (tests were performed using up to 300 cores). These results demonstrate that saCeSS2 can be used to successfully reverse engineer large dynamic models of complex biological pathways. Further, these results open up new possibilities for other MIDO-based large-scale applications in the life sciences such as metabolic engineering, synthetic biology, drug scheduling.

Automatic generation of efficient orderings of events for scheduling applications

NASA Technical Reports Server (NTRS)

Morris, Robert A.

1994-01-01

In scheduling a set of tasks, it is often not known with certainty how long a given event will take. We call this duration uncertainty. Duration uncertainty is a primary obstacle to the successful completion of a schedule. If a duration of one task is longer than expected, the remaining tasks are delayed. The delay may result in the abandonment of the schedule itself, a phenomenon known as schedule breakage. One response to schedule breakage is on-line, dynamic rescheduling. A more recent alternative is called proactive rescheduling. This method uses statistical data about the durations of events in order to anticipate the locations in the schedule where breakage is likely prior to the execution of the schedule. It generates alternative schedules at such sensitive points, which can be then applied by the scheduler at execution time, without the delay incurred by dynamic rescheduling. This paper proposes a technique for making proactive error management more effective. The technique is based on applying a similarity-based method of clustering to the problem of identifying similar events in a set of events.

System-level power optimization for real-time distributed embedded systems

NASA Astrophysics Data System (ADS)

Luo, Jiong

Power optimization is one of the crucial design considerations for modern electronic systems. In this thesis, we present several system-level power optimization techniques for real-time distributed embedded systems, based on dynamic voltage scaling, dynamic power management, and management of peak power and variance of the power profile. Dynamic voltage scaling has been widely acknowledged as an important and powerful technique to trade off dynamic power consumption and delay. Efficient dynamic voltage scaling requires effective variable-voltage scheduling mechanisms that can adjust voltages and clock frequencies adaptively based on workloads and timing constraints. For this purpose, we propose static variable-voltage scheduling algorithms utilizing criticalpath driven timing analysis for the case when tasks are assumed to have uniform switching activities, as well as energy-gradient driven slack allocation for a more general scenario. The proposed techniques can achieve closeto-optimal power savings with very low computational complexity, without violating any real-time constraints. We also present algorithms for power-efficient joint scheduling of multi-rate periodic task graphs along with soft aperiodic tasks. The power issue is addressed through both dynamic voltage scaling and power management. Periodic task graphs are scheduled statically. Flexibility is introduced into the static schedule to allow the on-line scheduler to make local changes to PE schedules through resource reclaiming and slack stealing, without interfering with the validity of the global schedule. We provide a unified framework in which the response times of aperiodic tasks and power consumption are dynamically optimized simultaneously. Interconnection network fabrics point to a new generation of power-efficient and scalable interconnection architectures for distributed embedded systems. As the system bandwidth continues to increase, interconnection networks become power/energy limited as well. Variable-frequency links have been designed by circuit designers for both parallel and serial links, which can adaptively regulate the supply voltage of transceivers to a desired link frequency, to exploit the variations in bandwidth requirement for power savings. We propose solutions for simultaneous dynamic voltage scaling of processors and links. The proposed solution considers real-time scheduling, flow control, and packet routing jointly. It can trade off the power consumption on processors and communication links via efficient slack allocation, and lead to more power savings than dynamic voltage scaling on processors alone. For battery-operated systems, the battery lifespan is an important concern. Due to the effects of discharge rate and battery recovery, the discharge pattern of batteries has an impact on the battery lifespan. Battery models indicate that even under the same average power consumption, reducing peak power current and variance in the power profile can increase the battery efficiency and thereby prolong battery lifetime. To take advantage of these effects, we propose battery-driven scheduling techniques for embedded applications, to reduce the peak power and the variance in the power profile of the overall system under real-time constraints. The proposed scheduling algorithms are also beneficial in addressing reliability and signal integrity concerns by effectively controlling peak power and variance of the power profile.

5 CFR 511.612 - Finality of decision.

Code of Federal Regulations, 2011 CFR

2011-01-01

....612 Administrative Personnel OFFICE OF PERSONNEL MANAGEMENT CIVIL SERVICE REGULATIONS CLASSIFICATION UNDER THE GENERAL SCHEDULE Classification Appeals § 511.612 Finality of decision. An appellate decision made by the Office is final unless reconsidered by the Office. There is no further right of appeal. The...

5 CFR 511.701 - Effective dates generally.

Code of Federal Regulations, 2010 CFR

2010-01-01

...) Except as provided in § 511.703, classification actions may not be made retroactive. (b) Office of Personnel Management's classification decision. (1) The effective date of a classification decision made by... CLASSIFICATION UNDER THE GENERAL SCHEDULE Effective Dates of Position Classification Actions or Decisions § 511...

5 CFR 511.701 - Effective dates generally.

Code of Federal Regulations, 2011 CFR

2011-01-01

...) Except as provided in § 511.703, classification actions may not be made retroactive. (b) Office of Personnel Management's classification decision. (1) The effective date of a classification decision made by... CLASSIFICATION UNDER THE GENERAL SCHEDULE Effective Dates of Position Classification Actions or Decisions § 511...

Designing a data-driven decision support tool for nurse scheduling in the emergency department: a case study of a southern New Jersey emergency department.

PubMed

Otegbeye, Mojisola; Scriber, Roslyn; Ducoin, Donna; Glasofer, Amy

2015-01-01

A health system serving Burlington and Camden Counties, New Jersey, sought to improve labor productivity for its emergency departments, with emphasis on optimizing nursing staff schedules. Using historical emergency department visit data and operating constraints, a decision support tool was designed to recommend the number of emergency nurses needed in each hour for each day of the week. The pilot emergency department nurse managers used the decision support tool's recommendations to redeploy nurse hours from weekends into a float pool to support periods of demand spikes on weekdays. Productivity improved significantly, with no unfavorable impact on patient throughput, and patient and staff satisfaction. Today's emergency department manager can leverage the increasing ease of access to the emergency department information system's data repository to successfully design a simple but effective tool to support the alignment of its nursing schedule with demand patterns. Copyright © 2015 Emergency Nurses Association. Published by Elsevier Inc. All rights reserved.

The current state of introduction of HPV vaccination into national immunisation schedules in Europe: results of the VENICE 2008 survey.

PubMed

Lévy-Bruhl, D; Bousquet, V; King, L A; O'Flanagan, D; Bacci, S; Lopalco, P L; Salmaso, S

2009-10-01

Three surveys have been undertaken in European Union (EU) member states since January 2007, within the European Commission funded Vaccine European New Integrated Collaboration Effort (VENICE) project, to monitor the decision status regarding the introduction of human papillomavirus (HPV) vaccination into national immunisation schedules. A web-based questionnaire was developed and completed online by the 28 countries participating in VENICE. According to the last update (31st December 2008), 15 countries have decided to introduce HPV vaccination into their national immunisation schedule, while another six have started the decision-making process with a recommendation favouring introduction. Varying target populations have been selected by the countries which have introduced vaccination. The number of countries which have made a decision or recommendation has increased from 12 to 21 between October 2007 and December 2008. This survey demonstrates the rapidly evolving nature of HPV vaccine introduction in Europe. A further update should be available in the second half of 2009.

Health Care Decision Support System for the Pediatric Emeregency Department Management.

PubMed

Ben Othman, Sarah; Hammadi, Slim; Quilliot, Alain; Martinot, Alain; Renard, Jean-Marie

2015-01-01

Health organization management is facing a high amount of complexity due to the inherent dynamics of the processes and the distributed organization of hospitals. It is therefore necessary for health care institutions to focus on this issue in order to deal with patients' requirements and satisfy their needs. The main objective of this study is to develop and implement a Decision Support System which can help physicians to better manage their organization, to anticipate the overcrowding feature, and to establish avoidance proposals for it. This work is a part of HOST project (Hospital: Optimization, Simulation, and Crowding Avoidance) of the French National Research Agency (ANR). It aims to optimize the functioning of the Pediatric Emergency Department characterized by stochastic arrivals of patients which leads to its overcrowding and services overload. Our study is a set of tools to smooth out patient flows, enhance care quality and minimize long waiting times and costs due to resources allocation. So we defined a decision aided tool based on Multi-agent Systems where actors negotiate and cooperate under some constraints in a dynamic environment. These entities which can be either physical agents representing real actors in the health care institution or software agents allowing the implementation of optimizing tools, cooperate to satisfy the demands of patients while respecting emergency degrees. This paper is concerned with agents' negotiation. It proposes a new approach for multi-skill tasks scheduling based on interactions between agents.

An operation support expert system based on on-line dynamics simulation and fuzzy reasoning for startup schedule optimization in fossil power plants

DOE Office of Scientific and Technical Information (OSTI.GOV)

Matsumoto, H.; Eki, Y.; Kaji, A.

1993-12-01

An expert system which can support operators of fossil power plants in creating the optimum startup schedule and executing it accurately is described. The optimum turbine speed-up and load-up pattern is obtained through an iterative manner which is based on fuzzy resonating using quantitative calculations as plant dynamics models and qualitative knowledge as schedule optimization rules with fuzziness. The rules represent relationships between stress margins and modification rates of the schedule parameters. Simulations analysis proves that the system provides quick and accurate plant startups.

Distributed decision-making in electric power system transmission maintenance scheduling using multi-agent systems (MAS)

NASA Astrophysics Data System (ADS)

Zhang, Zhong

In this work, motivated by the need to coordinate transmission maintenance scheduling among a multiplicity of self-interested entities in restructured power industry, a distributed decision support framework based on multiagent negotiation systems (MANS) is developed. An innovative risk-based transmission maintenance optimization procedure is introduced. Several models for linking condition monitoring information to the equipment's instantaneous failure probability are presented, which enable quantitative evaluation of the effectiveness of maintenance activities in terms of system cumulative risk reduction. Methodologies of statistical processing, equipment deterioration evaluation and time-dependent failure probability calculation are also described. A novel framework capable of facilitating distributed decision-making through multiagent negotiation is developed. A multiagent negotiation model is developed and illustrated that accounts for uncertainty and enables social rationality. Some issues of multiagent negotiation convergence and scalability are discussed. The relationships between agent-based negotiation and auction systems are also identified. A four-step MAS design methodology for constructing multiagent systems for power system applications is presented. A generic multiagent negotiation system, capable of inter-agent communication and distributed decision support through inter-agent negotiations, is implemented. A multiagent system framework for facilitating the automated integration of condition monitoring information and maintenance scheduling for power transformers is developed. Simulations of multiagent negotiation-based maintenance scheduling among several independent utilities are provided. It is shown to be a viable alternative solution paradigm to the traditional centralized optimization approach in today's deregulated environment. This multiagent system framework not only facilitates the decision-making among competing power system entities, but also provides a tool to use in studying competitive industry relative to monopolistic industry.

5 CFR 511.602 - Notification of classification decision.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 5 Administrative Personnel 1 2010-01-01 2010-01-01 false Notification of classification decision... REGULATIONS CLASSIFICATION UNDER THE GENERAL SCHEDULE Classification Appeals § 511.602 Notification of classification decision. An employee whose position is reclassified to a lower grade which is based in whole or...

5 CFR 511.602 - Notification of classification decision.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 5 Administrative Personnel 1 2011-01-01 2011-01-01 false Notification of classification decision... REGULATIONS CLASSIFICATION UNDER THE GENERAL SCHEDULE Classification Appeals § 511.602 Notification of classification decision. An employee whose position is reclassified to a lower grade which is based in whole or...

Dementia: Diagnosis and Tests

MedlinePlus

... for is having problems with memory, language, and decision-making that seem to be getting worse, schedule an ... the person’s physical and mental abilities, mood, personality, decision-making, or behavior. Ask about possible delusions or hallucinations ...

User interface issues in supporting human-computer integrated scheduling

NASA Technical Reports Server (NTRS)

Cooper, Lynne P.; Biefeld, Eric W.

1991-01-01

The topics are presented in view graph form and include the following: characteristics of Operations Mission Planner (OMP) schedule domain; OMP architecture; definition of a schedule; user interface dimensions; functional distribution; types of users; interpreting user interaction; dynamic overlays; reactive scheduling; and transitioning the interface.

IOPS advisor: Research in progress on knowledge-intensive methods for irregular operations airline scheduling

NASA Technical Reports Server (NTRS)

Borse, John E.; Owens, Christopher C.

1992-01-01

Our research focuses on the problem of recovering from perturbations in large-scale schedules, specifically on the ability of a human-machine partnership to dynamically modify an airline schedule in response to unanticipated disruptions. This task is characterized by massive interdependencies and a large space of possible actions. Our approach is to apply the following: qualitative, knowledge-intensive techniques relying on a memory of stereotypical failures and appropriate recoveries; and quantitative techniques drawn from the Operations Research community's work on scheduling. Our main scientific challenge is to represent schedules, failures, and repairs so as to make both sets of techniques applicable to the same data. This paper outlines ongoing research in which we are cooperating with United Airlines to develop our understanding of the scientific issues underlying the practicalities of dynamic, real-time schedule repair.

Cloud computing task scheduling strategy based on improved differential evolution algorithm

NASA Astrophysics Data System (ADS)

Ge, Junwei; He, Qian; Fang, Yiqiu

2017-04-01

In order to optimize the cloud computing task scheduling scheme, an improved differential evolution algorithm for cloud computing task scheduling is proposed. Firstly, the cloud computing task scheduling model, according to the model of the fitness function, and then used improved optimization calculation of the fitness function of the evolutionary algorithm, according to the evolution of generation of dynamic selection strategy through dynamic mutation strategy to ensure the global and local search ability. The performance test experiment was carried out in the CloudSim simulation platform, the experimental results show that the improved differential evolution algorithm can reduce the cloud computing task execution time and user cost saving, good implementation of the optimal scheduling of cloud computing tasks.

5 CFR 511.702 - Agency or Office classification appeal decisions.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 5 Administrative Personnel 1 2010-01-01 2010-01-01 false Agency or Office classification appeal... REGULATIONS CLASSIFICATION UNDER THE GENERAL SCHEDULE Effective Dates of Position Classification Actions or Decisions § 511.702 Agency or Office classification appeal decisions. (a) Subject to § 511.703, the...

5 CFR 511.702 - Agency or Office classification appeal decisions.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 5 Administrative Personnel 1 2011-01-01 2011-01-01 false Agency or Office classification appeal... REGULATIONS CLASSIFICATION UNDER THE GENERAL SCHEDULE Effective Dates of Position Classification Actions or Decisions § 511.702 Agency or Office classification appeal decisions. (a) Subject to § 511.703, the...

Ethical Dilemmas for School Administrators

ERIC Educational Resources Information Center

Denig, Stephen J.; Quinn, Terrence

2001-01-01

Schools are ethical organizations. The daily schedule of educational administrators is filled with ethical dilemmas and moral decisions. As reflective practitioners, school leaders know that the decisions that are made and the values that underlie those decisions are filled with moral implications for the entire school community. In this paper,…

Effects of NMDA receptor antagonists on probability discounting depend on the order of probability presentation.

PubMed

Yates, Justin R; Breitenstein, Kerry A; Gunkel, Benjamin T; Hughes, Mallory N; Johnson, Anthony B; Rogers, Katherine K; Shape, Sara M

Risky decision making can be measured using a probability-discounting procedure, in which animals choose between a small, certain reinforcer and a large, uncertain reinforcer. Recent evidence has identified glutamate as a mediator of risky decision making, as blocking the N-methyl-d-aspartate (NMDA) receptor with MK-801 increases preference for a large, uncertain reinforcer. Because the order in which probabilities associated with the large reinforcer can modulate the effects of drugs on choice, the current study determined if NMDA receptor ligands alter probability discounting using ascending and descending schedules. Sixteen rats were trained in a probability-discounting procedure in which the odds against obtaining the large reinforcer increased (n=8) or decreased (n=8) across blocks of trials. Following behavioral training, rats received treatments of the NMDA receptor ligands MK-801 (uncompetitive antagonist; 0, 0.003, 0.01, or 0.03mg/kg), ketamine (uncompetitive antagonist; 0, 1.0, 5.0, or 10.0mg/kg), and ifenprodil (NR2B-selective non-competitive antagonist; 0, 1.0, 3.0, or 10.0mg/kg). Results showed discounting was steeper (indicating increased risk aversion) for rats on an ascending schedule relative to rats on the descending schedule. Furthermore, the effects of MK-801, ketamine, and ifenprodil on discounting were dependent on the schedule used. Specifically, the highest dose of each drug decreased risk taking in rats in the descending schedule, but only MK-801 (0.03mg/kg) increased risk taking in rats on an ascending schedule. These results show that probability presentation order modulates the effects of NMDA receptor ligands on risky decision making. Copyright © 2016 Elsevier Inc. All rights reserved.

Production Planning and Planting Pattern Scheduling Information System for Horticulture

NASA Astrophysics Data System (ADS)

Vitadiar, Tanhella Zein; Farikhin; Surarso, Bayu

2018-02-01

This paper present the production of planning and planting pattern scheduling faced by horticulture farmer using two methods. Fuzzy time series method use to predict demand on based on sales amount, while linear programming is used to assist horticulture farmers in making production planning decisions and determining the schedule of cropping patterns in accordance with demand predictions of the fuzzy time series method, variable use in this paper is size of areas, production advantage, amount of seeds and age of the plants. This research result production planning and planting patterns scheduling information system with the output is recommendations planting schedule, harvest schedule and the number of seeds will be plant.

Tera-OP Reliable Intelligently Adaptive Processing System (TRIPS) Implementation

DTIC Science & Technology

2008-09-01

38 6.8 Instruction Scheduling ...39 6.8.1 Spatial Path Scheduling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39 6.8.2...oblivious scheduling for rapid application prototyping and deployment, environmental adaptivity for resilience in hostile environments, and dynamic

Exact and Heuristic Algorithms for Runway Scheduling

NASA Technical Reports Server (NTRS)

Malik, Waqar A.; Jung, Yoon C.

2016-01-01

This paper explores the Single Runway Scheduling (SRS) problem with arrivals, departures, and crossing aircraft on the airport surface. Constraints for wake vortex separations, departure area navigation separations and departure time window restrictions are explicitly considered. The main objective of this research is to develop exact and heuristic based algorithms that can be used in real-time decision support tools for Air Traffic Control Tower (ATCT) controllers. The paper provides a multi-objective dynamic programming (DP) based algorithm that finds the exact solution to the SRS problem, but may prove unusable for application in real-time environment due to large computation times for moderate sized problems. We next propose a second algorithm that uses heuristics to restrict the search space for the DP based algorithm. A third algorithm based on a combination of insertion and local search (ILS) heuristics is then presented. Simulation conducted for the east side of Dallas/Fort Worth International Airport allows comparison of the three proposed algorithms and indicates that the ILS algorithm performs favorably in its ability to find efficient solutions and its computation times.

An Interactive Decision Support System for Scheduling Fighter Pilot Training

DTIC Science & Technology

2002-03-26

Deitel , H.M. and Deitel , P.J. C: How to Program , 2nd ed., Prentice Hall, 1994. 8. Deitel , H.M. and Deitel , P.J. How to Program Java...Visual Basic Programming language, the Excel tool is modified in several ways. Scheduling Dispatch rules are implemented to automatically generate... programming language, the Excel tool was modified in several ways. Scheduling dispatch rules are implemented to automatically generate

NASA's Software Bank (CLIPS)

NASA Technical Reports Server (NTRS)

1992-01-01

C Language Integrated Production System (CLIPS) was used by Esse Systems to develop an expert system for clients who want to automate portions of their operations. The resulting program acts as a scheduling expert and automates routine, repetitive scheduling decisions, allowing employees to spend time on more creative projects.

An improved robust buffer allocation method for the project scheduling problem

NASA Astrophysics Data System (ADS)

Ghoddousi, Parviz; Ansari, Ramin; Makui, Ahmad

2017-04-01

Unpredictable uncertainties cause delays and additional costs for projects. Often, when using traditional approaches, the optimizing procedure of the baseline project plan fails and leads to delays. In this study, a two-stage multi-objective buffer allocation approach is applied for robust project scheduling. In the first stage, some decisions are made on buffer sizes and allocation to the project activities. A set of Pareto-optimal robust schedules is designed using the meta-heuristic non-dominated sorting genetic algorithm (NSGA-II) based on the decisions made in the buffer allocation step. In the second stage, the Pareto solutions are evaluated in terms of the deviation from the initial start time and due dates. The proposed approach was implemented on a real dam construction project. The outcomes indicated that the obtained buffered schedule reduces the cost of disruptions by 17.7% compared with the baseline plan, with an increase of about 0.3% in the project completion time.

Stochastic Routing and Scheduling Policies for Energy Harvesting Communication Networks

NASA Astrophysics Data System (ADS)

Calvo-Fullana, Miguel; Anton-Haro, Carles; Matamoros, Javier; Ribeiro, Alejandro

2018-07-01

In this paper, we study the joint routing-scheduling problem in energy harvesting communication networks. Our policies, which are based on stochastic subgradient methods on the dual domain, act as an energy harvesting variant of the stochastic family of backpresure algorithms. Specifically, we propose two policies: (i) the Stochastic Backpressure with Energy Harvesting (SBP-EH), in which a node's routing-scheduling decisions are determined by the difference between the Lagrange multipliers associated to their queue stability constraints and their neighbors'; and (ii) the Stochastic Soft Backpressure with Energy Harvesting (SSBP-EH), an improved algorithm where the routing-scheduling decision is of a probabilistic nature. For both policies, we show that given sustainable data and energy arrival rates, the stability of the data queues over all network nodes is guaranteed. Numerical results corroborate the stability guarantees and illustrate the minimal gap in performance that our policies offer with respect to classical ones which work with an unlimited energy supply.

Coordinating space telescope operations in an integrated planning and scheduling architecture

NASA Technical Reports Server (NTRS)

Muscettola, Nicola; Smith, Stephen F.; Cesta, Amedeo; D'Aloisi, Daniela

1992-01-01

The Heuristic Scheduling Testbed System (HSTS), a software architecture for integrated planning and scheduling, is discussed. The architecture has been applied to the problem of generating observation schedules for the Hubble Space Telescope. This problem is representative of the class of problems that can be addressed: their complexity lies in the interaction of resource allocation and auxiliary task expansion. The architecture deals with this interaction by viewing planning and scheduling as two complementary aspects of the more general process of constructing behaviors of a dynamical system. The principal components of the software architecture are described, indicating how to model the structure and dynamics of a system, how to represent schedules at multiple levels of abstraction in the temporal database, and how the problem solving machinery operates. A scheduler for the detailed management of Hubble Space Telescope operations that has been developed within HSTS is described. Experimental performance results are given that indicate the utility and practicality of the approach.

The application of Firefly algorithm in an Adaptive Emergency Evacuation Centre Management (AEECM) for dynamic relocation of flood victims

NASA Astrophysics Data System (ADS)

ChePa, Noraziah; Hashim, Nor Laily; Yusof, Yuhanis; Hussain, Azham

2016-08-01

Flood evacuation centre is defined as a temporary location or area of people from disaster particularly flood as a rescue or precautionary measure. Gazetted evacuation centres are normally located at secure places which have small chances from being drowned by flood. However, due to extreme flood several evacuation centres in Kelantan were unexpectedly drowned. Currently, there is no study done on proposing a decision support aid to reallocate victims and resources of the evacuation centre when the situation getting worsens. Therefore, this study proposes a decision aid model to be utilized in realizing an adaptive emergency evacuation centre management system. This study undergoes two main phases; development of algorithm and models, and development of a web-based and mobile app. The proposed model operates using Firefly multi-objective optimization algorithm that creates an optimal schedule for the relocation of victims and resources for an evacuation centre. The proposed decision aid model and the adaptive system can be applied in supporting the National Security Council's respond mechanisms for handling disaster management level II (State level) especially in providing better management of the flood evacuating centres.

Space shuttle maintenance program planning document

NASA Technical Reports Server (NTRS)

Brown, D. V.

1972-01-01

A means for developing a space shuttle maintenance program which will be acceptable to the development centers, the operators (KSC and AF), and the manufacturer is presented. The general organization and decision processes for determining the essential scheduled maintenance requirements for the space shuttle orbiter are outlined. The development of initial scheduled maintenance programs is discussed. The remaining maintenance, that is non-scheduled or non-routine maintenance, is directed by the findings of the scheduled maintenance program and the normal operation of the shuttle. The remaining maintenance consists of maintenance actions to correct discrepancies noted during scheduled maintenance tasks, nonscheduled maintenance, normal operation, or condition monitoring.

40 CFR 300.920 - Addition of products to Schedule.

Code of Federal Regulations, 2011 CFR

2011-07-01

... manufacturer of his decision in writing. (b) Surface washing agents, surface collecting agents, bioremediation... collecting agent, bioremediation agent, or miscellaneous oil spill control agent to the NCP Product Schedule... collecting agent, bioremediation agent, or miscellaneous oil spill control agent. On the basis of this data...

40 CFR 300.920 - Addition of products to Schedule.

Code of Federal Regulations, 2014 CFR

2014-07-01

... manufacturer of his decision in writing. (b) Surface washing agents, surface collecting agents, bioremediation... collecting agent, bioremediation agent, or miscellaneous oil spill control agent to the NCP Product Schedule... collecting agent, bioremediation agent, or miscellaneous oil spill control agent. On the basis of this data...

40 CFR 300.920 - Addition of products to Schedule.

Code of Federal Regulations, 2012 CFR

2012-07-01

... manufacturer of his decision in writing. (b) Surface washing agents, surface collecting agents, bioremediation... collecting agent, bioremediation agent, or miscellaneous oil spill control agent to the NCP Product Schedule... collecting agent, bioremediation agent, or miscellaneous oil spill control agent. On the basis of this data...

40 CFR 300.920 - Addition of products to Schedule.

Code of Federal Regulations, 2013 CFR

2013-07-01

... manufacturer of his decision in writing. (b) Surface washing agents, surface collecting agents, bioremediation... collecting agent, bioremediation agent, or miscellaneous oil spill control agent to the NCP Product Schedule... collecting agent, bioremediation agent, or miscellaneous oil spill control agent. On the basis of this data...

40 CFR 300.920 - Addition of products to Schedule.

Code of Federal Regulations, 2010 CFR

2010-07-01

... manufacturer of his decision in writing. (b) Surface washing agents, surface collecting agents, bioremediation... collecting agent, bioremediation agent, or miscellaneous oil spill control agent to the NCP Product Schedule... collecting agent, bioremediation agent, or miscellaneous oil spill control agent. On the basis of this data...

Discrete event simulation for healthcare organizations: a tool for decision making.

PubMed

Hamrock, Eric; Paige, Kerrie; Parks, Jennifer; Scheulen, James; Levin, Scott

2013-01-01

Healthcare organizations face challenges in efficiently accommodating increased patient demand with limited resources and capacity. The modern reimbursement environment prioritizes the maximization of operational efficiency and the reduction of unnecessary costs (i.e., waste) while maintaining or improving quality. As healthcare organizations adapt, significant pressures are placed on leaders to make difficult operational and budgetary decisions. In lieu of hard data, decision makers often base these decisions on subjective information. Discrete event simulation (DES), a computerized method of imitating the operation of a real-world system (e.g., healthcare delivery facility) over time, can provide decision makers with an evidence-based tool to develop and objectively vet operational solutions prior to implementation. DES in healthcare commonly focuses on (1) improving patient flow, (2) managing bed capacity, (3) scheduling staff, (4) managing patient admission and scheduling procedures, and (5) using ancillary resources (e.g., labs, pharmacies). This article describes applicable scenarios, outlines DES concepts, and describes the steps required for development. An original DES model developed to examine crowding and patient flow for staffing decision making at an urban academic emergency department serves as a practical example.

An Extended Deterministic Dendritic Cell Algorithm for Dynamic Job Shop Scheduling

NASA Astrophysics Data System (ADS)

Qiu, X. N.; Lau, H. Y. K.

The problem of job shop scheduling in a dynamic environment where random perturbation exists in the system is studied. In this paper, an extended deterministic Dendritic Cell Algorithm (dDCA) is proposed to solve such a dynamic Job Shop Scheduling Problem (JSSP) where unexpected events occurred randomly. This algorithm is designed based on dDCA and makes improvements by considering all types of signals and the magnitude of the output values. To evaluate this algorithm, ten benchmark problems are chosen and different kinds of disturbances are injected randomly. The results show that the algorithm performs competitively as it is capable of triggering the rescheduling process optimally with much less run time for deciding the rescheduling action. As such, the proposed algorithm is able to minimize the rescheduling times under the defined objective and to keep the scheduling process stable and efficient.

Final Report on DOE Project entitled Dynamic Optimized Advanced Scheduling of Bandwidth Demands for Large-Scale Science Applications

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ramamurthy, Byravamurthy

2014-05-05

In this project, developed scheduling frameworks for dynamic bandwidth demands for large-scale science applications. In particular, we developed scheduling algorithms for dynamic bandwidth demands in this project. Apart from theoretical approaches such as Integer Linear Programming, Tabu Search and Genetic Algorithm heuristics, we have utilized practical data from ESnet OSCARS project (from our DOE lab partners) to conduct realistic simulations of our approaches. We have disseminated our work through conference paper presentations and journal papers and a book chapter. In this project we addressed the problem of scheduling of lightpaths over optical wavelength division multiplexed (WDM) networks. We published severalmore » conference papers and journal papers on this topic. We also addressed the problems of joint allocation of computing, storage and networking resources in Grid/Cloud networks and proposed energy-efficient mechanisms for operatin optical WDM networks.« less

Complexity of line-seru conversion for different scheduling rules and two improved exact algorithms for the multi-objective optimization.

PubMed

Yu, Yang; Wang, Sihan; Tang, Jiafu; Kaku, Ikou; Sun, Wei

2016-01-01

Productivity can be greatly improved by converting the traditional assembly line to a seru system, especially in the business environment with short product life cycles, uncertain product types and fluctuating production volumes. Line-seru conversion includes two decision processes, i.e., seru formation and seru load. For simplicity, however, previous studies focus on the seru formation with a given scheduling rule in seru load. We select ten scheduling rules usually used in seru load to investigate the influence of different scheduling rules on the performance of line-seru conversion. Moreover, we clarify the complexities of line-seru conversion for ten different scheduling rules from the theoretical perspective. In addition, multi-objective decisions are often used in line-seru conversion. To obtain Pareto-optimal solutions of multi-objective line-seru conversion, we develop two improved exact algorithms based on reducing time complexity and space complexity respectively. Compared with the enumeration based on non-dominated sorting to solve multi-objective problem, the two improved exact algorithms saves computation time greatly. Several numerical simulation experiments are performed to show the performance improvement brought by the two proposed exact algorithms.

Automated Planning and Scheduling for Space Mission Operations

NASA Technical Reports Server (NTRS)

Chien, Steve; Jonsson, Ari; Knight, Russell

2005-01-01

Research Trends: a) Finite-capacity scheduling under more complex constraints and increased problem dimensionality (subcontracting, overtime, lot splitting, inventory, etc.) b) Integrated planning and scheduling. c) Mixed-initiative frameworks. d) Management of uncertainty (proactive and reactive). e) Autonomous agent architectures and distributed production management. e) Integration of machine learning capabilities. f) Wider scope of applications: 1) analysis of supplier/buyer protocols & tradeoffs; 2) integration of strategic & tactical decision-making; and 3) enterprise integration.

Proceedings of the Annual ONR/CADRC Decision-Support Workshop (6th), Held in Quantico, Virginia, on 8-9 Sep 2004. Interoperability

DTIC Science & Technology

2004-11-01

fixed schedule checkups and overhauls), Underway Replenishment (the goal being operation in sea states 3 and higher via technical improvements to...determine whether sufficient local resources are available to deal with current conditions. Scheduling Agent: Assists the Emergency Operations Bureau to...will commence per predefined schedule within 15 minutes) and subsequently alerts its subscribers that the rolling power blackout has commenced. The

Effects of maneuver dynamics on drag polars of the X-29A forward-swept-wing aircraft with automatic wing camber control

NASA Technical Reports Server (NTRS)

Hicks, John W.; Moulton, Bryan J.

1988-01-01

The camber control loop of the X-29A FSW aircraft was designed to furnish the optimum L/D for trimmed, stabilized flight. A marked difference was noted between automatic wing camber control loop behavior in dynamic maneuvers and in stabilized flight conditions, which in turn affected subsonic aerodynamic performance. The degree of drag level increase was a direct function of maneuver rate. Attention is given to the aircraft flight drag polar effects of maneuver dynamics in light of wing camber control loop schedule. The effect of changing camber scheduling to better track the optimum automatic camber control L/D schedule is discussed.

Dynamic Scheduling for Veterans Health Administration Patients using Geospatial Dynamic Overbooking.

PubMed

Adams, Stephen; Scherer, William T; White, K Preston; Payne, Jason; Hernandez, Oved; Gerber, Mathew S; Whitehead, N Peter

2017-10-12

The Veterans Health Administration (VHA) is plagued by abnormally high no-show and cancellation rates that reduce the productivity and efficiency of its medical outpatient clinics. We address this issue by developing a dynamic scheduling system that utilizes mobile computing via geo-location data to estimate the likelihood of a patient arriving on time for a scheduled appointment. These likelihoods are used to update the clinic's schedule in real time. When a patient's arrival probability falls below a given threshold, the patient's appointment is canceled. This appointment is immediately reassigned to another patient drawn from a pool of patients who are actively seeking an appointment. The replacement patients are prioritized using their arrival probability. Real-world data were not available for this study, so synthetic patient data were generated to test the feasibility of the design. The method for predicting the arrival probability was verified on a real set of taxicab data. This study demonstrates that dynamic scheduling using geo-location data can reduce the number of unused appointments with minimal risk of double booking resulting from incorrect predictions. We acknowledge that there could be privacy concerns with regards to government possession of one's location and offer strategies for alleviating these concerns in our conclusion.

An ex ante control chart for project monitoring using earned duration management observations

NASA Astrophysics Data System (ADS)

Mortaji, Seyed Taha Hossein; Noori, Siamak; Noorossana, Rassoul; Bagherpour, Morteza

2017-12-01

In the past few years, there has been an increasing interest in developing project control systems. The primary purpose of such systems is to indicate whether the actual performance is consistent with the baseline and to produce a signal in the case of non-compliance. Recently, researchers have shown an increased interest in monitoring project's performance indicators, by plotting them on the Shewhart-type control charts over time. However, these control charts are fundamentally designed for processes and ignore project-specific dynamics, which can lead to weak results and misleading interpretations. By paying close attention to the project baseline schedule and using statistical foundations, this paper proposes a new ex ante control chart which discriminates between acceptable (as-planned) and non-acceptable (not-as-planned) variations of the project's schedule performance. Such control chart enables project managers to set more realistic thresholds leading to a better decision making for taking corrective and/or preventive actions. For the sake of clarity, an illustrative example has been presented to show how the ex ante control chart is constructed in practice. Furthermore, an experimental investigation has been set up to analyze the performance of the proposed control chart. As expected, the results confirm that, when a project starts to deflect significantly from the project's baseline schedule, the ex ante control chart shows a respectable ability to detect and report right signals while avoiding false alarms.

5 CFR 315.710 - Professional and administrative career employees serving under Schedule B appointments.

Code of Federal Regulations, 2010 CFR

2010-01-01

... result of a deliberate decision by management. (c) Tenure on conversion. An employee converted under... employees serving under Schedule B appointments. 315.710 Section 315.710 Administrative Personnel OFFICE OF PERSONNEL MANAGEMENT CIVIL SERVICE REGULATIONS CAREER AND CAREER-CONDITIONAL EMPLOYMENT Conversion to Career...

Assessment of need and feasibility of truck-mounted changeable message signs (CMS) for scheduled and unscheduled operations : technical report.

DOT National Transportation Integrated Search

2010-10-01

The goal of this project was to develop implementation guidance that the Texas Department of Transportation : (TxDOT) can use to make better decisions regarding the use of truck mounted changeable message signs : (TMCMS) during scheduled and unschedu...

TethysCluster: A comprehensive approach for harnessing cloud resources for hydrologic modeling

NASA Astrophysics Data System (ADS)

Nelson, J.; Jones, N.; Ames, D. P.

2015-12-01

Advances in water resources modeling are improving the information that can be supplied to support decisions affecting the safety and sustainability of society. However, as water resources models become more sophisticated and data-intensive they require more computational power to run. Purchasing and maintaining the computing facilities needed to support certain modeling tasks has been cost-prohibitive for many organizations. With the advent of the cloud, the computing resources needed to address this challenge are now available and cost-effective, yet there still remains a significant technical barrier to leverage these resources. This barrier inhibits many decision makers and even trained engineers from taking advantage of the best science and tools available. Here we present the Python tools TethysCluster and CondorPy, that have been developed to lower the barrier to model computation in the cloud by providing (1) programmatic access to dynamically scalable computing resources, (2) a batch scheduling system to queue and dispatch the jobs to the computing resources, (3) data management for job inputs and outputs, and (4) the ability to dynamically create, submit, and monitor computing jobs. These Python tools leverage the open source, computing-resource management, and job management software, HTCondor, to offer a flexible and scalable distributed-computing environment. While TethysCluster and CondorPy can be used independently to provision computing resources and perform large modeling tasks, they have also been integrated into Tethys Platform, a development platform for water resources web apps, to enable computing support for modeling workflows and decision-support systems deployed as web apps.

77 FR 65137 - Consideration of Environmental Impacts of Temporary Storage of Spent Fuel After Cessation of...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-10-25

... provide input to decision-making for updating the Waste Confidence Decision and Rule and would not involve... Commission's tentative planning and decision-making schedule; g. Identify any cooperating agencies and, as... #0;notices is to give interested persons an opportunity to participate in #0;the rule making prior to...

Bases for Curriculum Decisions for Development of Curriculum for Minorities in Small Business Ownership and Management, Post-Secondary Level.

ERIC Educational Resources Information Center

Green (Del) Associates, Foster City, CA.

This document presents in three parts the bases for curriculum decisions in the development of a post-secondary curriculum for minorities in small business ownership and management. Part 1 covers the general curriculum decisions, including the following items: selection of curriculum testing site; academic credits; class scheduling; student…

76 FR 28847 - Adrian & Blissfield Rail Road Company-Continuance in Control-Charlotte Southern Railroad Company...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-05-18

...) requires that the Board take environmental considerations into account in its decision making.\\6\\ Under... schedule for consideration of the application, providing for the Board's final decision to be issued on... decision is May 18, 2011. Any person who wishes to participate in this proceeding as a party of record (POR...

Dynamic Hierarchical Sleep Scheduling for Wireless Ad-Hoc Sensor Networks

PubMed Central

Wen, Chih-Yu; Chen, Ying-Chih

2009-01-01

This paper presents two scheduling management schemes for wireless sensor networks, which manage the sensors by utilizing the hierarchical network structure and allocate network resources efficiently. A local criterion is used to simultaneously establish the sensing coverage and connectivity such that dynamic cluster-based sleep scheduling can be achieved. The proposed schemes are simulated and analyzed to abstract the network behaviors in a number of settings. The experimental results show that the proposed algorithms provide efficient network power control and can achieve high scalability in wireless sensor networks. PMID:22412343

Dynamic hierarchical sleep scheduling for wireless ad-hoc sensor networks.

PubMed

Wen, Chih-Yu; Chen, Ying-Chih

2009-01-01

This paper presents two scheduling management schemes for wireless sensor networks, which manage the sensors by utilizing the hierarchical network structure and allocate network resources efficiently. A local criterion is used to simultaneously establish the sensing coverage and connectivity such that dynamic cluster-based sleep scheduling can be achieved. The proposed schemes are simulated and analyzed to abstract the network behaviors in a number of settings. The experimental results show that the proposed algorithms provide efficient network power control and can achieve high scalability in wireless sensor networks.

The ATLAS Production System Evolution: New Data Processing and Analysis Paradigm for the LHC Run2 and High-Luminosity

NASA Astrophysics Data System (ADS)

Barreiro, F. H.; Borodin, M.; De, K.; Golubkov, D.; Klimentov, A.; Maeno, T.; Mashinistov, R.; Padolski, S.; Wenaus, T.; ATLAS Collaboration

2017-10-01

The second generation of the ATLAS Production System called ProdSys2 is a distributed workload manager that runs daily hundreds of thousands of jobs, from dozens of different ATLAS specific workflows, across more than hundred heterogeneous sites. It achieves high utilization by combining dynamic job definition based on many criteria, such as input and output size, memory requirements and CPU consumption, with manageable scheduling policies and by supporting different kind of computational resources, such as GRID, clouds, supercomputers and volunteer-computers. The system dynamically assigns a group of jobs (task) to a group of geographically distributed computing resources. Dynamic assignment and resources utilization is one of the major features of the system, it didn’t exist in the earliest versions of the production system where Grid resources topology was predefined using national or/and geographical pattern. Production System has a sophisticated job fault-recovery mechanism, which efficiently allows to run multi-Terabyte tasks without human intervention. We have implemented “train” model and open-ended production which allow to submit tasks automatically as soon as new set of data is available and to chain physics groups data processing and analysis with central production by the experiment. We present an overview of the ATLAS Production System and its major components features and architecture: task definition, web user interface and monitoring. We describe the important design decisions and lessons learned from an operational experience during the first year of LHC Run2. We also report the performance of the designed system and how various workflows, such as data (re)processing, Monte-Carlo and physics group production, users analysis, are scheduled and executed within one production system on heterogeneous computing resources.

Enhancing Adoption of Irrigation Scheduling to Sustain the Viability of Fruit and Nut Crops in California

NASA Astrophysics Data System (ADS)

Fulton, A.; Snyder, R.; Hillyer, C.; English, M.; Sanden, B.; Munk, D.

2012-04-01

Enhancing Adoption of Irrigation Scheduling to Sustain the Viability of Fruit and Nut Crops in California Allan Fulton, Richard Snyder, Charles Hillyer, Marshall English, Blake Sanden, and Dan Munk Adoption of scientific methods to decide when to irrigate and how much water to apply to a crop has increased over the last three decades in California. In 1988, less than 4.3 percent of US farmers employed some type of science-based technique to assist in making irrigation scheduling decisions (USDA, 1995). An ongoing survey in California, representing an industry irrigating nearly 0.4 million planted almond hectares, indicates adoption rates ranging from 38 to 55 percent of either crop evapotranspiration (ETc), soil moisture monitoring, plant water status, or some combination of these irrigation scheduling techniques to assist with making irrigation management decisions (California Almond Board, 2011). High capital investment to establish fruit and nut crops, sensitivity to over and under-irrigation on crop performance and longevity, and increasing costs and competition for water have all contributed to increased adoption of scientific irrigation scheduling methods. These trends in adoption are encouraging and more opportunities exist to develop improved irrigation scheduling tools, especially computer decision-making models. In 2009 and 2010, an "On-line Irrigation Scheduling Advisory Service" (OISO, 2012), also referred to as Online Irrigation Management (IMO), was used and evaluated in commercial walnut, almond, and French prune orchards in the northern Sacramento Valley of California. This specific model has many features described as the "Next Generation of Irrigation Schedulers" (Hillyer, 2010). While conventional irrigation management involves simply irrigating as needed to avoid crop stress, this IMO is designed to control crop stress, which requires: (i) precise control of crop water availability (rather than controlling applied water); (ii) quantifying crop stress in order to manage it in heterogeneous fields; and (iii) predicting crop responses to water stress. The capacities of this IMO include: 1. Modeling of the disposition of applied water in spatially variable fields; 2. Conjunctive scheduling for multiple fields, rather than scheduling each field independently; 3. Long range forecasting of crop water requirements to better utilize limited water or limited delivery system capacity: and 4. Explicit modeling of the uncertainties of water use and crop yield. This was one of the first efforts to employ a "Next Generation" type computer irrigation scheduling advisory model or IMO in orchard crops. This paper discusses experiences with introducing this model to fruit and nut growers of various size and scale in the northern Sacramento Valley of California and the accuracy of its forecasts of irrigation needs in fruit and nut crops. Strengths and opportunities to forge ahead in the development of a "Next Generation" irrigation scheduler were identified from this on-farm evaluation.

Dynamics and cultural specifics of information needs under conditions of long-term space flight

NASA Astrophysics Data System (ADS)

Feichtinger, Elena; Shved, Dmitry; Gushin, Vadim

Life in conditions of space flight or chamber study with prolonged isolation is associated with lack of familiar stimuli (sensory deprivation), monotony, significant limitation of communication, and deficit of information and media content (Myasnikov V.I., Stepanova S.I. et al., 2000). Fulfillment of a simulation experiment or flight schedule implies necessity of performance of sophisticated tasks and decision making with limited means of external support. On the other hand, the “stream” of information from the Mission Control (MC) and PI’s (reminders about different procedures to be performed, requests of reports, etc.) is often inadequate to communication needs of crewmembers. According to the theory of “information stress” (Khananashvili M.M., 1984), a distress condition could be formed if: a) it’s necessary to process large amounts of information and make decisions under time pressure; b) there is a prolonged deficit of necessary (e.g. for decision making) information. Thus, we suppose that one of the important goals of psychological support of space or space simulation crews should be forming of favorable conditions of information environment. For that purpose, means of crew-MC information exchange (quantitative characteristics and, if possible, content of radiograms, text and video messages, etc.) should be studied, as well as peculiarities of the crewmembers’ needs in different information and media content, and their reactions to incoming information. In the space simulation experiment with 520-day isolation, communication of international crew with external parties had been studied. Dynamics of quantitative and content characteristics of the crew’s messages was related to the experiment’s stage, presence of “key” events in the schedule (periods of high autonomy, simulated “planetary landing”, etc.), as well as to events not related to the experiment (holidays, news, etc.). It was shown that characteristics of information exchange are related not only to individual traits of the subjects, but to their nationality and cultural background as well. Cultural differences in information and communication needs of Russian and European crewmembers led to necessity of adaptation of psychological support to the specifics of each group. The results of the study suggest that the problem of information, communication and media-related needs should be studied thoroughly, with consequent development of recommendations for psychological support of international crews.

Multi-Satellite Observation Scheduling for Large Area Disaster Emergency Response

NASA Astrophysics Data System (ADS)

Niu, X. N.; Tang, H.; Wu, L. X.

2018-04-01

an optimal imaging plan, plays a key role in coordinating multiple satellites to monitor the disaster area. In the paper, to generate imaging plan dynamically according to the disaster relief, we propose a dynamic satellite task scheduling method for large area disaster response. First, an initial robust scheduling scheme is generated by a robust satellite scheduling model in which both the profit and the robustness of the schedule are simultaneously maximized. Then, we use a multi-objective optimization model to obtain a series of decomposing schemes. Based on the initial imaging plan, we propose a mixed optimizing algorithm named HA_NSGA-II to allocate the decomposing results thus to obtain an adjusted imaging schedule. A real disaster scenario, i.e., 2008 Wenchuan earthquake, is revisited in terms of rapid response using satellite resources and used to evaluate the performance of the proposed method with state-of-the-art approaches. We conclude that our satellite scheduling model can optimize the usage of satellite resources so as to obtain images in disaster response in a more timely and efficient manner.

Exploring a QoS Driven Scheduling Approach for Peer-to-Peer Live Streaming Systems with Network Coding

PubMed Central

Cui, Laizhong; Lu, Nan; Chen, Fu

2014-01-01

Most large-scale peer-to-peer (P2P) live streaming systems use mesh to organize peers and leverage pull scheduling to transmit packets for providing robustness in dynamic environment. The pull scheduling brings large packet delay. Network coding makes the push scheduling feasible in mesh P2P live streaming and improves the efficiency. However, it may also introduce some extra delays and coding computational overhead. To improve the packet delay, streaming quality, and coding overhead, in this paper are as follows. we propose a QoS driven push scheduling approach. The main contributions of this paper are: (i) We introduce a new network coding method to increase the content diversity and reduce the complexity of scheduling; (ii) we formulate the push scheduling as an optimization problem and transform it to a min-cost flow problem for solving it in polynomial time; (iii) we propose a push scheduling algorithm to reduce the coding overhead and do extensive experiments to validate the effectiveness of our approach. Compared with previous approaches, the simulation results demonstrate that packet delay, continuity index, and coding ratio of our system can be significantly improved, especially in dynamic environments. PMID:25114968

Environmental damage schedules: community judgments of importance and assessments of losses

Treesearch

Ratana Chuenpagdee; Jack L. Knetsch; Thomas C. Brown

2001-01-01

Available methods of valuing environmental changes are often limited in their applicability to current issues such as damage assessment and implementing regulatory controls, or may otherwise not provide reliable readings of community preferences. An alternative is to base decisions on predetermined fixed schedules of sanctions, restrictions, damage awards, and other...

Improving Hospital-wide Patient Scheduling Decisions by Clinical Pathway Mining.

PubMed

Gartner, Daniel; Arnolds, Ines V; Nickel, Stefan

2015-01-01

Recent research has highlighted the need for solving hospital-wide patient scheduling problems. Inpatient scheduling, patient activities have to be scheduled on scarce hospital resources such that temporal relations between activities (e.g. for recovery times) are ensured. Common objectives are, among others, the minimization of the length of stay (LOS). In this paper, we consider a hospital-wide patient scheduling problem with LOS minimization based on uncertain clinical pathways. We approach the problem in three stages: First, we learn most likely clinical pathways using a sequential pattern mining approach. Second, we provide a mathematical model for patient scheduling and finally, we combine the two approaches. In an experimental study carried out using real-world data, we show that our approach outperforms baseline approaches on two metrics.

Planning for deficit irrigation

USDA-ARS?s Scientific Manuscript database

Irrigators with limited water supplies that lead to deficit irrigation management need to make decisions about crop selection, water allocations to each crop, and irrigation schedules. Many of these decisions need to occur before the crop is planted and depend on yield-evapotranspiration (ET) and yi...

Secure Scientific Applications Scheduling Technique for Cloud Computing Environment Using Global League Championship Algorithm

PubMed Central

Abdulhamid, Shafi’i Muhammad; Abd Latiff, Muhammad Shafie; Abdul-Salaam, Gaddafi; Hussain Madni, Syed Hamid

2016-01-01

Cloud computing system is a huge cluster of interconnected servers residing in a datacenter and dynamically provisioned to clients on-demand via a front-end interface. Scientific applications scheduling in the cloud computing environment is identified as NP-hard problem due to the dynamic nature of heterogeneous resources. Recently, a number of metaheuristics optimization schemes have been applied to address the challenges of applications scheduling in the cloud system, without much emphasis on the issue of secure global scheduling. In this paper, scientific applications scheduling techniques using the Global League Championship Algorithm (GBLCA) optimization technique is first presented for global task scheduling in the cloud environment. The experiment is carried out using CloudSim simulator. The experimental results show that, the proposed GBLCA technique produced remarkable performance improvement rate on the makespan that ranges between 14.44% to 46.41%. It also shows significant reduction in the time taken to securely schedule applications as parametrically measured in terms of the response time. In view of the experimental results, the proposed technique provides better-quality scheduling solution that is suitable for scientific applications task execution in the Cloud Computing environment than the MinMin, MaxMin, Genetic Algorithm (GA) and Ant Colony Optimization (ACO) scheduling techniques. PMID:27384239

Secure Scientific Applications Scheduling Technique for Cloud Computing Environment Using Global League Championship Algorithm.

PubMed

Abdulhamid, Shafi'i Muhammad; Abd Latiff, Muhammad Shafie; Abdul-Salaam, Gaddafi; Hussain Madni, Syed Hamid

2016-01-01

Cloud computing system is a huge cluster of interconnected servers residing in a datacenter and dynamically provisioned to clients on-demand via a front-end interface. Scientific applications scheduling in the cloud computing environment is identified as NP-hard problem due to the dynamic nature of heterogeneous resources. Recently, a number of metaheuristics optimization schemes have been applied to address the challenges of applications scheduling in the cloud system, without much emphasis on the issue of secure global scheduling. In this paper, scientific applications scheduling techniques using the Global League Championship Algorithm (GBLCA) optimization technique is first presented for global task scheduling in the cloud environment. The experiment is carried out using CloudSim simulator. The experimental results show that, the proposed GBLCA technique produced remarkable performance improvement rate on the makespan that ranges between 14.44% to 46.41%. It also shows significant reduction in the time taken to securely schedule applications as parametrically measured in terms of the response time. In view of the experimental results, the proposed technique provides better-quality scheduling solution that is suitable for scientific applications task execution in the Cloud Computing environment than the MinMin, MaxMin, Genetic Algorithm (GA) and Ant Colony Optimization (ACO) scheduling techniques.

On program restructuring, scheduling, and communication for parallel processor systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Polychronopoulos, Constantine D.

1986-08-01

This dissertation discusses several software and hardware aspects of program execution on large-scale, high-performance parallel processor systems. The issues covered are program restructuring, partitioning, scheduling and interprocessor communication, synchronization, and hardware design issues of specialized units. All this work was performed focusing on a single goal: to maximize program speedup, or equivalently, to minimize parallel execution time. Parafrase, a Fortran restructuring compiler was used to transform programs in a parallel form and conduct experiments. Two new program restructuring techniques are presented, loop coalescing and subscript blocking. Compile-time and run-time scheduling schemes are covered extensively. Depending on the program construct, thesemore » algorithms generate optimal or near-optimal schedules. For the case of arbitrarily nested hybrid loops, two optimal scheduling algorithms for dynamic and static scheduling are presented. Simulation results are given for a new dynamic scheduling algorithm. The performance of this algorithm is compared to that of self-scheduling. Techniques for program partitioning and minimization of interprocessor communication for idealized program models and for real Fortran programs are also discussed. The close relationship between scheduling, interprocessor communication, and synchronization becomes apparent at several points in this work. Finally, the impact of various types of overhead on program speedup and experimental results are presented.« less

Filling the Holes: Work Schedulers as Job Crafters of Employment Practice in Long-Term Health Care

PubMed Central

Kossek, Ellen Ernst; Piszczek, Matthew M.; Mcalpine, Kristie L.; Hammer, Leslie B.; Burke, Lisa

2016-01-01

Although work schedulers serve an organizational role influencing decisions about balancing conflicting stakeholder interests over schedules and staffing, scheduling has primarily been described as an objective activity or individual job characteristic. The authors use the lens of job crafting to examine how schedulers in 26 health care facilities enact their roles as they “fill holes” to schedule workers. Qualitative analysis of interview data suggests that schedulers expand their formal scope and influence to meet their interpretations of how to manage stakeholders (employers, workers, and patients). The authors analyze variations in the extent of job crafting (cognitive, physical, relational) to broaden role repertoires. They find evidence that some schedulers engage in rule-bound interpretation to avoid role expansion. They also identify four types of schedulers: enforcers, patient-focused schedulers, employee-focused schedulers, and balancers. The article adds to the job-crafting literature by showing that job crafting is conducted not only to create meaningful work but also to manage conflicting demands and to mediate among the competing labor interests of workers, clients, and employers. PMID:27721517

Nonpreemptive run-time scheduling issues on a multitasked, multiprogrammed multiprocessor with dependencies, bidimensional tasks, folding and dynamic graphs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Miller, Allan Ray

1987-05-01

Increases in high speed hardware have mandated studies in software techniques to exploit the parallel capabilities. This thesis examines the effects a run-time scheduler has on a multiprocessor. The model consists of directed, acyclic graphs, generated from serial FORTRAN benchmark programs by the parallel compiler Parafrase. A multitasked, multiprogrammed environment is created. Dependencies are generated by the compiler. Tasks are bidimensional, i.e., they may specify both time and processor requests. Processor requests may be folded into execution time by the scheduler. The graphs may arrive at arbitrary time intervals. The general case is NP-hard, thus, a variety of heuristics aremore » examined by a simulator. Multiprogramming demonstrates a greater need for a run-time scheduler than does monoprogramming for a variety of reasons, e.g., greater stress on the processors, a larger number of independent control paths, more variety in the task parameters, etc. The dynamic critical path series of algorithms perform well. Dynamic critical volume did not add much. Unfortunately, dynamic critical path maximizes turnaround time as well as throughput. Two schedulers are presented which balance throughput and turnaround time. The first requires classification of jobs by type; the second requires selection of a ratio value which is dependent upon system parameters. 45 refs., 19 figs., 20 tabs.« less

Proposal for the completion of outstanding work on the installation scheduling and alignment of the SDC central calorimeter

DOE Office of Scientific and Technical Information (OSTI.GOV)

Guarino, V.; Hill, N.; Nasiatka, J.

The High Energy Physic Division at Argonne National Laboratory was given the task of developing the procedures, fixtures, and schedules for the final assembly of the barrel and endcap calorimeters for the SDC. The work completed led to some major decision about how and where this assembly work would be done. The primary assembly decision was the feasibility of assembling the major detector components (barrel and endcap sub-assemblies) above ground and lowering them into position in the experimental hall, as opposed to assembling the calorimeter directly in the experimental hall. Due to cost of above ground assembly and schedule changes,more » the in-hall option was adopted. Although no actual hardware was constructed, many conceptual ideas were formalized and brought to workable solutions as a result of the effort put forth at ANL.« less

Stratospheric Aerosol and Gas Experiment, SAGE III on ISS, An Earth Science Mission on the International Space Station, Schedule Risk Analysis, A Project Perspective

NASA Technical Reports Server (NTRS)

Bonine, Lauren

2015-01-01

The presentation provides insight into the schedule risk analysis process used by the Stratospheric Aerosol and Gas Experiment III on the International Space Station Project. The presentation focuses on the schedule risk analysis process highlighting the methods for identification of risk inputs, the inclusion of generic risks identified outside the traditional continuous risk management process, and the development of tailored analysis products used to improve risk informed decision making.

Departure Queue Prediction for Strategic and Tactical Surface Scheduler Integration

NASA Technical Reports Server (NTRS)

Zelinski, Shannon; Windhorst, Robert

2016-01-01

A departure metering concept to be demonstrated at Charlotte Douglas International Airport (CLT) will integrate strategic and tactical surface scheduling components to enable the respective collaborative decision making and improved efficiency benefits these two methods of scheduling provide. This study analyzes the effect of tactical scheduling on strategic scheduler predictability. Strategic queue predictions and target gate pushback times to achieve a desired queue length are compared between fast time simulations of CLT surface operations with and without tactical scheduling. The use of variable departure rates as a strategic scheduler input was shown to substantially improve queue predictions over static departure rates. With target queue length calibration, the strategic scheduler can be tuned to produce average delays within one minute of the tactical scheduler. However, root mean square differences between strategic and tactical delays were between 12 and 15 minutes due to the different methods the strategic and tactical schedulers use to predict takeoff times and generate gate pushback clearances. This demonstrates how difficult it is for the strategic scheduler to predict tactical scheduler assigned gate delays on an individual flight basis as the tactical scheduler adjusts departure sequence to accommodate arrival interactions. Strategic/tactical scheduler compatibility may be improved by providing more arrival information to the strategic scheduler and stabilizing tactical scheduler changes to runway sequence in response to arrivals.

Dynamic Appliances Scheduling in Collaborative MicroGrids System

PubMed Central

Bilil, Hasnae; Aniba, Ghassane; Gharavi, Hamid

2017-01-01

In this paper a new approach which is based on a collaborative system of MicroGrids (MG’s), is proposed to enable household appliance scheduling. To achieve this, appliances are categorized into flexible and non-flexible Deferrable Loads (DL’s), according to their electrical components. We propose a dynamic scheduling algorithm where users can systematically manage the operation of their electric appliances. The main challenge is to develop a flattening function calculus (reshaping) for both flexible and non-flexible DL’s. In addition, implementation of the proposed algorithm would require dynamically analyzing two successive multi-objective optimization (MOO) problems. The first targets the activation schedule of non-flexible DL’s and the second deals with the power profiles of flexible DL’s. The MOO problems are resolved by using a fast and elitist multi-objective genetic algorithm (NSGA-II). Finally, in order to show the efficiency of the proposed approach, a case study of a collaborative system that consists of 40 MG’s registered in the load curve for the flattening program has been developed. The results verify that the load curve can indeed become very flat by applying the proposed scheduling approach. PMID:28824226

Chemotherapy and treatment scheduling: the Johns Hopkins Oncology Center Outpatient Department.

PubMed Central

Majidi, F.; Enterline, J. P.; Ashley, B.; Fowler, M. E.; Ogorzalek, L. L.; Gaudette, R.; Stuart, G. J.; Fulton, M.; Ettinger, D. S.

1993-01-01

The Chemotherapy and Treatment Scheduling System provides integrated appointment and facility scheduling for very complex procedures. It is fully integrated with other scheduling systems at The Johns Hopkins Oncology Center and is supported by the Oncology Clinical Information System (OCIS). It provides a combined visual and textual environment for the scheduling of events that have multiple dimensions and dependencies on other scheduled events. It is also fully integrated with other clinical decision support and ancillary systems within OCIS. The system has resulted in better patient flow through the ambulatory care areas of the Center. Implementing the system required changes in behavior among physicians, staff, and patients. This system provides a working example of building a sophisticated rule-based scheduling system using a relatively simple paradigm. It also is an example of what can be achieved when there is total integration between the operational and clinical components of patient care automation. PMID:8130453

Job Scheduling Under the Portable Batch System

NASA Technical Reports Server (NTRS)

Henderson, Robert L.; Woodrow, Thomas S. (Technical Monitor)

1995-01-01

The typical batch queuing system schedules jobs for execution by a set of queue controls. The controls determine from which queues jobs may be selected. Within the queue, jobs are ordered first-in, first-run. This limits the set of scheduling policies available to a site. The Portable Batch System removes this limitation by providing an external scheduling module. This separate program has full knowledge of the available queued jobs, running jobs, and system resource usage. Sites are able to implement any policy expressible in one of several procedural language. Policies may range from "bet fit" to "fair share" to purely political. Scheduling decisions can be made over the full set of jobs regardless of queue or order. The scheduling policy can be changed to fit a wide variety of computing environments and scheduling goals. This is demonstrated by the use of PBS on an IBM SP-2 system at NASA Ames.

Wave scheduling - Decentralized scheduling of task forces in multicomputers

NASA Technical Reports Server (NTRS)

Van Tilborg, A. M.; Wittie, L. D.

1984-01-01

Decentralized operating systems that control large multicomputers need techniques to schedule competing parallel programs called task forces. Wave scheduling is a probabilistic technique that uses a hierarchical distributed virtual machine to schedule task forces by recursively subdividing and issuing wavefront-like commands to processing elements capable of executing individual tasks. Wave scheduling is highly resistant to processing element failures because it uses many distributed schedulers that dynamically assign scheduling responsibilities among themselves. The scheduling technique is trivially extensible as more processing elements join the host multicomputer. A simple model of scheduling cost is used by every scheduler node to distribute scheduling activity and minimize wasted processing capacity by using perceived workload to vary decentralized scheduling rules. At low to moderate levels of network activity, wave scheduling is only slightly less efficient than a central scheduler in its ability to direct processing elements to accomplish useful work.

Minimizing the regrets of long-term urban floodplain management decisions under deeply uncertain climate change

NASA Astrophysics Data System (ADS)

Hecht, J. S.; Kirshen, P. H.; Vogel, R. M.

2016-12-01

Making long-term floodplain management decisions under uncertain climate change is a major urban planning challenge of the 21stcentury. To support these efforts, we introduce a screening-level optimization model that identifies adaptation portfolios by minimizing the regrets associated with their flood-control and damage costs under different climate change trajectories that are deeply uncertain, i.e. have probabilities that cannot be specified plausibly. This mixed integer program explicitly considers the coupled damage-reduction impacts of different floodwall designs and property-scale investments (first-floor elevation, wet floodproofing of basements, permanent retreat and insurance), recommends implementation schedules, and assesses impacts to stakeholders residing in three types of homes. An application to a stylized municipality illuminates many nonlinear system dynamics stemming from large fixed capital costs, infrastructure design thresholds, and discharge-depth-damage relationships. If stakeholders tolerate mild damage, floodwalls that fully protect a community from large design events are less cost-effective than portfolios featuring both smaller floodwalls and property-scale measures. Potential losses of property tax revenue from permanent retreat motivate municipal property-tax initiatives for adaptation financing. Yet, insurance incentives for first-floor elevation may discourage locally financed floodwalls, in turn making lower-income residents more vulnerable to severe flooding. A budget constraint analysis underscores the benefits of flexible floodwall designs with low incremental expansion costs while near-optimal solutions demonstrate the scheduling flexibility of many property-scale measures. Finally, an equity analysis shows the importance of evaluating the overpayment and under-design regrets of recommended adaptation portfolios for each stakeholder and contrasts them to single-scenario model results.

Optimization of a pH-shift control strategy for producing monoclonal antibodies in Chinese hamster ovary cell cultures using a pH-dependent dynamic model.

PubMed

Hogiri, Tomoharu; Tamashima, Hiroshi; Nishizawa, Akitoshi; Okamoto, Masahiro

2018-02-01

To optimize monoclonal antibody (mAb) production in Chinese hamster ovary cell cultures, culture pH should be temporally controlled with high resolution. In this study, we propose a new pH-dependent dynamic model represented by simultaneous differential equations including a minimum of six system component, depending on pH value. All kinetic parameters in the dynamic model were estimated using an evolutionary numerical optimization (real-coded genetic algorithm) method based on experimental time-course data obtained at different pH values ranging from 6.6 to 7.2. We determined an optimal pH-shift schedule theoretically. We validated this optimal pH-shift schedule experimentally and mAb production increased by approximately 40% with this schedule. Throughout this study, it was suggested that the culture pH-shift optimization strategy using a pH-dependent dynamic model is suitable to optimize any pH-shift schedule for CHO cell lines used in mAb production projects. Copyright © 2017 The Society for Biotechnology, Japan. Published by Elsevier B.V. All rights reserved.

5 CFR 511.703 - Retroactive effective date.

Code of Federal Regulations, 2011 CFR

2011-01-01

... CLASSIFICATION UNDER THE GENERAL SCHEDULE Effective Dates of Position Classification Actions or Decisions § 511... if the employee is wrongfully demoted. (b) Downgrading. (1) The effective date of a classification appellate certificate or agency appellate decision can be retroactive only if it corrects a classification...

16 CFR 1203.13 - Test schedule.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 16 Commercial Practices 2 2012-01-01 2012-01-01 false Test schedule. 1203.13 Section 1203.13... STANDARD FOR BICYCLE HELMETS The Standard § 1203.13 Test schedule. (a) Helmet sample 1 of the set of eight... environments, respectively) shall be tested in accordance with the dynamic retention system strength test at...

Continual planning and scheduling for managing patient tests in hospital laboratories.

PubMed

Marinagi, C C; Spyropoulos, C D; Papatheodorou, C; Kokkotos, S

2000-10-01

Hospital laboratories perform examination tests upon patients, in order to assist medical diagnosis or therapy progress. Planning and scheduling patient requests for examination tests is a complicated problem because it concerns both minimization of patient stay in hospital and maximization of laboratory resources utilization. In the present paper, we propose an integrated patient-wise planning and scheduling system which supports the dynamic and continual nature of the problem. The proposed combination of multiagent and blackboard architecture allows the dynamic creation of agents that share a set of knowledge sources and a knowledge base to service patient test requests.

Utilizing AI in Temporal, Spatial, and Resource Scheduling

NASA Technical Reports Server (NTRS)

Stottler, Richard; Kalton, Annaka; Bell, Aaron

2006-01-01

Aurora is a software system enabling the rapid, easy solution of complex scheduling problems involving spatial and temporal constraints among operations and scarce resources (such as equipment, workspace, and human experts). Although developed for use in the International Space Station Processing Facility, Aurora is flexible enough that it can be easily customized for application to other scheduling domains and adapted as the requirements change or become more precisely known over time. Aurora s scheduling module utilizes artificial-intelligence (AI) techniques to make scheduling decisions on the basis of domain knowledge, including knowledge of constraints and their relative importance, interdependencies among operations, and possibly frequent changes in governing schedule requirements. Unlike many other scheduling software systems, Aurora focuses on resource requirements and temporal scheduling in combination. For example, Aurora can accommodate a domain requirement to schedule two subsequent operations to locations adjacent to a shared resource. The graphical interface allows the user to quickly visualize the schedule and perform changes reflecting additional knowledge or alterations in the situation. For example, the user might drag the activity corresponding to the start of operations to reflect a late delivery.

Plant operation planning and scheduling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jammar, R.J.

When properly designed, planning and scheduling can actually add millions of dollars per year to the bottom line. Planning and scheduling is a continuum of decisions starting with crude selection and ending with establishing short-term targets for crude processing and blending. It also includes maintaining optimization and operation simulation models. It is thought that conservatively, a refinery may save from $5 million to $10 million a year if it pays more attention to the processes behind proper planning and scheduling. Of course, the amount of savings can reach staggering proportions for companies now at the bottom of the Solomon Associatesmore » Inc. refinery performance ranking.« less

How To Select an Event Management System: A Guide to Selecting the Most Effective Resource Management System for College Union and Student Activities Professionals.

ERIC Educational Resources Information Center

Anderson, Scott; Raasch, Kevin

2002-01-01

Provides an evaluation template for student activities professionals charged with evaluating competitive event scheduling software. Guides staff in making an informed decision on whether to retain event management technology provided through an existing vendor or choose "best-of-breed" scheduling software. (EV)

Validity and Diagnostic Accuracy of Scores from the Autism Diagnostic Observation Schedule-Generic

ERIC Educational Resources Information Center

Reid, Melissa A.

2012-01-01

The purpose of this study was to examine the internal structure, relationships with other variables, and diagnostic accuracy of scores on the Autism Diagnostic Observation Schedule-Generic (ADOS-G; Lord et al., 1999) for the purpose of diagnostic decision-making. Participants were 462 children enrolled in a public school district in the southern…

Job Scheduling with Efficient Resource Monitoring in Cloud Datacenter

PubMed Central

Loganathan, Shyamala; Mukherjee, Saswati

2015-01-01

Cloud computing is an on-demand computing model, which uses virtualization technology to provide cloud resources to users in the form of virtual machines through internet. Being an adaptable technology, cloud computing is an excellent alternative for organizations for forming their own private cloud. Since the resources are limited in these private clouds maximizing the utilization of resources and giving the guaranteed service for the user are the ultimate goal. For that, efficient scheduling is needed. This research reports on an efficient data structure for resource management and resource scheduling technique in a private cloud environment and discusses a cloud model. The proposed scheduling algorithm considers the types of jobs and the resource availability in its scheduling decision. Finally, we conducted simulations using CloudSim and compared our algorithm with other existing methods, like V-MCT and priority scheduling algorithms. PMID:26473166

Job Scheduling with Efficient Resource Monitoring in Cloud Datacenter.

PubMed

Loganathan, Shyamala; Mukherjee, Saswati

2015-01-01

Cloud computing is an on-demand computing model, which uses virtualization technology to provide cloud resources to users in the form of virtual machines through internet. Being an adaptable technology, cloud computing is an excellent alternative for organizations for forming their own private cloud. Since the resources are limited in these private clouds maximizing the utilization of resources and giving the guaranteed service for the user are the ultimate goal. For that, efficient scheduling is needed. This research reports on an efficient data structure for resource management and resource scheduling technique in a private cloud environment and discusses a cloud model. The proposed scheduling algorithm considers the types of jobs and the resource availability in its scheduling decision. Finally, we conducted simulations using CloudSim and compared our algorithm with other existing methods, like V-MCT and priority scheduling algorithms.

Memory and Processing Limits in Decision-Making.

ERIC Educational Resources Information Center

Klapp, Stuart T.

According to the classical working memory perspective, tasks such as command and control decision-making should be performed less effectively if extraneous material must be retained in short-term memory. Only marginal support for this prediction was obtained for a simulation involving scheduling trucking and transportation missions, although…

General Methodology Combining Engineering Optimization of Primary HVAC and R Plants with Decision Analysis Methods--Part II: Uncertainty and Decision Analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jiang, Wei; Reddy, T. A.; Gurian, Patrick

2007-01-31

A companion paper to Jiang and Reddy that presents a general and computationally efficient methodology for dyanmic scheduling and optimal control of complex primary HVAC&R plants using a deterministic engineering optimization approach.

Time Management

ERIC Educational Resources Information Center

Stoilov, Todor, Ed.

2012-01-01

The time management is worthy goal of many human activities. It concerns variety problems related to goals definition, assessment of available resources, control of management policies, scheduling of decisions. This book is an attempt to illustrate the decision making process in time management for different success stories, which can be used as…

Integration of scheduling and discrete event simulation systems to improve production flow planning

NASA Astrophysics Data System (ADS)

Krenczyk, D.; Paprocka, I.; Kempa, W. M.; Grabowik, C.; Kalinowski, K.

2016-08-01

The increased availability of data and computer-aided technologies such as MRPI/II, ERP and MES system, allowing producers to be more adaptive to market dynamics and to improve production scheduling. Integration of production scheduling and computer modelling, simulation and visualization systems can be useful in the analysis of production system constraints related to the efficiency of manufacturing systems. A integration methodology based on semi-automatic model generation method for eliminating problems associated with complexity of the model and labour-intensive and time-consuming process of simulation model creation is proposed. Data mapping and data transformation techniques for the proposed method have been applied. This approach has been illustrated through examples of practical implementation of the proposed method using KbRS scheduling system and Enterprise Dynamics simulation system.

Dynamic Energy Management System for a Smart Microgrid.

PubMed

Venayagamoorthy, Ganesh Kumar; Sharma, Ratnesh K; Gautam, Prajwal K; Ahmadi, Afshin

2016-08-01

This paper presents the development of an intelligent dynamic energy management system (I-DEMS) for a smart microgrid. An evolutionary adaptive dynamic programming and reinforcement learning framework is introduced for evolving the I-DEMS online. The I-DEMS is an optimal or near-optimal DEMS capable of performing grid-connected and islanded microgrid operations. The primary sources of energy are sustainable, green, and environmentally friendly renewable energy systems (RESs), e.g., wind and solar; however, these forms of energy are uncertain and nondispatchable. Backup battery energy storage and thermal generation were used to overcome these challenges. Using the I-DEMS to schedule dispatches allowed the RESs and energy storage devices to be utilized to their maximum in order to supply the critical load at all times. Based on the microgrid's system states, the I-DEMS generates energy dispatch control signals, while a forward-looking network evaluates the dispatched control signals over time. Typical results are presented for varying generation and load profiles, and the performance of I-DEMS is compared with that of a decision tree approach-based DEMS (D-DEMS). The robust performance of the I-DEMS was illustrated by examining microgrid operations under different battery energy storage conditions.

A Conceptual Framework for Defense Acquisition Decision Makers: Giving the Schedule its Due

DTIC Science & Technology

2014-01-01

Principles from microeconomic theory and operations research can provide insight into acquisition decisions to produce military capabili- ties in an...models based on economic and operations research principles can yield valuable insight into defense acquisition decisions. This article focuses on models...Department Edmund Conrow (1995) developed an excellent microeconomic framework to investigate the incentives of buyers and sellers in the defense

Interface Evaluation for Open System Architectures

DTIC Science & Technology

2014-03-01

maker (SDM) is responsible for balancing all of the influences of the IPT when making decisions. Coalescing the IPT perspectives for a single IIM...factors are considered in IIM decisions and that decisions are consistent with the preferences of the SDM, ultimately leading to a balance of schedule... board to perform ranking and weighting determinations. Rank sum, rank exponent, rank reciprocal and ROC leverage a subjective assessment of the

An Experimental Test of a Model for Decision Strategy Selection

DTIC Science & Technology

1977-12-01

University of Washington, Seattle, WA 98195 1l. CONTROLLING OFFICE NAME AND ADDRESS 12. REPORT DATE Organizational Effectiveness Research Programg... Controlling Office) IS. SECURITY CLASS, (of this report) UNCLASSI FIED 15. DECLASSIFICATION/DOWNGRADING SCHEDULE 16. DISTRIBUTION STATEMENT (of this Report... Equivalence Interval Decision Maker Cost Curve Strategy Cost Expected Net Utility Effect of the Value of the Perceived Strategy Da ision Strategies Decision on

A Model and Algorithms For a Software Evolution Control System

DTIC Science & Technology

1993-12-01

dynamic scheduling approaches can be found in [67). Task scheduling can also be characterized as preemptive and nonpreemptive . A task is preemptive ...is NP-hard for both the preemptive and nonpreemptive cases [671 [84). Scheduling nonpreemptive tasks with arbitrary ready times is NP-hard in both...the preemptive and nonpreemptive cases [671 [841. Scheduling nonpreemptive tasks with arbitrary ready times is NP-hard in both multiprocessor and

An FMS Dynamic Production Scheduling Algorithm Considering Cutting Tool Failure and Cutting Tool Life

NASA Astrophysics Data System (ADS)

Setiawan, A.; Wangsaputra, R.; Martawirya, Y. Y.; Halim, A. H.

2016-02-01

This paper deals with Flexible Manufacturing System (FMS) production rescheduling due to unavailability of cutting tools caused either of cutting tool failure or life time limit. The FMS consists of parallel identical machines integrated with an automatic material handling system and it runs fully automatically. Each machine has a same cutting tool configuration that consists of different geometrical cutting tool types on each tool magazine. The job usually takes two stages. Each stage has sequential operations allocated to machines considering the cutting tool life. In the real situation, the cutting tool can fail before the cutting tool life is reached. The objective in this paper is to develop a dynamic scheduling algorithm when a cutting tool is broken during unmanned and a rescheduling needed. The algorithm consists of four steps. The first step is generating initial schedule, the second step is determination the cutting tool failure time, the third step is determination of system status at cutting tool failure time and the fourth step is the rescheduling for unfinished jobs. The approaches to solve the problem are complete-reactive scheduling and robust-proactive scheduling. The new schedules result differences starting time and completion time of each operations from the initial schedule.

Dynamic Network Selection for Multicast Services in Wireless Cooperative Networks

NASA Astrophysics Data System (ADS)

Chen, Liang; Jin, Le; He, Feng; Cheng, Hanwen; Wu, Lenan

In next generation mobile multimedia communications, different wireless access networks are expected to cooperate. However, it is a challenging task to choose an optimal transmission path in this scenario. This paper focuses on the problem of selecting the optimal access network for multicast services in the cooperative mobile and broadcasting networks. An algorithm is proposed, which considers multiple decision factors and multiple optimization objectives. An analytic hierarchy process (AHP) method is applied to schedule the service queue and an artificial neural network (ANN) is used to improve the flexibility of the algorithm. Simulation results show that by applying the AHP method, a group of weight ratios can be obtained to improve the performance of multiple objectives. And ANN method is effective to adaptively adjust weight ratios when users' new waiting threshold is generated.

SRM Internal Flow Tests and Computational Fluid Dynamic Analysis. Volume 4; Cold Flow Analyses and CFD Analysis Capability Development

NASA Technical Reports Server (NTRS)

1995-01-01

An evaluation of the effect of model inlet air temperature drift during a test run was performed to aid in the decision on the need for and/or the schedule for including heaters in the SRMAFTE. The Sverdrup acceptance test data was used to determine the drift in air temperature during runs over the entire range of delivered flow rates and pressures. The effect of this temperature drift on the model Reynolds number was also calculated. It was concluded from this study that a 2% change in absolute temperature during a test run could be adequately accounted for by the data analysis program. A handout package of these results was prepared and presented to ED35 management.

Electrical utilities model for determining electrical distribution capacity

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fritz, R. L.

1997-09-03

In its simplest form, this model was to obtain meaningful data on the current state of the Site`s electrical transmission and distribution assets, and turn this vast collection of data into useful information. The resulting product is an Electrical Utilities Model for Determining Electrical Distribution Capacity which provides: current state of the electrical transmission and distribution systems; critical Hanford Site needs based on outyear planning documents; decision factor model. This model will enable Electrical Utilities management to improve forecasting requirements for service levels, budget, schedule, scope, and staffing, and recommend the best path forward to satisfy customer demands at themore » minimum risk and least cost to the government. A dynamic document, the model will be updated annually to reflect changes in Hanford Site activities.« less

Using Iterative Repair to Increase the Responsiveness of Planning and Scheduling for Autonomous Spacecraft

NASA Technical Reports Server (NTRS)

Chien, Steve; Knight, Russell; Stechert, Andre; Sherwood, Rob; Rabideau, Gregg

1998-01-01

An autonomous spacecraft must balance long-term and short-term considerations. It must perform purposeful activities that ensure long-term science and engineering goals are achieved and ensure that it maintains positive resource margins. This requires planning in advance to avoid a series of shortsighted decisions that can lead to failure, However, it must also respond in a timely fashion to a somewhat dynamic and unpredictable environment. Thus, spacecraft plans must often be modified due to fortuitous events such as early completion of observations and setbacks such as failure to acquire a guidestar for a science observation. This paper describes the use of iterative repair to support continuous modification and updating of a current working plan in light of changing operating context.

Drug scheduling of cancer chemotherapy based on natural actor-critic approach.

PubMed

Ahn, Inkyung; Park, Jooyoung

2011-11-01

Recently, reinforcement learning methods have drawn significant interests in the area of artificial intelligence, and have been successfully applied to various decision-making problems. In this paper, we study the applicability of the NAC (natural actor-critic) approach, a state-of-the-art reinforcement learning method, to the drug scheduling of cancer chemotherapy for an ODE (ordinary differential equation)-based tumor growth model. ODE-based cancer dynamics modeling is an active research area, and many different mathematical models have been proposed. Among these, we use the model proposed by de Pillis and Radunskaya (2003), which considers the growth of tumor cells and their interaction with normal cells and immune cells. The NAC approach is applied to this ODE model with the goal of minimizing the tumor cell population and the drug amount while maintaining the adequate population levels of normal cells and immune cells. In the framework of the NAC approach, the drug dose is regarded as the control input, and the reward signal is defined as a function of the control input and the cell populations of tumor cells, normal cells, and immune cells. According to the control policy found by the NAC approach, effective drug scheduling in cancer chemotherapy for the considered scenarios has turned out to be close to the strategy of continuing drug injection from the beginning until an appropriate time. Also, simulation results showed that the NAC approach can yield better performance than conventional pulsed chemotherapy. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

The evaluation of the OSGLR algorithm for restructurable controls

NASA Technical Reports Server (NTRS)

Bonnice, W. F.; Wagner, E.; Hall, S. R.; Motyka, P.

1986-01-01

The detection and isolation of commercial aircraft control surface and actuator failures using the orthogonal series generalized likelihood ratio (OSGLR) test was evaluated. The OSGLR algorithm was chosen as the most promising algorithm based on a preliminary evaluation of three failure detection and isolation (FDI) algorithms (the detection filter, the generalized likelihood ratio test, and the OSGLR test) and a survey of the literature. One difficulty of analytic FDI techniques and the OSGLR algorithm in particular is their sensitivity to modeling errors. Therefore, methods of improving the robustness of the algorithm were examined with the incorporation of age-weighting into the algorithm being the most effective approach, significantly reducing the sensitivity of the algorithm to modeling errors. The steady-state implementation of the algorithm based on a single cruise linear model was evaluated using a nonlinear simulation of a C-130 aircraft. A number of off-nominal no-failure flight conditions including maneuvers, nonzero flap deflections, different turbulence levels and steady winds were tested. Based on the no-failure decision functions produced by off-nominal flight conditions, the failure detection performance at the nominal flight condition was determined. The extension of the algorithm to a wider flight envelope by scheduling the linear models used by the algorithm on dynamic pressure and flap deflection was also considered. Since simply scheduling the linear models over the entire flight envelope is unlikely to be adequate, scheduling of the steady-state implentation of the algorithm was briefly investigated.

A hierarchical scheduling and management solution for dynamic reconfiguration in FPGA-based embedded systems

NASA Astrophysics Data System (ADS)

Cervero, T.; Gómez, A.; López, S.; Sarmiento, R.; Dondo, J.; Rincón, F.; López, J. C.

2013-05-01

One of the limiting factors that have prevented a widely dissemination of the reconfigurable technology is the absence of an appropriate model for certain target applications capable of offering a reliable control. Moreover, the lack of flexible and easy-to-use scheduling and management systems are also relevant drawbacks to be considered. Under static scenarios, it is relatively easy to schedule and manage the reconfiguration process since all the variations corresponding to predetermined and well-known tasks. However, the difficulty increases when the adaptation needs of the overall system change semi-randomly according to the environmental fluctuations. In this context, this work proposes a change in the paradigm of dynamically reconfigurable systems, by attending to the dynamically reconfigurable control problematic as a whole, in which the scheduling and the placement issues are packed together as a hierarchical management structure, interacting together as one entity from the system point of view, but performing their tasks with certain degree of independence each other. In this sense, the top hierarchical level corresponds with a dynamic scheduler in charge of planning and adjusting all the reconfigurable modules according to the variations of the external stimulus. The lower level interacts with the physical layer of the device by means of instantiating, relocating, removing a reconfigurable module following the scheduler's instructions. In regards to how fast is the proposed solution, the total partial reconfiguration time achieved with this proposal has been measured and compared with other two approaches: 1) using traditional Xilinx's tools; 2) using an optimized version of the Xilinx's drivers. The collected numbers demonstrate that our solution reaches a gain up to 10 times faster than the other approaches.

Logistics Management: Cases Studies,

DTIC Science & Technology

LOGISTICS , * MANAGEMENT PLANNING AND CONTROL), DECISION MAKING, INVENTORY CONTROL, SPARE PARTS, AIR FORCE EQUIPMENT, NAVAL AIRCRAFT, MAINTENANCE, DEPLOYMENT, SCHEDULING, SYSTEMS ENGINEERING, TEXTBOOKS

The Value of Weather Forecast in Irrigation

NASA Astrophysics Data System (ADS)

Cai, X.; Wang, D.

2007-12-01

This paper studies irrigation scheduling (when and how much water to apply during the crop growth season) in the Havana Lowlands region, Illinois, using meteorological, agronomic and agricultural production data from 2002. Irrigation scheduling determines the timing and amount of water applied to an irrigated cropland during the crop growing season. In this study a hydrologic-agronomic simulation is coupled with an optimization algorithm to search for the optimal irrigation schedule under various weather forecast horizons. The economic profit of irrigated corn from an optimized scheduling is compared to that from and the actual schedule, which is adopted from a pervious study. Extended and reliable climate prediction and weather forecast are found to be significantly valuable. If a weather forecast horizon is long enough to include the critical crop growth stage, in which crop yield bears the maximum loss over all stages, much economic loss can be avoided. Climate predictions of one to two months, which can cover the critical period, might be even more beneficial during a dry year. The other purpose of this paper is to analyze farmers' behavior in irrigation scheduling by comparing the "actual" schedule to the "optimized" ones. The ultimate goal of irrigation schedule optimization is to provide information to farmers so that they may modify their behavior. In practice, farmers' decision may not follow an optimal irrigation schedule due to the impact of various factors such as natural conditions, policies, farmers' habits and empirical knowledge, and the uncertain or inexact information that they receive. In this study farmers' behavior in irrigation decision making is analyzed by comparing the "actual" schedule to the "optimized" ones. This study finds that the identification of the crop growth stage with the most severe water stress is critical for irrigation scheduling. For the case study site in the year of 2002, framers' response to water stress was found to be late; they did not even respond appropriately to a major rainfall just 3 days ahead, which might be due to either an unreliable weather forecast or farmer's ignorance of the forecast.

Designing an optimal software intensive system acquisition: A game theoretic approach

NASA Astrophysics Data System (ADS)

Buettner, Douglas John

The development of schedule-constrained software-intensive space systems is challenging. Case study data from national security space programs developed at the U.S. Air Force Space and Missile Systems Center (USAF SMC) provide evidence of the strong desire by contractors to skip or severely reduce software development design and early defect detection methods in these schedule-constrained environments. The research findings suggest recommendations to fully address these issues at numerous levels. However, the observations lead us to investigate modeling and theoretical methods to fundamentally understand what motivated this behavior in the first place. As a result, Madachy's inspection-based system dynamics model is modified to include unit testing and an integration test feedback loop. This Modified Madachy Model (MMM) is used as a tool to investigate the consequences of this behavior on the observed defect dynamics for two remarkably different case study software projects. Latin Hypercube sampling of the MMM with sample distributions for quality, schedule and cost-driven strategies demonstrate that the higher cost and effort quality-driven strategies provide consistently better schedule performance than the schedule-driven up-front effort-reduction strategies. Game theory reasoning for schedule-driven engineers cutting corners on inspections and unit testing is based on the case study evidence and Austin's agency model to describe the observed phenomena. Game theory concepts are then used to argue that the source of the problem and hence the solution to developers cutting corners on quality for schedule-driven system acquisitions ultimately lies with the government. The game theory arguments also lead to the suggestion that the use of a multi-player dynamic Nash bargaining game provides a solution for our observed lack of quality game between the government (the acquirer) and "large-corporation" software developers. A note is provided that argues this multi-player dynamic Nash bargaining game also provides the solution to Freeman Dyson's problem, for a way to place a label of good or bad on systems.

A new task scheduling algorithm based on value and time for cloud platform

NASA Astrophysics Data System (ADS)

Kuang, Ling; Zhang, Lichen

2017-08-01

Tasks scheduling, a key part of increasing resource utilization and enhancing system performance, is a never outdated problem especially in cloud platforms. Based on the value density algorithm of the real-time task scheduling system and the character of the distributed system, the paper present a new task scheduling algorithm by further studying the cloud technology and the real-time system: Least Level Value Density First (LLVDF). The algorithm not only introduces some attributes of time and value for tasks, it also can describe weighting relationships between these properties mathematically. As this feature of the algorithm, it can gain some advantages to distinguish between different tasks more dynamically and more reasonably. When the scheme was used in the priority calculation of the dynamic task scheduling on cloud platform, relying on its advantage, it can schedule and distinguish tasks with large amounts and many kinds more efficiently. The paper designs some experiments, some distributed server simulation models based on M/M/C model of queuing theory and negative arrivals, to compare the algorithm against traditional algorithm to observe and show its characters and advantages.

Technical Adequacy of Response to Intervention Decisions

ERIC Educational Resources Information Center

VanDerHeyden, Amanda M.

2011-01-01

Perhaps the greatest value of response to intervention (RTI) as a decision framework is that it brings attention to variables (e.g., mastery of prerequisite skills, frequency of instructional corrective feedback, reinforcement schedules for correct responding) that if changed might make a meaningful difference for students (e.g., child rate of…

May Babies and Posttenure Babies: Maternal Decisions of Women Professors

ERIC Educational Resources Information Center

Armenti, Carmen

2004-01-01

This research explores the maternal and career progression decisions of different generations of women professors in Canada. Nineteen women, interviewed in-depth, reveal how they carefully plan childbearing and childrearing experiences around their demanding work schedules, by having May babies or posttenure babies. Results demonstrate the need…

Multiple Criteria Decision-Making Techniques in Higher Education

ERIC Educational Resources Information Center

Ho, William; Dey, Prasanta K.; Higson, Helen E.

2006-01-01

Purpose: The purpose of this paper is to review the literature which focuses on four major higher education decision problems. These are: resource allocation; performance measurement; budgeting; and scheduling. Design/methodology/approach: Related articles appearing in the international journals from 1996 to 2005 are gathered and analyzed so that…

Implementing a Quality Needs Assessment

ERIC Educational Resources Information Center

Cuiccio, Cary

2012-01-01

Districts nationwide are facing budget cuts that, to some, feel more like funding cliffs. Accordingly, school teams are re-examining their personnel, programs, and schedules so that they can make difficult decisions about where to spend resources to realize the greatest improvement. The principals who are able to make decisions with data from…

DORCA II: Dynamic operations requirements and cost analysis program

NASA Technical Reports Server (NTRS)

1976-01-01

Program is written to handle logistics of acquisition and transport of personnel, equipment, and services and to determine costs, transport schedules, acquisition schedules, and fuel requirements of cargo transport.

Decision support for clinical laboratory capacity planning.

PubMed

van Merode, G G; Hasman, A; Derks, J; Goldschmidt, H M; Schoenmaker, B; Oosten, M

1995-01-01

The design of a decision support system for capacity planning in clinical laboratories is discussed. The DSS supports decisions concerning the following questions: how should the laboratory be divided into job shops (departments/sections), how should staff be assigned to workstations and how should samples be assigned to workstations for testing. The decision support system contains modules for supporting decisions at the overall laboratory level (concerning the division of the laboratory into job shops) and for supporting decisions at the job shop level (assignment of staff to workstations and sample scheduling). Experiments with these modules are described showing both the functionality and the validity.

Adaptive critics for dynamic optimization.

PubMed

Kulkarni, Raghavendra V; Venayagamoorthy, Ganesh Kumar

2010-06-01

A novel action-dependent adaptive critic design (ACD) is developed for dynamic optimization. The proposed combination of a particle swarm optimization-based actor and a neural network critic is demonstrated through dynamic sleep scheduling of wireless sensor motes for wildlife monitoring. The objective of the sleep scheduler is to dynamically adapt the sleep duration to node's battery capacity and movement pattern of animals in its environment in order to obtain snapshots of the animal on its trajectory uniformly. Simulation results show that the sleep time of the node determined by the actor critic yields superior quality of sensory data acquisition and enhanced node longevity. Copyright 2010 Elsevier Ltd. All rights reserved.

Nuclear Weapons: NNSA Has a New Approach to Managing the B61-12 Life Extension, but a Constrained Schedule and Other Risks Remain

DTIC Science & Technology

2016-02-01

components. In 2010, they began an LEP to consolidate four versions of a legacy nuclear weapon, the B61 bomb , into a bomb called the B61-12 (see...Force Integrated Master Schedule BIMS Boeing Integrated Master Schedule B61 bomb B61 legacy bomb CD critical decision Cost Guide GAO Cost...are versions of the B61 bomb , an aircraft-delivered weapon that is a key component of the United States’ commitments to the North Atlantic Treaty

A field test of procedures for evaluating and scheduling white-pine weevil control

Treesearch

Robert P. Ford; Robert L. Talerico; D. Gordon Mott

1965-01-01

Procedures have recently been developed that permit economic and biological information to be integrated in making decisions about the need for control against the white-pine weevil, and in scheduling control in young white pine plantations. The procedures are based upon studies of the magnitude of economic losses that result from weevil attack in white pine and upon...

Inputs requested from earth resources remote sensing data users regarding LANDSAT-C mission requirements and data needs

NASA Technical Reports Server (NTRS)

1976-01-01

Inputs from prospective LANDSAT-C data users are requested to aid NASA in defining LANDSAT-C mission and data requirements and in making decisions regarding the scheduling of satellite operations and ground data processing operations. Design specifications, multispectral band scanner performance characteristics, satellite schedule operations, and types of available data products are briefly described.

[The social hygiene problems in the operator work of hydroelectric power station workers and the means for enhancing work capacity].

PubMed

Karakashian, A N; Lepeshkina, T R; Ratushnaia, A N; Glushchenko, S S; Zakharenko, M I; Lastovchenko, V B; Diordichuk, T I

1993-01-01

Weight, tension and harmfulness of professional activity, peculiarities of labour conditions and characteristics of work, shift dynamics of operative personnel's working capacity were studied in the course of 8-hour working day currently accepted at hydroelectric power stations (HEPS) and experimental 12-hour schedule. Working conditions classified as "admissible", positive dynamics of operators' state, their social and material contentment were a basis for 12-hour two-shift schedule to be recommended as more appropriate. At the same time, problem of optimal shift schedules for operative personnel of HEPS remains unsolved and needs to be further explored.

Scheduling Software for Complex Scenarios

NASA Technical Reports Server (NTRS)

2006-01-01

Preparing a vehicle and its payload for a single launch is a complex process that involves thousands of operations. Because the equipment and facilities required to carry out these operations are extremely expensive and limited in number, optimal assignment and efficient use are critically important. Overlapping missions that compete for the same resources, ground rules, safety requirements, and the unique needs of processing vehicles and payloads destined for space impose numerous constraints that, when combined, require advanced scheduling. Traditional scheduling systems use simple algorithms and criteria when selecting activities and assigning resources and times to each activity. Schedules generated by these simple decision rules are, however, frequently far from optimal. To resolve mission-critical scheduling issues and predict possible problem areas, NASA historically relied upon expert human schedulers who used their judgment and experience to determine where things should happen, whether they will happen on time, and whether the requested resources are truly necessary.

Two-machine flow shop scheduling integrated with preventive maintenance planning

NASA Astrophysics Data System (ADS)

Wang, Shijin; Liu, Ming

2016-02-01

This paper investigates an integrated optimisation problem of production scheduling and preventive maintenance (PM) in a two-machine flow shop with time to failure of each machine subject to a Weibull probability distribution. The objective is to find the optimal job sequence and the optimal PM decisions before each job such that the expected makespan is minimised. To investigate the value of integrated scheduling solution, computational experiments on small-scale problems with different configurations are conducted with total enumeration method, and the results are compared with those of scheduling without maintenance but with machine degradation, and individual job scheduling combined with independent PM planning. Then, for large-scale problems, four genetic algorithm (GA) based heuristics are proposed. The numerical results with several large problem sizes and different configurations indicate the potential benefits of integrated scheduling solution and the results also show that proposed GA-based heuristics are efficient for the integrated problem.

Study on optimization of the short-term operation of cascade hydropower stations by considering output error

NASA Astrophysics Data System (ADS)

Wang, Liping; Wang, Boquan; Zhang, Pu; Liu, Minghao; Li, Chuangang

2017-06-01

The study of reservoir deterministic optimal operation can improve the utilization rate of water resource and help the hydropower stations develop more reasonable power generation schedules. However, imprecise forecasting inflow may lead to output error and hinder implementation of power generation schedules. In this paper, output error generated by the uncertainty of the forecasting inflow was regarded as a variable to develop a short-term reservoir optimal operation model for reducing operation risk. To accomplish this, the concept of Value at Risk (VaR) was first applied to present the maximum possible loss of power generation schedules, and then an extreme value theory-genetic algorithm (EVT-GA) was proposed to solve the model. The cascade reservoirs of Yalong River Basin in China were selected as a case study to verify the model, according to the results, different assurance rates of schedules can be derived by the model which can present more flexible options for decision makers, and the highest assurance rate can reach 99%, which is much higher than that without considering output error, 48%. In addition, the model can greatly improve the power generation compared with the original reservoir operation scheme under the same confidence level and risk attitude. Therefore, the model proposed in this paper can significantly improve the effectiveness of power generation schedules and provide a more scientific reference for decision makers.

Characterization of Decision Making Behaviors Associated with Human Systems Integration (HSI) Design Tradeoffs: Subject Matter Expert Interviews

DTIC Science & Technology

2014-11-18

this research was to characterize the naturalistic decision making process used in Naval Aviation acquisition to assess cost, schedule and...Naval Aviation acquisitions can be identified, which can support the future development of new processes and tools for training and decision making...part of Department of Defense acquisition processes , HSI ensures that operator, maintainer and sustainer considerations are incorporated into

Multi-objective decision-making model based on CBM for an aircraft fleet

NASA Astrophysics Data System (ADS)

Luo, Bin; Lin, Lin

2018-04-01

Modern production management patterns, in which multi-unit (e.g., a fleet of aircrafts) are managed in a holistic manner, have brought new challenges for multi-unit maintenance decision making. To schedule a good maintenance plan, not only does the individual machine maintenance have to be considered, but also the maintenance of the other individuals have to be taken into account. Since most condition-based maintenance researches for aircraft focused on solely reducing maintenance cost or maximizing the availability of single aircraft, as well as considering that seldom researches concentrated on both the two objectives: minimizing cost and maximizing the availability of a fleet (total number of available aircraft in fleet), a multi-objective decision-making model based on condition-based maintenance concentrated both on the above two objectives is established. Furthermore, in consideration of the decision maker may prefer providing the final optimal result in the form of discrete intervals instead of a set of points (non-dominated solutions) in real decision-making problem, a novel multi-objective optimization method based on support vector regression is proposed to solve the above multi-objective decision-making model. Finally, a case study regarding a fleet is conducted, with the results proving that the approach efficiently generates outcomes that meet the schedule requirements.

2007 Wholesale Power Rate Adjustment Proceeding (WP-07) : Administrator's Final Record of Decision.

DOE Office of Scientific and Technical Information (OSTI.GOV)

United States. Bonneville Power Administration.

2006-07-01

This Record of Decision (ROD) contains the decisions of the Bonneville Power Administration (BPA), based on the record compiled in this rate proceeding, with respect to the adoption of power rates for the three-year rate period commencing October 1, 2006, through September 30, 2009. This ''2007 Wholesale Power Rate Adjustment Proceeding'' is designed to establish replacement rate schedules and General Rate Schedule Provisions (GRSPs) for those that expire on September 30, 2006. This power rate case also establishes the General Transfer Agreement (GTA) Delivery Charge for the period of October 1, 2007, through September 30, 2009. BPA's Power Subscription Strategymore » and Record of Decision (Subscription Strategy), as well as other Agency processes, provide much of the policy context for this rate case and are described in Section 2. This ROD follows a full evidentiary hearing and briefing, including an Oral Argument before the BPA Administrator. Sections 3 through 18, including any appendices or attachments, present the issues raised by parties in this proceeding, the parties positions, BPA staff positions on the issues, BPA's evaluations of the positions, and the Administrator's decisions. Parties had the opportunity to file briefs on exceptions to the Draft ROD, before issuance of this Final Record of Decision.« less

Spot and Runway Departure Advisor

NASA Technical Reports Server (NTRS)

Jung, Yoon Chul

2013-01-01

The Spot and Runway Departure Advisor (SARDA) is a research prototype of a decision support tool for ATC tower controllers to assist in manging and controlling traffic on the surface of an airport. SARDA employs a scheduler to generate an optimal runway schedule and gate push-back - spot release sequence and schedule that improves efficiency of surface operations. The advisories for ATC tower controllers are displayed on an Electronic Flight Strip (EFS) system. The human-in-the-loop simulation of the SARDA tool was conducted for east operations of Dallas-Ft. Worth International Airport (DFW) to evaluate performance of the SARDA tool and human factors, such as situational awareness and workload. The results indicates noticeable taxi delay reduction and fuel savings by using the SARDA tool. Reduction in controller workload were also observed throughout the scenario runs. The future plan includes modeling and simulation of the ramp operations of the Charlotte International Airport, and develop a decision support tool for the ramp controllers.

Intelligent Scheduling for Underground Mobile Mining Equipment.

PubMed

Song, Zhen; Schunnesson, Håkan; Rinne, Mikael; Sturgul, John

2015-01-01

Many studies have been carried out and many commercial software applications have been developed to improve the performances of surface mining operations, especially for the loader-trucks cycle of surface mining. However, there have been quite few studies aiming to improve the mining process of underground mines. In underground mines, mobile mining equipment is mostly scheduled instinctively, without theoretical support for these decisions. Furthermore, in case of unexpected events, it is hard for miners to rapidly find solutions to reschedule and to adapt the changes. This investigation first introduces the motivation, the technical background, and then the objective of the study. A decision support instrument (i.e. schedule optimizer for mobile mining equipment) is proposed and described to address this issue. The method and related algorithms which are used in this instrument are presented and discussed. The proposed method was tested by using a real case of Kittilä mine located in Finland. The result suggests that the proposed method can considerably improve the working efficiency and reduce the working time of the underground mine.

Value of information of repair times for offshore wind farm maintenance planning

NASA Astrophysics Data System (ADS)

Seyr, Helene; Muskulus, Michael

2016-09-01

A large contribution to the total cost of energy in offshore wind farms is due to maintenance costs. In recent years research has focused therefore on lowering the maintenance costs using different approaches. Decision support models for scheduling the maintenance exist already, dealing with different factors influencing the scheduling. Our contribution deals with the uncertainty in the repair times. Given the mean repair times for different turbine components we make some assumptions regarding the underlying repair time distribution. We compare the results of a decision support model for the mean times to repair and those repair time distributions. Additionally, distributions with the same mean but different variances are compared under the same conditions. The value of lowering the uncertainty in the repair time is calculated and we find that using distributions significantly decreases the availability, when scheduling maintenance for multiple turbines in a wind park. Having detailed information about the repair time distribution may influence the results of maintenance modeling and might help identify cost factors.

Dynamic Photorefractive Memory and its Application for Opto-Electronic Neural Networks.

NASA Astrophysics Data System (ADS)

Sasaki, Hironori

This dissertation describes the analysis of the photorefractive crystal dynamics and its application for opto-electronic neural network systems. The realization of the dynamic photorefractive memory is investigated in terms of the following aspects: fast memory update, uniform grating multiplexing schedules and the prevention of the partial erasure of existing gratings. The fast memory update is realized by the selective erasure process that superimposes a new grating on the original one with an appropriate phase shift. The dynamics of the selective erasure process is analyzed using the first-order photorefractive material equations and experimentally confirmed. The effects of beam coupling and fringe bending on the selective erasure dynamics are also analyzed by numerically solving a combination of coupled wave equations and the photorefractive material equation. Incremental recording technique is proposed as a uniform grating multiplexing schedule and compared with the conventional scheduled recording technique in terms of phase distribution in the presence of an external dc electric field, as well as the image gray scale dependence. The theoretical analysis and experimental results proved the superiority of the incremental recording technique over the scheduled recording. Novel recirculating information memory architecture is proposed and experimentally demonstrated to prevent partial degradation of the existing gratings by accessing the memory. Gratings are circulated through a memory feed back loop based on the incremental recording dynamics and demonstrate robust read/write/erase capabilities. The dynamic photorefractive memory is applied to opto-electronic neural network systems. Module architecture based on the page-oriented dynamic photorefractive memory is proposed. This module architecture can implement two complementary interconnection organizations, fan-in and fan-out. The module system scalability and the learning capabilities are theoretically investigated using the photorefractive dynamics described in previous chapters of the dissertation. The implementation of the feed-forward image compression network with 900 input and 9 output neurons with 6-bit interconnection accuracy is experimentally demonstrated. Learning of the Perceptron network that determines sex based on input face images of 900 pixels is also successfully demonstrated.

Exploring the Decision Process of "School Leavers" and "Mature Students" in University Choice.

ERIC Educational Resources Information Center

Harker, Debra; Slade, Peter; Harker, Michael

2001-01-01

Examined potential differences in how Australian mature entrants and those who have just left school undertake the decision to attend a new university. Found differences between the two groups in terms of their need for public transportation and scheduling convenience, emphasis on program quality, and college search strategies. (EV)

Improved Decision Making for School Organization. What and What for

ERIC Educational Resources Information Center

Myers, Donald A.; Sinclair, Robert

1973-01-01

A framework of 13 decision criteria to give educators help in comparing the relative merits of different forms of school organization. The methods of school organization judged to be in widespread use and defined in the article are (1) the self-contained classroom, team teaching, departmentalization, modular scheduling, differentiated staffing,…

Forestry Decisions

Treesearch

Stephen G. Boyce

1985-01-01

Viewing the forest as a system that self-organizes in response to a schedule of harvest and culture provides a new basis for making forestry decisions. Computer simulations of states of forest organization through time provide displays of tne production of forest benefits ranging from timber and water to wildlife and recreation. From these displays, the manager chooses...

A Methodology for Making Early Comparative Architecture Performance Evaluations

ERIC Educational Resources Information Center

Doyle, Gerald S.

2010-01-01

Complex and expensive systems' development suffers from a lack of method for making good system-architecture-selection decisions early in the development process. Failure to make a good system-architecture-selection decision increases the risk that a development effort will not meet cost, performance and schedule goals. This research provides a…

75 FR 13217 - Energy Conservation Program for Consumer Products: Classifying Products as Covered Products

Federal Register 2010, 2011, 2012, 2013, 2014

2010-03-19

... determines that labeling will assist purchasers in making purchasing decisions and is economically and... Sept. 7, 2005), DOE has re-assessed its rulemaking procedures and scheduling decisions. DOE held a... the focus of the RECS. This behavior is a primary driver behind purchases and consumption of energy in...

Scheduling multimedia services in cloud computing environment

NASA Astrophysics Data System (ADS)

Liu, Yunchang; Li, Chunlin; Luo, Youlong; Shao, Yanling; Zhang, Jing

2018-02-01

Currently, security is a critical factor for multimedia services running in the cloud computing environment. As an effective mechanism, trust can improve security level and mitigate attacks within cloud computing environments. Unfortunately, existing scheduling strategy for multimedia service in the cloud computing environment do not integrate trust mechanism when making scheduling decisions. In this paper, we propose a scheduling scheme for multimedia services in multi clouds. At first, a novel scheduling architecture is presented. Then, We build a trust model including both subjective trust and objective trust to evaluate the trust degree of multimedia service providers. By employing Bayesian theory, the subjective trust degree between multimedia service providers and users is obtained. According to the attributes of QoS, the objective trust degree of multimedia service providers is calculated. Finally, a scheduling algorithm integrating trust of entities is proposed by considering the deadline, cost and trust requirements of multimedia services. The scheduling algorithm heuristically hunts for reasonable resource allocations and satisfies the requirement of trust and meets deadlines for the multimedia services. Detailed simulated experiments demonstrate the effectiveness and feasibility of the proposed trust scheduling scheme.

12-hour shifts: an ethical dilemma for the nurse executive.

PubMed

Lorenz, Susan G

2008-06-01

Flexible work hours, including 12-hour shifts, have become a common scheduling option for nurses. The author explores whether 12-hour shifts are an ethical scheduling option for nurses because recent research suggests that 12-hour shifts are a potential hazard to patients. A multistep model for ethical decision making, reflecting the concept of procedural justice, is used to examine this issue.

Modeling the Violation of Reward Maximization and Invariance in Reinforcement Schedules

PubMed Central

La Camera, Giancarlo; Richmond, Barry J.

2008-01-01

It is often assumed that animals and people adjust their behavior to maximize reward acquisition. In visually cued reinforcement schedules, monkeys make errors in trials that are not immediately rewarded, despite having to repeat error trials. Here we show that error rates are typically smaller in trials equally distant from reward but belonging to longer schedules (referred to as “schedule length effect”). This violates the principles of reward maximization and invariance and cannot be predicted by the standard methods of Reinforcement Learning, such as the method of temporal differences. We develop a heuristic model that accounts for all of the properties of the behavior in the reinforcement schedule task but whose predictions are not different from those of the standard temporal difference model in choice tasks. In the modification of temporal difference learning introduced here, the effect of schedule length emerges spontaneously from the sensitivity to the immediately preceding trial. We also introduce a policy for general Markov Decision Processes, where the decision made at each node is conditioned on the motivation to perform an instrumental action, and show that the application of our model to the reinforcement schedule task and the choice task are special cases of this general theoretical framework. Within this framework, Reinforcement Learning can approach contextual learning with the mixture of empirical findings and principled assumptions that seem to coexist in the best descriptions of animal behavior. As examples, we discuss two phenomena observed in humans that often derive from the violation of the principle of invariance: “framing,” wherein equivalent options are treated differently depending on the context in which they are presented, and the “sunk cost” effect, the greater tendency to continue an endeavor once an investment in money, effort, or time has been made. The schedule length effect might be a manifestation of these phenomena in monkeys. PMID:18688266

Modeling the violation of reward maximization and invariance in reinforcement schedules.

PubMed

La Camera, Giancarlo; Richmond, Barry J

2008-08-08

It is often assumed that animals and people adjust their behavior to maximize reward acquisition. In visually cued reinforcement schedules, monkeys make errors in trials that are not immediately rewarded, despite having to repeat error trials. Here we show that error rates are typically smaller in trials equally distant from reward but belonging to longer schedules (referred to as "schedule length effect"). This violates the principles of reward maximization and invariance and cannot be predicted by the standard methods of Reinforcement Learning, such as the method of temporal differences. We develop a heuristic model that accounts for all of the properties of the behavior in the reinforcement schedule task but whose predictions are not different from those of the standard temporal difference model in choice tasks. In the modification of temporal difference learning introduced here, the effect of schedule length emerges spontaneously from the sensitivity to the immediately preceding trial. We also introduce a policy for general Markov Decision Processes, where the decision made at each node is conditioned on the motivation to perform an instrumental action, and show that the application of our model to the reinforcement schedule task and the choice task are special cases of this general theoretical framework. Within this framework, Reinforcement Learning can approach contextual learning with the mixture of empirical findings and principled assumptions that seem to coexist in the best descriptions of animal behavior. As examples, we discuss two phenomena observed in humans that often derive from the violation of the principle of invariance: "framing," wherein equivalent options are treated differently depending on the context in which they are presented, and the "sunk cost" effect, the greater tendency to continue an endeavor once an investment in money, effort, or time has been made. The schedule length effect might be a manifestation of these phenomena in monkeys.

Automation Improves Schedule Quality and Increases Scheduling Efficiency for Residents.

PubMed

Perelstein, Elizabeth; Rose, Ariella; Hong, Young-Chae; Cohn, Amy; Long, Micah T

2016-02-01

Medical resident scheduling is difficult due to multiple rules, competing educational goals, and ever-evolving graduate medical education requirements. Despite this, schedules are typically created manually, consuming hours of work, producing schedules of varying quality, and yielding negative consequences for resident morale and learning. To determine whether computerized decision support can improve the construction of residency schedules, saving time and improving schedule quality. The Optimized Residency Scheduling Assistant was designed by a team from the University of Michigan Department of Industrial and Operations Engineering. It was implemented in the C.S. Mott Children's Hospital Pediatric Emergency Department in the 2012-2013 academic year. The 4 metrics of schedule quality that were compared between the 2010-2011 and 2012-2013 academic years were the incidence of challenging shift transitions, the incidence of shifts following continuity clinics, the total shift inequity, and the night shift inequity. All scheduling rules were successfully incorporated. Average schedule creation time fell from 22 to 28 hours to 4 to 6 hours per month, and 3 of 4 metrics of schedule quality significantly improved. For the implementation year, the incidence of challenging shift transitions decreased from 83 to 14 (P < .01); the incidence of postclinic shifts decreased from 72 to 32 (P < .01); and the SD of night shifts dropped by 55.6% (P < .01). This automated shift scheduling system improves the current manual scheduling process, reducing time spent and improving schedule quality. Embracing such automated tools can benefit residency programs with shift-based scheduling needs.

Work/Family Balancing and 24/7 Work Schedules: Network Analysis of Strategies in a Transport Company Cleaning Service: Concilier travail-famille et horaires 24/7: analyse réseau des stratégies au sein du service de nettoyage d'une compagnie de transport.

PubMed

Lefrançois, Mélanie; Saint-Charles, Johanne; Riel, Jessica

2017-11-01

Whether or not official work/family balance measures exist within an organization, scheduling accommodations often go through informal channels involving colleagues and superiors and are negotiated within interpersonal relationships. This study examines the relationship dimensions of the scheduling strategies of cleaners working atypical hours in the transport sector through the lenses of ergonomic activity, network, and gender analyses. Using semi-directed interviews, observation, and network analysis, we revealed the effect of gender on relationship dynamics and the influence of these dynamics on work/family balance strategies deployed by cleaners. One of the main contributions of this study is to demonstrate the decisive effect of relationships by revealing inequalities in access to organizational social networks. Creating spaces to discuss work/family balancing and a more equitable circulation of information could contribute to reducing inequalities associated with gender, social status, and family responsibilities and support the work/family strategies developed by workers dealing with restrictive work schedules. Résumé Les accommodements du temps de travail pour la conciliation travail-famille (CTF) passent souvent par des ententes informelles qui s'inscrivent dans les relations entre collègues ou avec des gestionnaires. Notre étude, intégrant l'ergonomie et la communication dans une perspective de genre, porte sur les dimensions relationnelles des stratégies de choix d'horaire d'agentes et agents de nettoyage devant composer avec des horaires atypiques dans le secteur des transports. À partir d'entretiens semi-dirigés, d'observations et d'analyse de réseaux, nous avons pu observer l'influence des dynamiques relationnelles, notamment de genre, sur les stratégies de CTF. Un apport central de cette étude est de montrer l'effet structurant des relations en révélant notamment des inégalités dans l'accès aux ressources facilitant le choix d'horaire, mais aussi dans l'inclusion au sein du réseau de relations. L'article conclut en proposant des pistes de solutions concrètes pour la réduction de ces inégalités.

Linear-parameter-varying gain-scheduled control of aerospace systems

NASA Astrophysics Data System (ADS)

Barker, Jeffrey Michael

The dynamics of many aerospace systems vary significantly as a function of flight condition. Robust control provides methods of guaranteeing performance and stability goals across flight conditions. In mu-syntthesis, changes to the dynamical system are primarily treated as uncertainty. This method has been successfully applied to many control problems, and here is applied to flutter control. More recently, two techniques for generating robust gain-scheduled controller have been developed. Linear fractional transformation (LFT) gain-scheduled control is an extension of mu-synthesis in which the plant and controller are explicit functions of parameters measurable in real-time. This LFT gain-scheduled control technique is applied to the Benchmark Active Control Technology (BACT) wing, and compared with mu-synthesis control. Linear parameter-varying (LPV) gain-scheduled control is an extension of Hinfinity control to parameter varying systems. LPV gain-scheduled control directly incorporates bounds on the rate of change of the scheduling parameters, and often reduces conservatism inherent in LFT gain-scheduled control. Gain-scheduled LPV control of the BACT wing compares very favorably with the LFT controller. Gain-scheduled LPV controllers are generated for the lateral-directional and longitudinal axes of the Innovative Control Effectors (ICE) aircraft and implemented in nonlinear simulations and real-time piloted nonlinear simulations. Cooper-Harper and pilot-induced oscillation ratings were obtained for an initial design, a reference aircraft and a redesign. Piloted simulation results for the initial LPV gain-scheduled control of the ICE aircraft are compared with results for a conventional fighter aircraft in discrete pitch and roll angle tracking tasks. The results for the redesigned controller are significantly better than both the previous LPV controller and the conventional aircraft.

Analysis of tasks for dynamic man/machine load balancing in advanced helicopters

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jorgensen, C.C.

1987-10-01

This report considers task allocation requirements imposed by advanced helicopter designs incorporating mixes of human pilots and intelligent machines. Specifically, it develops an analogy between load balancing using distributed non-homogeneous multiprocessors and human team functions. A taxonomy is presented which can be used to identify task combinations likely to cause overload for dynamic scheduling and process allocation mechanisms. Designer criteria are given for function decomposition, separation of control from data, and communication handling for dynamic tasks. Possible effects of n-p complete scheduling problems are noted and a class of combinatorial optimization methods are examined.

Multiresource allocation and scheduling for periodic soft real-time applications

NASA Astrophysics Data System (ADS)

Gopalan, Kartik; Chiueh, Tzi-cker

2001-12-01

Real-time applications that utilize multiple system resources, such as CPU, disks, and network links, require coordinated scheduling of these resources in order to meet their end-to-end performance requirements. Most state-of-the-art operating systems support independent resource allocation and deadline-driven scheduling but lack coordination among multiple heterogeneous resources. This paper describes the design and implementation of an Integrated Real-time Resource Scheduler (IRS) that performs coordinated allocation and scheduling of multiple heterogeneous resources on the same machine for periodic soft real-time application. The principal feature of IRS is a heuristic multi-resource allocation algorithm that reserves multiple resources for real-time applications in a manner that can maximize the number of applications admitted into the system in the long run. At run-time, a global scheduler dispatches the tasks of the soft real-time application to individual resource schedulers according to the precedence constraints between tasks. The individual resource schedulers, which could be any deadline based schedulers, can make scheduling decisions locally and yet collectively satisfy a real-time application's performance requirements. The tightness of overall timing guarantees is ultimately determined by the properties of individual resource schedulers. However, IRS maximizes overall system resource utilization efficiency by coordinating deadline assignment across multiple tasks in a soft real-time application.

A Conceptual Level Design for a Static Scheduler for Hard Real-Time Systems

DTIC Science & Technology

1988-03-01

The design of hard real - time systems is gaining a great deal of attention in the software engineering field as more and more real-world processes are...for these hard real - time systems . PSDL, as an executable design language, is supported by an execution support system consisting of a static scheduler, dynamic scheduler, and translator.

Autonomous Scheduling Requirements for Agile Cubesat Constellations in Earth Observation

NASA Astrophysics Data System (ADS)

Nag, S.; Li, A. S. X.; Kumar, S.

2017-12-01

Distributed Space Missions such as formation flight and constellations, are being recognized as important Earth Observation solutions to increase measurement samples over space and time. Cubesats are increasing in size (27U, 40 kg) with increasing capabilities to host imager payloads. Given the precise attitude control systems emerging commercially, Cubesats now have the ability to slew and capture images within short notice. Prior literature has demonstrated a modular framework that combines orbital mechanics, attitude control and scheduling optimization to plan the time-varying orientation of agile Cubesats in a constellation such that they maximize the number of observed images, within the constraints of hardware specs. Schedule optimization is performed on the ground autonomously, using dynamic programming with two levels of heuristics, verified and improved upon using mixed integer linear programming. Our algorithm-in-the-loop simulation applied to Landsat's use case, captured up to 161% more Landsat images than nadir-pointing sensors with the same field of view, on a 2-satellite constellation over a 12-hour simulation. In this paper, we will derive the requirements for the above algorithm to run onboard small satellites such that the constellation can make time-sensitive decisions to slew and capture images autonomously, without ground support. We will apply the above autonomous algorithm to a time critical use case - monitoring of precipitation and subsequent effects on floods, landslides and soil moisture, as quantified by the NASA Unified Weather Research and Forecasting Model. Since the latency between these event occurrences is quite low, they make a strong case for autonomous decisions among satellites in a constellation. The algorithm can be implemented in the Plan Execution Interchange Language - NASA's open source technology for automation, used to operate the International Space Station and LADEE's in flight software - enabling a controller-in-the-loop demonstration. The autonomy software can then be integrated with NASA's open source Core Flight Software, ported onto a Raspberry Pi 3.0 for a software-in-the-loop demonstration. Future use cases can be time critical events such as cloud movement, storms or other disasters, and in conjunction with other platforms in a Sensor Web.

Solution and reasoning reuse in space planning and scheduling applications

NASA Technical Reports Server (NTRS)

Verfaillie, Gerard; Schiex, Thomas

1994-01-01

In the space domain, as in other domains, the CSP (Constraint Satisfaction Problems) techniques are increasingly used to represent and solve planning and scheduling problems. But these techniques have been developed to solve CSP's which are composed of fixed sets of variables and constraints, whereas many planning and scheduling problems are dynamic. It is therefore important to develop methods which allow a new solution to be rapidly found, as close as possible to the previous one, when some variables or constraints are added or removed. After presenting some existing approaches, this paper proposes a simple and efficient method, which has been developed on the basis of the dynamic backtracking algorithm. This method allows previous solution and reasoning to be reused in the framework of a CSP which is close to the previous one. Some experimental results on general random CSPs and on operation scheduling problems for remote sensing satellites are given.

A hybrid dynamic harmony search algorithm for identical parallel machines scheduling

NASA Astrophysics Data System (ADS)

Chen, Jing; Pan, Quan-Ke; Wang, Ling; Li, Jun-Qing

2012-02-01

In this article, a dynamic harmony search (DHS) algorithm is proposed for the identical parallel machines scheduling problem with the objective to minimize makespan. First, an encoding scheme based on a list scheduling rule is developed to convert the continuous harmony vectors to discrete job assignments. Second, the whole harmony memory (HM) is divided into multiple small-sized sub-HMs, and each sub-HM performs evolution independently and exchanges information with others periodically by using a regrouping schedule. Third, a novel improvisation process is applied to generate a new harmony by making use of the information of harmony vectors in each sub-HM. Moreover, a local search strategy is presented and incorporated into the DHS algorithm to find promising solutions. Simulation results show that the hybrid DHS (DHS_LS) is very competitive in comparison to its competitors in terms of mean performance and average computational time.

Fault-tolerant dynamic task graph scheduling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kurt, Mehmet C.; Krishnamoorthy, Sriram; Agrawal, Kunal

2014-11-16

In this paper, we present an approach to fault tolerant execution of dynamic task graphs scheduled using work stealing. In particular, we focus on selective and localized recovery of tasks in the presence of soft faults. We elicit from the user the basic task graph structure in terms of successor and predecessor relationships. The work stealing-based algorithm to schedule such a task graph is augmented to enable recovery when the data and meta-data associated with a task get corrupted. We use this redundancy, and the knowledge of the task graph structure, to selectively recover from faults with low space andmore » time overheads. We show that the fault tolerant design retains the essential properties of the underlying work stealing-based task scheduling algorithm, and that the fault tolerant execution is asymptotically optimal when task re-execution is taken into account. Experimental evaluation demonstrates the low cost of recovery under various fault scenarios.« less

A framework for quantifying and optimizing the value of seismic monitoring of infrastructure

NASA Astrophysics Data System (ADS)

Omenzetter, Piotr

2017-04-01

This paper outlines a framework for quantifying and optimizing the value of information from structural health monitoring (SHM) technology deployed on large infrastructure, which may sustain damage in a series of earthquakes (the main and the aftershocks). The evolution of the damage state of the infrastructure without or with SHM is presented as a time-dependent, stochastic, discrete-state, observable and controllable nonlinear dynamical system. The pre-posterior Bayesian analysis and the decision tree are used for quantifying and optimizing the value of SHM information. An optimality problem is then formulated how to decide on the adoption of SHM and how to manage optimally the usage and operations of the possibly damaged infrastructure and its repair schedule using the information from SHM. The objective function to minimize is the expected total cost or risk.

The Consolidated Planning and Scheduling System for Space Transportation and Space Station operations - Successful development experience

NASA Technical Reports Server (NTRS)

Hornstein, Rhoda S.; Willoughby, John K.; Gardner, Jo A.; Shinkle, Gerald L.

1993-01-01

In 1992, NASA made the decision to evolve a Consolidated Planning System (CPS) by adding the Space Transportation System (STS) requirements to the Space Station Freedom (SSF) planning software. This paper describes this evolutionary process, which began with a series of six-month design-build-test cycles, using a domain-independent architecture and a set of developmental tools known as the Advanced Scheduling Environment. It is shown that, during these tests, the CPS could be used at multiple organizational levels of planning and for integrating schedules from geographically distributed (including international) planning environments. The potential for using the CPS for other planning and scheduling tasks in the SSF program is being currently examined.

Parallel processing of real-time dynamic systems simulation on OSCAR (Optimally SCheduled Advanced multiprocessoR)

NASA Technical Reports Server (NTRS)

Kasahara, Hironori; Honda, Hiroki; Narita, Seinosuke

1989-01-01

Parallel processing of real-time dynamic systems simulation on a multiprocessor system named OSCAR is presented. In the simulation of dynamic systems, generally, the same calculation are repeated every time step. However, we cannot apply to Do-all or the Do-across techniques for parallel processing of the simulation since there exist data dependencies from the end of an iteration to the beginning of the next iteration and furthermore data-input and data-output are required every sampling time period. Therefore, parallelism inside the calculation required for a single time step, or a large basic block which consists of arithmetic assignment statements, must be used. In the proposed method, near fine grain tasks, each of which consists of one or more floating point operations, are generated to extract the parallelism from the calculation and assigned to processors by using optimal static scheduling at compile time in order to reduce large run time overhead caused by the use of near fine grain tasks. The practicality of the scheme is demonstrated on OSCAR (Optimally SCheduled Advanced multiprocessoR) which has been developed to extract advantageous features of static scheduling algorithms to the maximum extent.

Swarm satellite mission scheduling & planning using Hybrid Dynamic Mutation Genetic Algorithm

NASA Astrophysics Data System (ADS)

Zheng, Zixuan; Guo, Jian; Gill, Eberhard

2017-08-01

Space missions have traditionally been controlled by operators from a mission control center. Given the increasing number of satellites for some space missions, generating a command list for multiple satellites can be time-consuming and inefficient. Developing multi-satellite, onboard mission scheduling & planning techniques is, therefore, a key research field for future space mission operations. In this paper, an improved Genetic Algorithm (GA) using a new mutation strategy is proposed as a mission scheduling algorithm. This new mutation strategy, called Hybrid Dynamic Mutation (HDM), combines the advantages of both dynamic mutation strategy and adaptive mutation strategy, overcoming weaknesses such as early convergence and long computing time, which helps standard GA to be more efficient and accurate in dealing with complex missions. HDM-GA shows excellent performance in solving both unconstrained and constrained test functions. The experiments of using HDM-GA to simulate a multi-satellite, mission scheduling problem demonstrates that both the computation time and success rate mission requirements can be met. The results of a comparative test between HDM-GA and three other mutation strategies also show that HDM has outstanding performance in terms of speed and reliability.

Spinning Straw into Gold: How State Education Agencies Can Transform Their Data to Improve Critical School Resource Decisions

ERIC Educational Resources Information Center

Frank, Stephen; Trawick-Smith, Joseph

2014-01-01

K-12 education resources are often allocated non-strategically, with schools spending time and money on activities that have little relationship to student outcomes. Most of these decisions take place within districts, rooted in the processes of setting schedules, staffing levels, and assignments, and creating final budgets. Local Education…

Naval Systems Engineering Guide

DTIC Science & Technology

2004-10-01

Decision Critical Design Review System Integration Activities IOC FRP Decision Review Production & Deployment Sustainment IOT & FOC Sustainmen...reentered when things change significantly, such as funding, requirements, or schedule. This process must start at the very beginning of a Major...outputs through sub-processes will reveal a number of things : a. Determine the level of process applicability and tailoring required. b. Additional

Rescheduling nursing shifts: scoping the challenge and examining the potential of mathematical model based tools.

PubMed

Clark, Alistair; Moule, Pam; Topping, Annie; Serpell, Martin

2015-05-01

To review research in the literature on nursing shift scheduling / rescheduling, and to report key issues identified in a consultation exercise with managers in four English National Health Service trusts to inform the development of mathematical tools for rescheduling decision-making. Shift rescheduling is unrecognised as an everyday time-consuming management task with different imperatives from scheduling. Poor rescheduling decisions can have quality, cost and morale implications. A systematic critical literature review identified rescheduling issues and existing mathematic modelling tools. A consultation exercise with nursing managers examined the complex challenges associated with rescheduling. Minimal research exists on rescheduling compared with scheduling. Poor rescheduling can result in greater disruption to planned nursing shifts and may impact negatively on the quality and cost of patient care, and nurse morale and retention. Very little research examines management challenges or mathematical modelling for rescheduling. Shift rescheduling is a complex and frequent management activity that is more challenging than scheduling. Mathematical modelling may have potential as a tool to support managers to minimise rescheduling disruption. The lack of specific methodological support for rescheduling that takes into account its complexity, increases the likelihood of harm for patients and stress for nursing staff and managers. © 2013 John Wiley & Sons Ltd.

Benefit Opportunities for Integrated Surface and Airspace Departure Scheduling: A Study of Operations at Charlotte-Douglas International Airport

NASA Technical Reports Server (NTRS)

Coppenbarger, Rich; Jung, Yoon; Kozon, Tom; Farrahi, Amir; Malik, Wakar; Lee, Hanbong; Chevalley, Eric; Kistler, Matt

2016-01-01

NASA is collaborating with the FAA and aviation industry to develop and demonstrate new capabilities that integrate arrival, departure, and surface air-traffic operations. The concept relies on trajectory-based departure scheduling and collaborative decision making to reduce delays and uncertainties in taxi and climb operations. The paper describes the concept and benefit mechanisms aimed at improving flight efficiency and predictability while maintaining or improving operational throughput. The potential impact of the technology is studied and discussed through a quantitative analysis of relevant shortfalls at the site identified for initial deployment and demonstration in 2017: Charlotte-Douglas International Airport. Results from trajectory analysis indicate substantial opportunity to reduce taxi delays for both departures and arrivals by metering departures at the gate in a manner that maximizes throughput while adhering to takeoff restrictions due mostly to airspace constraints. Substantial taxi-out delay reduction is shown for flights subject to departure restrictions stemming from traffic flow management initiatives. Opportunities to improve the predictability of taxi, takeoff, and climb operations are examined and their potential impact on airline scheduling decisions and air-traffic forecasting is discussed. In addition, the potential to improve throughput with departure scheduling that maximizes use of available runway and airspace capacity is analyzed.

Dynamic Sensor Networks

DTIC Science & Technology

2004-03-01

turned off. SLEEP Set the timer for 30 seconds before scheduled transmit time, then sleep the processor. WAKE When timer trips, power up the processor...slots where none of its neighbors are schedule to transmit. This allows the sensor nodes to perform a simple power man- agement scheme that puts the...routing This simple case study highlights the following crucial observation: optimal traffic scheduling in energy constrained networks requires future

A short-term operating room surgery scheduling problem integrating multiple nurses roster constraints.

PubMed

Xiang, Wei; Yin, Jiao; Lim, Gino

2015-02-01

Operating room (OR) surgery scheduling determines the individual surgery's operation start time and assigns the required resources to each surgery over a schedule period, considering several constraints related to a complete surgery flow and the multiple resources involved. This task plays a decisive role in providing timely treatments for the patients while balancing hospital resource utilization. The originality of the present study is to integrate the surgery scheduling problem with real-life nurse roster constraints such as their role, specialty, qualification and availability. This article proposes a mathematical model and an ant colony optimization (ACO) approach to efficiently solve such surgery scheduling problems. A modified ACO algorithm with a two-level ant graph model is developed to solve such combinatorial optimization problems because of its computational complexity. The outer ant graph represents surgeries, while the inner graph is a dynamic resource graph. Three types of pheromones, i.e. sequence-related, surgery-related, and resource-related pheromone, fitting for a two-level model are defined. The iteration-best and feasible update strategy and local pheromone update rules are adopted to emphasize the information related to the good solution in makespan, and the balanced utilization of resources as well. The performance of the proposed ACO algorithm is then evaluated using the test cases from (1) the published literature data with complete nurse roster constraints, and 2) the real data collected from a hospital in China. The scheduling results using the proposed ACO approach are compared with the test case from both the literature and the real life hospital scheduling. Comparison results with the literature shows that the proposed ACO approach has (1) an 1.5-h reduction in end time; (2) a reduction in variation of resources' working time, i.e. 25% for ORs, 50% for nurses in shift 1 and 86% for nurses in shift 2; (3) an 0.25h reduction in individual maximum overtime (OT); and (4) an 42% reduction in the total OT of nurses. Comparison results with the real 10-workday hospital scheduling further show the advantage of the ACO in several measurements. Instead of assigning all surgeries by a surgeon to only one OR and the same nurses by traditional manual approach in hospital, ACO realizes a more balanced surgery arrangement by assigning the surgeries to different ORs and nurses. It eventually leads to shortening the end time within the confidential interval of [7.4%, 24.6%] with 95% confidence level. The ACO approach proposed in this paper efficiently solves the surgery scheduling problem with daily nurse roster while providing a shortened end time and relatively balanced resource allocations. It also supports the advantage of integrating the surgery scheduling with the nurse scheduling and the efficiency of systematic optimization considering a complete three-stage surgery flow and resources involved. Copyright © 2014 Elsevier B.V. All rights reserved.

Scheduling Future Water Supply Investments Under Uncertainty

NASA Astrophysics Data System (ADS)

Huskova, I.; Matrosov, E. S.; Harou, J. J.; Kasprzyk, J. R.; Reed, P. M.

2014-12-01

Uncertain hydrological impacts of climate change, population growth and institutional changes pose a major challenge to planning of water supply systems. Planners seek optimal portfolios of supply and demand management schemes but also when to activate assets whilst considering many system goals and plausible futures. Incorporation of scheduling into the planning under uncertainty problem strongly increases its complexity. We investigate some approaches to scheduling with many-objective heuristic search. We apply a multi-scenario many-objective scheduling approach to the Thames River basin water supply system planning problem in the UK. Decisions include which new supply and demand schemes to implement, at what capacity and when. The impact of different system uncertainties on scheme implementation schedules are explored, i.e. how the choice of future scenarios affects the search process and its outcomes. The activation of schemes is influenced by the occurrence of extreme hydrological events in the ensemble of plausible scenarios and other factors. The approach and results are compared with a previous study where only the portfolio problem is addressed (without scheduling).

A System for Planning Ahead

NASA Technical Reports Server (NTRS)

2002-01-01

A software system that uses artificial intelligence techniques to help with complex Space Shuttle scheduling at Kennedy Space Center is commercially available. Stottler Henke Associates, Inc.(SHAI), is marketing its automatic scheduling system, the Automated Manifest Planner (AMP), to industries that must plan and project changes many different times before the tasks are executed. The system creates optimal schedules while reducing manpower costs. Using information entered into the system by expert planners, the system automatically makes scheduling decisions based upon resource limitations and other constraints. It provides a constraint authoring system for adding other constraints to the scheduling process as needed. AMP is adaptable to assist with a variety of complex scheduling problems in manufacturing, transportation, business, architecture, and construction. AMP can benefit vehicle assembly plants, batch processing plants, semiconductor manufacturing, printing and textiles, surface and underground mining operations, and maintenance shops. For most of SHAI's commercial sales, the company obtains a service contract to customize AMP to a specific domain and then issues the customer a user license.

Decision theory for computing variable and value ordering decisions for scheduling problems

NASA Technical Reports Server (NTRS)

Linden, Theodore A.

1993-01-01

Heuristics that guide search are critical when solving large planning and scheduling problems, but most variable and value ordering heuristics are sensitive to only one feature of the search state. One wants to combine evidence from all features of the search state into a subjective probability that a value choice is best, but there has been no solid semantics for merging evidence when it is conceived in these terms. Instead, variable and value ordering decisions should be viewed as problems in decision theory. This led to two key insights: (1) The fundamental concept that allows heuristic evidence to be merged is the net incremental utility that will be achieved by assigning a value to a variable. Probability distributions about net incremental utility can merge evidence from the utility function, binary constraints, resource constraints, and other problem features. The subjective probability that a value is the best choice is then derived from probability distributions about net incremental utility. (2) The methods used for rumor control in Bayesian Networks are the primary way to prevent cycling in the computation of probable net incremental utility. These insights lead to semantically justifiable ways to compute heuristic variable and value ordering decisions that merge evidence from all available features of the search state.

Determinants of parents' decisions on childhood immunisations at Kumasi Metropolis in Ghana.

PubMed

Hagan, Doris; Phethlu, Deliwe R

2016-07-29

To describe factors that influence parents' decisions on childhood immunisations at Kumasi Metropolis in Ghana. Quantitative cross-sectional survey. A sample of 303 parents was obtained from a monthly accessible population of 1420 individuals from the five district hospitals through convenience sampling of respondents at immunisation sessions in Kumasi. Data obtained from the survey were analysed with SPSS version 21 software. Most parents were aware of child immunisations, but they had limited knowledge on vaccines and immunisation schedules. Antenatal nurses constituted the most accessible source of vaccine information. The study established a high percentage of complete immunisation, influenced by parents' fear of their children contracting vaccine-preventable diseases. Remarkably, some parents indicated that they immunised their children because they wanted to know the weight of their children. Forgetfulness and lack of personnel or vaccine at the centres were the reasons given by the few parents who could not complete immunisation schedules for their children, whereas the socio-demographic variables considered did not influence parents' decision on immunisation. Knowledge on immunisation could not influence immunisation decisions but parents' fear of vaccine-preventable diseases, awareness on the benefits of immunisations and sources of vaccine information were the main factors that influenced immunisation decision at Kumasi in Ghana.

Market-Based Approaches to Managing Science Return from Planetary Missions

NASA Technical Reports Server (NTRS)

Wessen, Randii R.; Porter, David; Hanson, Robin

1996-01-01

A research plan is described for the design and testing of a method for the planning and negotiation of science observations. The research plan is presented in relation to the fact that the current method, which involves a hierarchical process of science working groups, is unsuitable for the planning of the Cassini mission. The research plan involves the market-based approach in which participants are allocated budgets of scheduling points. The points are used to provide an intensity of preference for the observations being scheduled. In this way, the schedulers do not have to limit themselves to solving major conflicts, but try to maximize the number of scheduling points that result in a conflict-free timeline. Incentives are provided for the participants by the fixed budget concerning their tradeoff decisions. A degree of feedback is provided in the process so that the schedulers may rebid based on the current timeline.

Knowledge-Based Scheduling of Arrival Aircraft in the Terminal Area

NASA Technical Reports Server (NTRS)

Krzeczowski, K. J.; Davis, T.; Erzberger, H.; Lev-Ram, Israel; Bergh, Christopher P.

1995-01-01

A knowledge based method for scheduling arrival aircraft in the terminal area has been implemented and tested in real time simulation. The scheduling system automatically sequences, assigns landing times, and assign runways to arrival aircraft by utilizing continuous updates of aircraft radar data and controller inputs. The scheduling algorithm is driven by a knowledge base which was obtained in over two thousand hours of controller-in-the-loop real time simulation. The knowledge base contains a series of hierarchical 'rules' and decision logic that examines both performance criteria, such as delay reductions, as well as workload reduction criteria, such as conflict avoidance. The objective of the algorithm is to devise an efficient plan to land the aircraft in a manner acceptable to the air traffic controllers. This paper describes the scheduling algorithms, gives examples of their use, and presents data regarding their potential benefits to the air traffic system.

Knowledge-based scheduling of arrival aircraft

NASA Technical Reports Server (NTRS)

Krzeczowski, K.; Davis, T.; Erzberger, H.; Lev-Ram, I.; Bergh, C.

1995-01-01

A knowledge-based method for scheduling arrival aircraft in the terminal area has been implemented and tested in real-time simulation. The scheduling system automatically sequences, assigns landing times, and assigns runways to arrival aircraft by utilizing continuous updates of aircraft radar data and controller inputs. The scheduling algorithms is driven by a knowledge base which was obtained in over two thousand hours of controller-in-the-loop real-time simulation. The knowledge base contains a series of hierarchical 'rules' and decision logic that examines both performance criteria, such as delay reduction, as well as workload reduction criteria, such as conflict avoidance. The objective of the algorithms is to devise an efficient plan to land the aircraft in a manner acceptable to the air traffic controllers. This paper will describe the scheduling algorithms, give examples of their use, and present data regarding their potential benefits to the air traffic system.

A dynamic case-based planning system for space station application

NASA Technical Reports Server (NTRS)

Oppacher, F.; Deugo, D.

1988-01-01

We are currently investigating the use of a case-based reasoning approach to develop a dynamic planning system. The dynamic planning system (DPS) is designed to perform resource management, i.e., to efficiently schedule tasks both with and without failed components. This approach deviates from related work on scheduling and on planning in AI in several aspects. In particular, an attempt is made to equip the planner with an ability to cope with a changing environment by dynamic replanning, to handle resource constraints and feedback, and to achieve some robustness and autonomy through plan learning by dynamic memory techniques. We briefly describe the proposed architecture of DPS and its four major components: the PLANNER, the plan EXECUTOR, the dynamic REPLANNER, and the plan EVALUATOR. The planner, which is implemented in Smalltalk, is being evaluated for use in connection with the Space Station Mobile Service System (MSS).

The Utility of Impulsive Bias and Altered Decision Making as Predictors of Drug Efficacy and Target Selection: Rethinking Behavioral Screening for Antidepressant Drugs.

PubMed

Marek, Gerard J; Day, Mark; Hudzik, Thomas J

2016-03-01

Cognitive dysfunction may be a core feature of major depressive disorder, including affective processing bias, abnormal response to negative feedback, changes in decision making, and increased impulsivity. Accordingly, a translational medicine paradigm predicts clinical action of novel antidepressants by examining drug-induced changes in affective processing bias. With some exceptions, these concepts have not been systematically applied to preclinical models to test new chemical entities. The purpose of this review is to examine whether an empirically derived behavioral screen for antidepressant drugs may screen for compounds, at least in part, by modulating an impulsive biasing of responding and altered decision making. The differential-reinforcement-of-low-rate (DRL) 72-second schedule is an operant schedule with a documented fidelity for discriminating antidepressant drugs from nonantidepressant drugs. However, a theoretical basis for this empirical relationship has been lacking. Therefore, this review will discuss whether response bias toward impulsive behavior may be a critical screening characteristic of DRL behavior requiring long inter-response times to obtain rewards. This review will compare and contrast DRL behavior with the five-choice serial reaction time task, a test specifically designed for assessing motoric impulsivity, with respect to psychopharmacological testing and the neural basis of distributed macrocircuits underlying these tasks. This comparison suggests that the existing empirical basis for the DRL 72-second schedule as a pharmacological screen for antidepressant drugs is complemented by a novel hypothesis that altering impulsive response bias for rodents trained on this operant schedule is a previously unrecognized theoretical cornerstone for this screening paradigm. Copyright © 2016 by The American Society for Pharmacology and Experimental Therapeutics.

The training schedule affects the stability, not the magnitude, of the interlimb transfer of learned dynamics

PubMed Central

Joiner, Wilsaan M.; Brayanov, Jordan B.

2013-01-01

The way that a motor adaptation is trained, for example, the manner in which it is introduced or the duration of the training period, can influence its internal representation. However, recent studies examining the gradual versus abrupt introduction of a novel environment have produced conflicting results. Here we examined how these effects determine the effector specificity of motor adaptation during visually guided reaching. After adaptation to velocity-dependent dynamics in the right arm, we estimated the amount of adaptation transferred to the left arm, using error-clamp measurement trials to directly measure changes in learned dynamics. We found that a small but significant amount of generalization to the untrained arm occurs under three different training schedules: a short-duration (15 trials) abrupt presentation, a long-duration (160 trials) abrupt presentation, and a long-duration gradual presentation of the novel dynamic environment. Remarkably, we found essentially no difference between the amount of interlimb generalization when comparing these schedules, with 9–12% transfer of the trained adaptation for all three. However, the duration of training had a pronounced effect on the stability of the interlimb transfer: The transfer elicited from short-duration training decayed rapidly, whereas the transfer from both long-duration training schedules was considerably more persistent (<50% vs. >90% retention over the first 20 trials). These results indicate that the amount of interlimb transfer is similar for gradual versus abrupt training and that interlimb transfer of learned dynamics can occur after even a brief training period but longer training is required for an enduring effect. PMID:23719204

The training schedule affects the stability, not the magnitude, of the interlimb transfer of learned dynamics.

PubMed

Joiner, Wilsaan M; Brayanov, Jordan B; Smith, Maurice A

2013-08-01

The way that a motor adaptation is trained, for example, the manner in which it is introduced or the duration of the training period, can influence its internal representation. However, recent studies examining the gradual versus abrupt introduction of a novel environment have produced conflicting results. Here we examined how these effects determine the effector specificity of motor adaptation during visually guided reaching. After adaptation to velocity-dependent dynamics in the right arm, we estimated the amount of adaptation transferred to the left arm, using error-clamp measurement trials to directly measure changes in learned dynamics. We found that a small but significant amount of generalization to the untrained arm occurs under three different training schedules: a short-duration (15 trials) abrupt presentation, a long-duration (160 trials) abrupt presentation, and a long-duration gradual presentation of the novel dynamic environment. Remarkably, we found essentially no difference between the amount of interlimb generalization when comparing these schedules, with 9-12% transfer of the trained adaptation for all three. However, the duration of training had a pronounced effect on the stability of the interlimb transfer: The transfer elicited from short-duration training decayed rapidly, whereas the transfer from both long-duration training schedules was considerably more persistent (<50% vs. >90% retention over the first 20 trials). These results indicate that the amount of interlimb transfer is similar for gradual versus abrupt training and that interlimb transfer of learned dynamics can occur after even a brief training period but longer training is required for an enduring effect.

The GBT Dynamic Scheduling System: Powered by the Web

NASA Astrophysics Data System (ADS)

Marganian, P.; Clark, M.; McCarty, M.; Sessoms, E.; Shelton, A.

2009-09-01

The web technologies utilized for the Robert C. Byrd Green Bank Telescope's (GBT) new Dynamic Scheduling System are discussed, focusing on languages, frameworks, and tools. We use a popular Python web framework, TurboGears, to take advantage of the extensive web services the system provides. TurboGears is a model-view-controller framework, which aggregates SQLAlchemy, Genshi, and CherryPy respectively. On top of this framework, Javascript (Prototype, script.aculo.us, and JQuery) and cascading style sheets (Blueprint) are used for desktop-quality web pages.

Automation of orbit determination functions for National Aeronautics and Space Administration (NASA)-supported satellite missions

NASA Technical Reports Server (NTRS)

Mardirossian, H.; Beri, A. C.; Doll, C. E.

1990-01-01

The Flight Dynamics Facility (FDF) at Goddard Space Flight Center (GSFC) provides spacecraft trajectory determination for a wide variety of National Aeronautics and Space Administration (NASA)-supported satellite missions, using the Tracking Data Relay Satellite System (TDRSS) and Ground Spaceflight and Tracking Data Network (GSTDN). To take advantage of computerized decision making processes that can be used in spacecraft navigation, the Orbit Determination Automation System (ODAS) was designed, developed, and implemented as a prototype system to automate orbit determination (OD) and orbit quality assurance (QA) functions performed by orbit operations. Based on a machine-resident generic schedule and predetermined mission-dependent QA criteria, ODAS autonomously activates an interface with the existing trajectory determination system using a batch least-squares differential correction algorithm to perform the basic OD functions. The computational parameters determined during the OD are processed to make computerized decisions regarding QA, and a controlled recovery process is activated when the criteria are not satisfied. The complete cycle is autonomous and continuous. ODAS was extensively tested for performance under conditions resembling actual operational conditions and found to be effective and reliable for extended autonomous OD. Details of the system structure and function are discussed, and test results are presented.

Automation of orbit determination functions for National Aeronautics and Space Administration (NASA)-supported satellite missions

NASA Technical Reports Server (NTRS)

Mardirossian, H.; Heuerman, K.; Beri, A.; Samii, M. V.; Doll, C. E.

1989-01-01

The Flight Dynamics Facility (FDF) at Goddard Space Flight Center (GSFC) provides spacecraft trajectory determination for a wide variety of National Aeronautics and Space Administration (NASA)-supported satellite missions, using the Tracking Data Relay Satellite System (TDRSS) and Ground Spaceflight and Tracking Data Network (GSTDN). To take advantage of computerized decision making processes that can be used in spacecraft navigation, the Orbit Determination Automation System (ODAS) was designed, developed, and implemented as a prototype system to automate orbit determination (OD) and orbit quality assurance (QA) functions performed by orbit operations. Based on a machine-resident generic schedule and predetermined mission-dependent QA criteria, ODAS autonomously activates an interface with the existing trajectory determination system using a batch least-squares differential correction algorithm to perform the basic OD functions. The computational parameters determined during the OD are processed to make computerized decisions regarding QA, and a controlled recovery process isactivated when the criteria are not satisfied. The complete cycle is autonomous and continuous. ODAS was extensively tested for performance under conditions resembling actual operational conditions and found to be effective and reliable for extended autonomous OD. Details of the system structure and function are discussed, and test results are presented.

The application of system dynamics modelling to environmental health decision-making and policy - a scoping review.

PubMed

Currie, Danielle J; Smith, Carl; Jagals, Paul

2018-03-27

Policy and decision-making processes are routinely challenged by the complex and dynamic nature of environmental health problems. System dynamics modelling has demonstrated considerable value across a number of different fields to help decision-makers understand and predict the dynamic behaviour of complex systems in support the development of effective policy actions. In this scoping review we investigate if, and in what contexts, system dynamics modelling is being used to inform policy or decision-making processes related to environmental health. Four electronic databases and the grey literature were systematically searched to identify studies that intersect the areas environmental health, system dynamics modelling, and decision-making. Studies identified in the initial screening were further screened for their contextual, methodological and application-related relevancy. Studies deemed 'relevant' or 'highly relevant' according to all three criteria were included in this review. Key themes related to the rationale, impact and limitation of using system dynamics in the context of environmental health decision-making and policy were analysed. We identified a limited number of relevant studies (n = 15), two-thirds of which were conducted between 2011 and 2016. The majority of applications occurred in non-health related sectors (n = 9) including transportation, public utilities, water, housing, food, agriculture, and urban and regional planning. Applications were primarily targeted at micro-level (local, community or grassroots) decision-making processes (n = 9), with macro-level (national or international) decision-making to a lesser degree. There was significant heterogeneity in the stated rationales for using system dynamics and the intended impact of the system dynamics model on decision-making processes. A series of user-related, technical and application-related limitations and challenges were identified. None of the reported limitations or challenges appeared unique to the application of system dynamics within the context of environmental health problems, but rather to the use of system dynamics in general. This review reveals that while system dynamics modelling is increasingly being used to inform decision-making related to environmental health, applications are currently limited. Greater application of system dynamics within this context is needed before its benefits and limitations can be fully understood.

A comparison of multiprocessor scheduling methods for iterative data flow architectures

NASA Technical Reports Server (NTRS)

Storch, Matthew

1993-01-01

A comparative study is made between the Algorithm to Architecture Mapping Model (ATAMM) and three other related multiprocessing models from the published literature. The primary focus of all four models is the non-preemptive scheduling of large-grain iterative data flow graphs as required in real-time systems, control applications, signal processing, and pipelined computations. Important characteristics of the models such as injection control, dynamic assignment, multiple node instantiations, static optimum unfolding, range-chart guided scheduling, and mathematical optimization are identified. The models from the literature are compared with the ATAMM for performance, scheduling methods, memory requirements, and complexity of scheduling and design procedures.

7 CFR 275.4 - Record retention.

Code of Federal Regulations, 2010 CFR

2010-01-01

... Stamps and Medicaid Quality Control Reviews, FNS-380-1, Integrated Review Schedule, FNS-245, Negative... materials supporting the review decision; sample lists; sampling frames; tabulation sheets; and reports of...

Dynamics of individual perceptual decisions

PubMed Central

Clark, Torin K.; Lu, Yue M.; Karmali, Faisal

2015-01-01

Perceptual decision making is fundamental to a broad range of fields including neurophysiology, economics, medicine, advertising, law, etc. Although recent findings have yielded major advances in our understanding of perceptual decision making, decision making as a function of time and frequency (i.e., decision-making dynamics) is not well understood. To limit the review length, we focus most of this review on human findings. Animal findings, which are extensively reviewed elsewhere, are included when beneficial or necessary. We attempt to put these various findings and data sets, which can appear to be unrelated in the absence of a formal dynamic analysis, into context using published models. Specifically, by adding appropriate dynamic mechanisms (e.g., high-pass filters) to existing models, it appears that a number of otherwise seemingly disparate findings from the literature might be explained. One hypothesis that arises through this dynamic analysis is that decision making includes phasic (high pass) neural mechanisms, an evidence accumulator and/or some sort of midtrial decision-making mechanism (e.g., peak detector and/or decision boundary). PMID:26467513

Working-Memory Load and Temporal Myopia in Dynamic Decision Making

ERIC Educational Resources Information Center

Worthy, Darrell A.; Otto, A. Ross; Maddox, W. Todd

2012-01-01

We examined the role of working memory (WM) in dynamic decision making by having participants perform decision-making tasks under single-task or dual-task conditions. In 2 experiments participants performed dynamic decision-making tasks in which they chose 1 of 2 options on each trial. The decreasing option always gave a larger immediate reward…

Dynamic Decision Making under Uncertainty and Partial Information

DTIC Science & Technology

2017-01-30

order to address these problems, we investigated efficient computational methodologies for dynamic decision making under uncertainty and partial...information. In the course of this research, we developed and studied efficient simulation-based methodologies for dynamic decision making under...uncertainty and partial information; (ii) studied the application of these decision making models and methodologies to practical problems, such as those

Landslide: Systematic Dynamic Race Detection in Kernel Space

DTIC Science & Technology

2012-05-01

schedule_in_flight← true; CAUSE_TIMER_INTERRUPT(); end if end function Thread Scheduling Finally, the Landslide scheduler is responsible for managing ...child process vanish() simultaneously. • double_wait: Tests interactions of multiple waiters on a single child. • double_thread_fork: Tests for...conditions using Landslide. We describe them here. • Too many waiters allowed. Using the double_wait test case, Group 1 found a bug in which more threads

Defense Science Board Task Force Report: The Role of Autonomy in DoD Systems

DTIC Science & Technology

2012-07-01

ASD(R&E) and the Military Services should schedule periodic, on-site collaborations that bring together academia, government and not-for-profit labs...expressing UxV activities, increased problem solving, planning and scheduling capabilities to enable dynamic tasking of distributed UxVs and tools for...industrial, governmental and military. Manufacturing has long exploited planning for logistics and matching product demand to production schedules

Empirical results on scheduling and dynamic backtracking

NASA Technical Reports Server (NTRS)

Boddy, Mark S.; Goldman, Robert P.

1994-01-01

At the Honeywell Technology Center (HTC), we have been working on a scheduling problem related to commercial avionics. This application is large, complex, and hard to solve. To be a little more concrete: 'large' means almost 20,000 activities, 'complex' means several activity types, periodic behavior, and assorted types of temporal constraints, and 'hard to solve' means that we have been unable to eliminate backtracking through the use of search heuristics. At this point, we can generate solutions, where solutions exist, or report failure and sometimes why the system failed. To the best of our knowledge, this is among the largest and most complex scheduling problems to have been solved as a constraint satisfaction problem, at least that has appeared in the published literature. This abstract is a preliminary report on what we have done and how. In the next section, we present our approach to treating scheduling as a constraint satisfaction problem. The following sections present the application in more detail and describe how we solve scheduling problems in the application domain. The implemented system makes use of Ginsberg's Dynamic Backtracking algorithm, with some minor extensions to improve its utility for scheduling. We describe those extensions and the performance of the resulting system. The paper concludes with some general remarks, open questions and plans for future work.

Intelligent Scheduling for Underground Mobile Mining Equipment

PubMed Central

Song, Zhen; Schunnesson, Håkan; Rinne, Mikael; Sturgul, John

2015-01-01

Many studies have been carried out and many commercial software applications have been developed to improve the performances of surface mining operations, especially for the loader-trucks cycle of surface mining. However, there have been quite few studies aiming to improve the mining process of underground mines. In underground mines, mobile mining equipment is mostly scheduled instinctively, without theoretical support for these decisions. Furthermore, in case of unexpected events, it is hard for miners to rapidly find solutions to reschedule and to adapt the changes. This investigation first introduces the motivation, the technical background, and then the objective of the study. A decision support instrument (i.e. schedule optimizer for mobile mining equipment) is proposed and described to address this issue. The method and related algorithms which are used in this instrument are presented and discussed. The proposed method was tested by using a real case of Kittilä mine located in Finland. The result suggests that the proposed method can considerably improve the working efficiency and reduce the working time of the underground mine. PMID:26098934

Strategic Retirement Reform: Identifying the Broader Strategic Effects from Changes in Human Capital

DTIC Science & Technology

2012-12-01

service and what factors influence their decisions?  What are the potential implications from adopting a defined contribution military retirement system...that best accommodated their personal schedules. After initial sign up , the focus groups were organized and conducted. Focus groups were scheduled to...positive or negative shock, or some other factor , compels a person to “evaluate against (a) a preexisting plan of action; (b) the individual’s values

Designing an Interactive Local and Global Decision Support System for Aircraft Carrier Deck Scheduling

DTIC Science & Technology

2011-03-01

These two elements again address the local and global perspectives of functionality. Upon schedule request, the Variable Ranking Tool ( VRT ) in...Figure 1 enlarges, moves to the interior of the screen, and becomes actionable (Figure 5 provides an enlarged view of the VRT , Figure 6 shows how the...full display is rearranged). The VRT addresses global properties through the handling of groups of entities in the system. Globally, functional

Scheduling multicore workload on shared multipurpose clusters

NASA Astrophysics Data System (ADS)

Templon, J. A.; Acosta-Silva, C.; Flix Molina, J.; Forti, A. C.; Pérez-Calero Yzquierdo, A.; Starink, R.

2015-12-01

With the advent of workloads containing explicit requests for multiple cores in a single grid job, grid sites faced a new set of challenges in workload scheduling. The most common batch schedulers deployed at HEP computing sites do a poor job at multicore scheduling when using only the native capabilities of those schedulers. This paper describes how efficient multicore scheduling was achieved at the sites the authors represent, by implementing dynamically-sized multicore partitions via a minimalistic addition to the Torque/Maui batch system already in use at those sites. The paper further includes example results from use of the system in production, as well as measurements on the dependence of performance (especially the ramp-up in throughput for multicore jobs) on node size and job size.

Defense Acquisitions: Future Aerostat and Airship Investment Decisions Drive Oversight and Coordination Needs

DTIC Science & Technology

2012-10-01

earlier, LEMV experienced schedule delays of at least 10 months, largely rooted in technical, design, and engineering problems in scaling up the airship ...had informal coordination with the Blue Devil Block 2 effort in the past. For example, originally both airships had several diesel engine ...DEFENSE ACQUISITIONS Future Aerostat and Airship Investment Decisions Drive Oversight and Coordination Needs

76 FR 36515 - Rangeland Allotment Management Planning on the Fall River and Oglala Geographic Areas, Pine Ridge...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-06-22

... full environmental analysis and decision-making process that will occur on the proposal so interested and affected people may become aware of how they may participate in the process and contribute to the... issued to update the project schedule. There will be a record of decision (ROD) for each geographic area...

Automated control of hierarchical systems using value-driven methods

NASA Technical Reports Server (NTRS)

Pugh, George E.; Burke, Thomas E.

1990-01-01

An introduction is given to the Value-driven methodology, which has been successfully applied to solve a variety of difficult decision, control, and optimization problems. Many real-world decision processes (e.g., those encountered in scheduling, allocation, and command and control) involve a hierarchy of complex planning considerations. For such problems it is virtually impossible to define a fixed set of rules that will operate satisfactorily over the full range of probable contingencies. Decision Science Applications' value-driven methodology offers a systematic way of automating the intuitive, common-sense approach used by human planners. The inherent responsiveness of value-driven systems to user-controlled priorities makes them particularly suitable for semi-automated applications in which the user must remain in command of the systems operation. Three examples of the practical application of the approach in the automation of hierarchical decision processes are discussed: the TAC Brawler air-to-air combat simulation is a four-level computerized hierarchy; the autonomous underwater vehicle mission planning system is a three-level control system; and the Space Station Freedom electrical power control and scheduling system is designed as a two-level hierarchy. The methodology is compared with rule-based systems and with other more widely-known optimization techniques.

Strategic behavior, workload, and performance in task scheduling

NASA Technical Reports Server (NTRS)

Moray, Neville; Dessouky, Mohamed I.; Kijowski, Brian A.; Adapathya, Ravi

1991-01-01

Scheduling theory is proposed as a normative model for strategic behavior when operators are confronted by several tasks, all of which should be completed within a fixed time span, and when they are free to choose the order in which the tasks should be done. Three experiments are described to investigate the effect of knowing the correct scheduling rule on the efficiency of performance, subjective workload, and choice of strategy under different conditions of time pressure. The most potent effects are from time pressure. The reasons for the weak effect of knowing the rules are discussed, and implications for strategic behavior, displays, and decision aids are indicated.

E3 Charter Template

EPA Pesticide Factsheets

This is a charter template which includes decisions made during the project planning phase, as well as local project goals, a communication strategy, an outreach strategy, distribution of responsibilities and a schedule.

Automated power management and control

NASA Technical Reports Server (NTRS)

Dolce, James L.

1991-01-01

A comprehensive automation design is being developed for Space Station Freedom's electric power system. A joint effort between NASA's Office of Aeronautics and Exploration Technology and NASA's Office of Space Station Freedom, it strives to increase station productivity by applying expert systems and conventional algorithms to automate power system operation. The initial station operation will use ground-based dispatches to perform the necessary command and control tasks. These tasks constitute planning and decision-making activities that strive to eliminate unplanned outages. We perceive an opportunity to help these dispatchers make fast and consistent on-line decisions by automating three key tasks: failure detection and diagnosis, resource scheduling, and security analysis. Expert systems will be used for the diagnostics and for the security analysis; conventional algorithms will be used for the resource scheduling.

ROBUS-2: A Fault-Tolerant Broadcast Communication System

NASA Technical Reports Server (NTRS)

Torres-Pomales, Wilfredo; Malekpour, Mahyar R.; Miner, Paul S.

2005-01-01

The Reliable Optical Bus (ROBUS) is the core communication system of the Scalable Processor-Independent Design for Enhanced Reliability (SPIDER), a general-purpose fault-tolerant integrated modular architecture currently under development at NASA Langley Research Center. The ROBUS is a time-division multiple access (TDMA) broadcast communication system with medium access control by means of time-indexed communication schedule. ROBUS-2 is a developmental version of the ROBUS providing guaranteed fault-tolerant services to the attached processing elements (PEs), in the presence of a bounded number of faults. These services include message broadcast (Byzantine Agreement), dynamic communication schedule update, clock synchronization, and distributed diagnosis (group membership). The ROBUS also features fault-tolerant startup and restart capabilities. ROBUS-2 is tolerant to internal as well as PE faults, and incorporates a dynamic self-reconfiguration capability driven by the internal diagnostic system. This version of the ROBUS is intended for laboratory experimentation and demonstrations of the capability to reintegrate failed nodes, dynamically update the communication schedule, and tolerate and recover from correlated transient faults.

Collaborative Arrival Planning: Data Sharing and User Preference Tools

NASA Technical Reports Server (NTRS)

Zelenka, Richard E.; Edwards, Thomas A. (Technical Monitor)

1998-01-01

Air traffic growth and air carrier economic pressures have motivated efforts to increase the flexibility of the air traffic management process and change the relationship between the air traffic control service provider and the system user. One of the most visible of these efforts is the U.S. government/industry "free flight" initiative, in which the service provider concentrates on safety and cross-airline fairness, and the user on their business objectives and operating preferences, including selecting their own path and speed in real-time. In the terminal arrival phase of flight, severe restrictions and rigid control are currently placed on system users, typically without regard for individual user operational preferences. Airborne delays applied to arriving aircraft into capacity constrained airports are imposed on a first-come, first-serve basis, and thus do not allow the system user to plan for or prioritize late arrivals, or to economically optimize their arrival sequence. A central tenant of the free-flight operating paradigm is collaboration between service providers and users in reaching air traffic management decisions. Such collaboration would be particularly beneficial to an airline's "hub" operation, where off-schedule arrival aircraft are a consistent problem, as they cause serious air-port ramp difficulties, rippling airline scheduling effects, and result in large economic inefficiencies. Greater collaboration can also lead to increased airport capacity and decrease the severity of over-capacity rush periods. In the NASA Collaborative Arrival Planning (CAP) project, both independent exchange of real-time data between the service provider and system user and collaborative decision support tools are addressed. Data exchange of real-time arrival scheduling, airspace management, and air carrier fleet data between the FAA service provider and an air carrier is being conducted and evaluated. Collaborative arrival decision support tools to allow intra-airline arrival preferences are being developed and simulated. The CAP project is part of and leveraged from the NASA/FAA Center TRACON Automation System (CTAS), a fielded set of decision support tools that provide computer generated advisories for both enroute and terminal area controllers to manage and control arrival traffic more efficiently. In this paper, the NASA Collaborative Arrival Planning project is outlined and recent results detailed, including the real-time use of CTAS arrival scheduling data by a major air carrier and simulations of tactical and strategic user preference decision support tools.

Scheduling rules to achieve lead-time targets in outpatient appointment systems.

PubMed

Nguyen, Thu-Ba T; Sivakumar, Appa Iyer; Graves, Stephen C

2017-12-01

This paper considers how to schedule appointments for outpatients, for a clinic that is subject to appointment lead-time targets for both new and returning patients. We develop heuristic rules, which are the exact and relaxed appointment scheduling rules, to schedule each new patient appointment (only) in light of uncertainty about future arrivals. The scheduling rules entail two decisions. First, the rules need to determine whether or not a patient's request can be accepted; then, if the request is not rejected, the rules prescribe how to assign the patient to an available slot. The intent of the scheduling rules is to maximize the utilization of the planned resource (i.e., the physician staff), or equivalently to maximize the number of patients that are admitted, while maintaining the service targets on the median, the 95th percentile, and the maximum appointment lead-times. We test the proposed scheduling rules with numerical experiments using real data from the chosen clinic of Tan Tock Seng hospital in Singapore. The results show the efficiency and the efficacy of the scheduling rules, in terms of the service-target satisfaction and the resource utilization. From the sensitivity analysis, we find that the performance of the proposed scheduling rules is fairly robust to the specification of the established lead-time targets.

E-mail as the Appropriate Method of Communication for the Decision-Maker When Soliciting Advice for an Intellective Decision Task.

PubMed

Prahl, Andrew; Dexter, Franklin; Swol, Lyn Van; Braun, Michael T; Epstein, Richard H

2015-09-01

For many problems in operating room and anesthesia group management, there are tasks with optimal decisions, and yet experienced personnel tend to make decisions that are worse or no better than random chance. Such decisions include staff scheduling, case scheduling, moving cases among operating rooms, and choosing patient arrival times. In such settings, operating room management leadership decision-making should typically be autocratic rather than participative. Autocratic-style decision-making calls for managers to solicit and consider feedback from stakeholders in the decision outcome but to make the decision themselves using their expert knowledge and the facts received. For this to be effective, often the manager will obtain expert advice from outside the organization (e.g., health system). In this narrative review, we evaluate the advantages and disadvantages of using prompt asynchronous written communication (i.e., e-mail) as a communication channel for such interaction between a decision-maker (manager) and advisor. A detailed Appendix (Supplemental Digital Content, http://links.lww.com/AA/B72) lists each observational and experimental result. We find that the current ubiquitous role of e-mail for such communication is appropriate. Its benefits include improved time management via asynchronicity, low cognitive load (e.g., relative to Web conferencing), the ability to hide undesirable and irrelevant cues (e.g., physical appearance), the appropriateness of adding desirable cues (e.g., titles and degrees), the opportunity to provide written expression of confidence, and the ability for the advisor to demonstrate the answer for the decision-maker. Given that the manager is e-mailing an advisor whose competence the manager trusts, it is unnecessary to use a richer communication channel to develop trust. Finally, many of the limitations of e-mail can be rectified through training. We expect that decades from now, e-mail (i.e., asynchronous writing) between an expert and decision-maker will remain the dominant means of communication for intellective tasks.

Hard real-time beam scheduler enables adaptive images in multi-probe systems

NASA Astrophysics Data System (ADS)

Tobias, Richard J.

2014-03-01

Real-time embedded-system concepts were adapted to allow an imaging system to responsively control the firing of multiple probes. Large-volume, operator-independent (LVOI) imaging would increase the diagnostic utility of ultrasound. An obstacle to this innovation is the inability of current systems to drive multiple transducers dynamically. Commercial systems schedule scanning with static lists of beams to be fired and processed; here we allow an imager to adapt to changing beam schedule demands, as an intelligent response to incoming image data. An example of scheduling changes is demonstrated with a flexible duplex mode two-transducer application mimicking LVOI imaging. Embedded-system concepts allow an imager to responsively control the firing of multiple probes. Operating systems use powerful dynamic scheduling algorithms, such as fixed priority preemptive scheduling. Even real-time operating systems lack the timing constraints required for ultrasound. Particularly for Doppler modes, events must be scheduled with sub-nanosecond precision, and acquired data is useless without this requirement. A successful scheduler needs unique characteristics. To get close to what would be needed in LVOI imaging, we show two transducers scanning different parts of a subjects leg. When one transducer notices flow in a region where their scans overlap, the system reschedules the other transducer to start flow mode and alter its beams to get a view of the observed vessel and produce a flow measurement. The second transducer does this in a focused region only. This demonstrates key attributes of a successful LVOI system, such as robustness against obstructions and adaptive self-correction.

Tethered satellite system dynamics and control

NASA Technical Reports Server (NTRS)

Musetti, B.; Cibrario, B.; Bussolino, L.; Bodley, C. S.; Flanders, H. A.; Mowery, D. K.; Tomlin, D. D.

1990-01-01

The first tethered satellite system, scheduled for launch in May 1991, is reviewed. The system dynamics, dynamics control, and dynamics simulations are discussed. Particular attention is given to in-plane and out-of-plane librations; tether oscillation modes; orbiter and sub-satellite dynamics; deployer control system; the sub-satellite attitude measurement and control system; the Aeritalia Dynamics Model; the Martin-Marietta and NASA-MSFC Dynamics Model; and simulation results.

Ant Colony Optimization for Mapping, Scheduling and Placing in Reconfigurable Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ferrandi, Fabrizio; Lanzi, Pier Luca; Pilato, Christian

Modern heterogeneous embedded platforms, com- posed of several digital signal, application specific and general purpose processors, also include reconfigurable devices support- ing partial dynamic reconfiguration. These devices can change the behavior of some of their parts during execution, allowing hardware acceleration of more sections of the applications. Never- theless, partial dynamic reconfiguration imposes severe overheads in terms of latency. For such systems, a critical part of the design phase is deciding on which processing elements (mapping) and when (scheduling) executing a task, but also how to place them on the reconfigurable device to guarantee the most efficient reuse of themore » programmable logic. In this paper we propose an algorithm based on Ant Colony Optimization (ACO) that simultaneously executes the scheduling, the mapping and the linear placing of tasks, hiding reconfiguration overheads through prefetching. Our heuristic gradually constructs solutions and then searches around the best ones, cutting out non-promising areas of the design space. We show how to consider the partial dynamic reconfiguration constraints in the scheduling, placing and mapping problems and compare our formulation to other heuristics that address the same problems. We demonstrate that our proposal is more general and robust, and finds better solutions (16.5% in average) with respect to competing solutions.« less

Dynamic I/O Power Management for Hard Real-Time Systems

DTIC Science & Technology

2005-01-01

recently emerged as an attractive alternative to inflexible hardware solutions. DPM for hard real - time systems has received relatively little attention...In particular, energy-driven I/O device scheduling for real - time systems has not been considered before. We present the first online DPM algorithm...which we call Low Energy Device Scheduler (LEDES), for hard real - time systems . LEDES takes as inputs a predetermined task schedule and a device-usage

Dynamic Routing for Delay-Tolerant Networking in Space Flight Operations

NASA Technical Reports Server (NTRS)

Burleigh, Scott C.

2008-01-01

Contact Graph Routing (CGR) is a dynamic routing system that computes routes through a time-varying topology composed of scheduled, bounded communication contacts in a network built on the Delay-Tolerant Networking (DTN) architecture. It is designed to support operations in a space network based on DTN, but it also could be used in terrestrial applications where operation according to a predefined schedule is preferable to opportunistic communication, as in a low-power sensor network. This paper will describe the operation of the CGR system and explain how it can enable data delivery over scheduled transmission opportunities, fully utilizing the available transmission capacity, without knowing the current state of any bundle protocol node (other than the local node itself) and without exhausting processing resources at any bundle router.

User-Assisted Store Recycling for Dynamic Task Graph Schedulers

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kurt, Mehmet Can; Krishnamoorthy, Sriram; Agrawal, Gagan

The emergence of the multi-core era has led to increased interest in designing effective yet practical parallel programming models. Models based on task graphs that operate on single-assignment data are attractive in several ways: they can support dynamic applications and precisely represent the available concurrency. However, they also require nuanced algorithms for scheduling and memory management for efficient execution. In this paper, we consider memory-efficient dynamic scheduling of task graphs. Specifically, we present a novel approach for dynamically recycling the memory locations assigned to data items as they are produced by tasks. We develop algorithms to identify memory-efficient store recyclingmore » functions by systematically evaluating the validity of a set of (user-provided or automatically generated) alternatives. Because recycling function can be input data-dependent, we have also developed support for continued correct execution of a task graph in the presence of a potentially incorrect store recycling function. Experimental evaluation demonstrates that our approach to automatic store recycling incurs little to no overheads, achieves memory usage comparable to the best manually derived solutions, often produces recycling functions valid across problem sizes and input parameters, and efficiently recovers from an incorrect choice of store recycling functions.« less

Getting the Most from the Twin Mars Rovers

NASA Technical Reports Server (NTRS)

Laufenberg, Larry

2003-01-01

The report discusses the Mixed-initiative Activity Planning GENerator (MARGEN) automatically generates activity plans for rovers. Decision support system mixes autonomous planning/scheduling with user modifications. Accommodating change. Technology spotlight

Energy Efficient Real-Time Scheduling Using DPM on Mobile Sensors with a Uniform Multi-Cores

PubMed Central

Kim, Youngmin; Lee, Chan-Gun

2017-01-01

In wireless sensor networks (WSNs), sensor nodes are deployed for collecting and analyzing data. These nodes use limited energy batteries for easy deployment and low cost. The use of limited energy batteries is closely related to the lifetime of the sensor nodes when using wireless sensor networks. Efficient-energy management is important to extending the lifetime of the sensor nodes. Most effort for improving power efficiency in tiny sensor nodes has focused mainly on reducing the power consumed during data transmission. However, recent emergence of sensor nodes equipped with multi-cores strongly requires attention to be given to the problem of reducing power consumption in multi-cores. In this paper, we propose an energy efficient scheduling method for sensor nodes supporting a uniform multi-cores. We extend the proposed T-Ler plane based scheduling for global optimal scheduling of a uniform multi-cores and multi-processors to enable power management using dynamic power management. In the proposed approach, processor selection for a scheduling and mapping method between the tasks and processors is proposed to efficiently utilize dynamic power management. Experiments show the effectiveness of the proposed approach compared to other existing methods. PMID:29240695

Learning to improve iterative repair scheduling

NASA Technical Reports Server (NTRS)

Zweben, Monte; Davis, Eugene

1992-01-01

This paper presents a general learning method for dynamically selecting between repair heuristics in an iterative repair scheduling system. The system employs a version of explanation-based learning called Plausible Explanation-Based Learning (PEBL) that uses multiple examples to confirm conjectured explanations. The basic approach is to conjecture contradictions between a heuristic and statistics that measure the quality of the heuristic. When these contradictions are confirmed, a different heuristic is selected. To motivate the utility of this approach we present an empirical evaluation of the performance of a scheduling system with respect to two different repair strategies. We show that the scheduler that learns to choose between the heuristics outperforms the same scheduler with any one of two heuristics alone.

Design Evolution of a Fighter Training Scheduling Decision Support System.

DTIC Science & Technology

1987-03-01

SYSTEM THESIS Paul E. Trapp Jeffrey W. Grechanik Captain, USAF Captain, USAF AFIT/GST/ENS/87M-8 MAY 191987 " Approved for public release; distribution...E. Trapp, B.S., M.A. Jeffrey W. Grechanik, B.S. Captain, USAF Captain, USAF March 87 Approved for public release; distribution unlimited This work...DNIF, TDY, and other disruptions. Therefore, cycli- cal scheduling will not be used (3:1-18). ProgAMming. Arthur and Ravindran proposed a goal

United States Marine Corps 2012 Financial Report. Schedule of Budgetary Activity for Fiscal Year 2012 Appropriations

DTIC Science & Technology

2012-01-01

activity schedule for current year appropriations that is also compliant with Generally Accepted Accounting Principles ( GAAP ). The audit of this financial...are not only fighters, but also who can serve as trainers, mentors and advisers. Marine Corps Value to the Nation For a remarkably small investment ...who are interested in and could use the information in the statements to help them make resource allocation and other decisions and hold the entity

Validating and Verifying Biomathematical Models of Human Fatigue

NASA Technical Reports Server (NTRS)

Martinez, Siera Brooke; Quintero, Luis Ortiz; Flynn-Evans, Erin

2015-01-01

Airline pilots experience acute and chronic sleep deprivation, sleep inertia, and circadian desynchrony due to the need to schedule flight operations around the clock. This sleep loss and circadian desynchrony gives rise to cognitive impairments, reduced vigilance and inconsistent performance. Several biomathematical models, based principally on patterns observed in circadian rhythms and homeostatic drive, have been developed to predict a pilots levels of fatigue or alertness. These models allow for the Federal Aviation Administration (FAA) and commercial airlines to make decisions about pilot capabilities and flight schedules. Although these models have been validated in a laboratory setting, they have not been thoroughly tested in operational environments where uncontrolled factors, such as environmental sleep disrupters, caffeine use and napping, may impact actual pilot alertness and performance. We will compare the predictions of three prominent biomathematical fatigue models (McCauley Model, Harvard Model, and the privately-sold SAFTE-FAST Model) to actual measures of alertness and performance. We collected sleep logs, movement and light recordings, psychomotor vigilance task (PVT), and urinary melatonin (a marker of circadian phase) from 44 pilots in a short-haul commercial airline over one month. We will statistically compare with the model predictions to lapses on the PVT and circadian phase. We will calculate the sensitivity and specificity of each model prediction under different scheduling conditions. Our findings will aid operational decision-makers in determining the reliability of each model under real-world scheduling situations.

Automated Platform Management System Scheduling

NASA Technical Reports Server (NTRS)

Hull, Larry G.

1990-01-01

The Platform Management System was established to coordinate the operation of platform systems and instruments. The management functions are split between ground and space components. Since platforms are to be out of contact with the ground more than the manned base, the on-board functions are required to be more autonomous than those of the manned base. Under this concept, automated replanning and rescheduling, including on-board real-time schedule maintenance and schedule repair, are required to effectively and efficiently meet Space Station Freedom mission goals. In a FY88 study, we developed several promising alternatives for automated platform planning and scheduling. We recommended both a specific alternative and a phased approach to automated platform resource scheduling. Our recommended alternative was based upon use of exactly the same scheduling engine in both ground and space components of the platform management system. Our phased approach recommendation was based upon evolutionary development of the platform. In the past year, we developed platform scheduler requirements and implemented a rapid prototype of a baseline platform scheduler. Presently we are rehosting this platform scheduler rapid prototype and integrating the scheduler prototype into two Goddard Space Flight Center testbeds, as the ground scheduler in the Scheduling Concepts, Architectures, and Networks Testbed and as the on-board scheduler in the Platform Management System Testbed. Using these testbeds, we will investigate rescheduling issues, evaluate operational performance and enhance the platform scheduler prototype to demonstrate our evolutionary approach to automated platform scheduling. The work described in this paper was performed prior to Space Station Freedom rephasing, transfer of platform responsibility to Code E, and other recently discussed changes. We neither speculate on these changes nor attempt to predict the impact of the final decisions. As a consequence some of our work and results may be outdated when this paper is published.

Scheduling Policies for an Antiterrorist Surveillance System

DTIC Science & Technology

2008-06-27

times; for example, see Reiman and Wein [17] and Olsen [15]. For real-time scheduling problems involving impatient customers, see Gaver et al. [2...heavy traffic with throughput time constraints: Asymptotically optimal dynamic controls. Queueing Systems 39, 23–54. 30 [17] Reiman , M. I. and Wein

Using filtered forecasting techniques to determine personalized monitoring schedules for patients with open-angle glaucoma.

PubMed

Schell, Greggory J; Lavieri, Mariel S; Helm, Jonathan E; Liu, Xiang; Musch, David C; Van Oyen, Mark P; Stein, Joshua D

2014-08-01

To determine whether dynamic and personalized schedules of visual field (VF) testing and intraocular pressure (IOP) measurements result in an improvement in disease progression detection compared with fixed interval schedules for performing these tests when evaluating patients with open-angle glaucoma (OAG). Secondary analyses using longitudinal data from 2 randomized controlled trials. A total of 571 participants from the Advanced Glaucoma Intervention Study (AGIS) and the Collaborative Initial Glaucoma Treatment Study (CIGTS). Perimetric and tonometric data were obtained for AGIS and CIGTS trial participants and used to parameterize and validate a Kalman filter model. The Kalman filter updates knowledge about each participant's disease dynamics as additional VF tests and IOP measurements are obtained. After incorporating the most recent VF and IOP measurements, the model forecasts each participant's disease dynamics into the future and characterizes the forecasting error. To determine personalized schedules for future VF tests and IOP measurements, we developed an algorithm by combining the Kalman filter for state estimation with the predictive power of logistic regression to identify OAG progression. The algorithm was compared with 1-, 1.5-, and 2-year fixed interval schedules of obtaining VF and IOP measurements. Length of diagnostic delay in detecting OAG progression, efficiency of detecting progression, and number of VF and IOP measurements needed to assess for progression. Participants were followed in the AGIS and CIGTS trials for a mean (standard deviation) of 6.5 (2.8) years. Our forecasting model achieved a 29% increased efficiency in identifying OAG progression (P<0.0001) and detected OAG progression 57% sooner (reduced diagnostic delay) (P = 0.02) than following a fixed yearly monitoring schedule, without increasing the number of VF tests and IOP measurements required. The model performed well for patients with mild and advanced disease. The model performed significantly more testing of patients who exhibited OAG progression than nonprogressing patients (1.3 vs. 1.0 tests per year; P<0.0001). Use of dynamic and personalized testing schedules can enhance the efficiency of OAG progression detection and reduce diagnostic delay compared with yearly fixed monitoring intervals. If further validation studies confirm these findings, such algorithms may be able to greatly enhance OAG management. Copyright © 2014 American Academy of Ophthalmology. Published by Elsevier Inc. All rights reserved.

Linear modeling of steady-state behavioral dynamics.

PubMed Central

Palya, William L; Walter, Donald; Kessel, Robert; Lucke, Robert

2002-01-01

The observed steady-state behavioral dynamics supported by unsignaled periods of reinforcement within repeating 2,000-s trials were modeled with a linear transfer function. These experiments employed improved schedule forms and analytical methods to improve the precision of the measured transfer function, compared to previous work. The refinements include both the use of multiple reinforcement periods that improve spectral coverage and averaging of independently determined transfer functions. A linear analysis was then used to predict behavior observed for three different test schedules. The fidelity of these predictions was determined. PMID:11831782

[Toward a New Immunization Schedule in Spain, 2016 (Part 2)].

PubMed

Navarro-Alonso, José Antonio; Taboada-Rodríguez, José Antonio; Limia-Sánchez, Aurora

2016-03-08

Immunization schedules are intrinsically dynamic in order to embed the immunologic and epidemiologic changes in any specific geographic Region. According to this, the current study addresses a proposal to modify the Childhood Immunization Schedule in Spain. In order to move from a three plus one schema to a two plus one, we undertake a review of the available literature to explore the immunological and clinical rationale behind this change, including an overview of the potential impact on this schedule of premature infants. Additionally, some recommendations are made regarding those Spanish regions which start hepatitis B vaccination at the newborn period.

76 FR 53700 - Records Schedules; Availability and Request for Comments

Federal Register 2010, 2011, 2012, 2013, 2014

2011-08-29

... business intelligence and finance and accounting information to Department of Defense (DOD) decision makers... to process printing orders and bill customers. 15. Department of State, Bureau of Diplomatic Security...

Optimal Shift Duration and Sequence: Recommended Approach for Short-Term Emergency Response Activations for Public Health and Emergency Management

PubMed Central

Burgess, Paula A.

2007-01-01

Since September 11, 2001, and the consequent restructuring of the US preparedness and response activities, public health workers are increasingly called on to activate a temporary round-the-clock staffing schedule. These workers may have to make key decisions that could significantly impact the health and safety of the public. The unique physiological demands of rotational shift work and night shift work have the potential to negatively impact decisionmaking ability. A responsible, evidence-based approach to scheduling applies the principles of circadian physiology, as well as unique individual physiologies and preferences. Optimal scheduling would use a clockwise (morning-afternoon-night) rotational schedule: limiting night shifts to blocks of 3, limiting shift duration to 8 hours, and allowing 3 days of recuperation after night shifts. PMID:17413074

Designing a fuzzy scheduler for hard real-time systems

NASA Technical Reports Server (NTRS)

Yen, John; Lee, Jonathan; Pfluger, Nathan; Natarajan, Swami

1992-01-01

In hard real-time systems, tasks have to be performed not only correctly, but also in a timely fashion. If timing constraints are not met, there might be severe consequences. Task scheduling is the most important problem in designing a hard real-time system, because the scheduling algorithm ensures that tasks meet their deadlines. However, the inherent nature of uncertainty in dynamic hard real-time systems increases the problems inherent in scheduling. In an effort to alleviate these problems, we have developed a fuzzy scheduler to facilitate searching for a feasible schedule. A set of fuzzy rules are proposed to guide the search. The situation we are trying to address is the performance of the system when no feasible solution can be found, and therefore, certain tasks will not be executed. We wish to limit the number of important tasks that are not scheduled.

Novel Hybrid Scheduling Technique for Sensor Nodes with Mixed Criticality Tasks.

PubMed

Micea, Mihai-Victor; Stangaciu, Cristina-Sorina; Stangaciu, Valentin; Curiac, Daniel-Ioan

2017-06-26

Sensor networks become increasingly a key technology for complex control applications. Their potential use in safety- and time-critical domains has raised the need for task scheduling mechanisms specially adapted to sensor node specific requirements, often materialized in predictable jitter-less execution of tasks characterized by different criticality levels. This paper offers an efficient scheduling solution, named Hybrid Hard Real-Time Scheduling (H²RTS), which combines a static, clock driven method with a dynamic, event driven scheduling technique, in order to provide high execution predictability, while keeping a high node Central Processing Unit (CPU) utilization factor. From the detailed, integrated schedulability analysis of the H²RTS, a set of sufficiency tests are introduced and demonstrated based on the processor demand and linear upper bound metrics. The performance and correct behavior of the proposed hybrid scheduling technique have been extensively evaluated and validated both on a simulator and on a sensor mote equipped with ARM7 microcontroller.

Stochastic flow shop scheduling of overlapping jobs on tandem machines in application to optimizing the US Army's deliberate nuclear, biological, and chemical decontamination process, (final report). Master's thesis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Novikov, V.

1991-05-01

The U.S. Army's detailed equipment decontamination process is a stochastic flow shop which has N independent non-identical jobs (vehicles) which have overlapping processing times. This flow shop consists of up to six non-identical machines (stations). With the exception of one station, the processing times of the jobs are random variables. Based on an analysis of the processing times, the jobs for the 56 Army heavy division companies were scheduled according to the best shortest expected processing time - longest expected processing time (SEPT-LEPT) sequence. To assist in this scheduling the Gap Comparison Heuristic was developed to select the best SEPT-LEPTmore » schedule. This schedule was then used in balancing the detailed equipment decon line in order to find the best possible site configuration subject to several constraints. The detailed troop decon line, in which all jobs are independent and identically distributed, was then balanced. Lastly, an NBC decon optimization computer program was developed using the scheduling and line balancing results. This program serves as a prototype module for the ANBACIS automated NBC decision support system.... Decontamination, Stochastic flow shop, Scheduling, Stochastic scheduling, Minimization of the makespan, SEPT-LEPT Sequences, Flow shop line balancing, ANBACIS.« less

A New Engine for Schools: The Flexible Scheduling Paradigm

ERIC Educational Resources Information Center

Snyder, Yaakov; Herer, Yale T.; Moore, Michael

2012-01-01

We present a new approach for the organization of schools, which we call the flexible scheduling paradigm (FSP). FSP improves student learning by dynamically redeploying teachers and other pedagogical resources to provide students with customized learning conditions over shorter time periods called "mini-terms" instead of semesters or years. By…

Optimal infrastructure maintenance scheduling problem under budget uncertainty.

DOT National Transportation Integrated Search

2010-05-01

This research addresses a general class of infrastructure asset management problems. Infrastructure : agencies usually face budget uncertainties that will eventually lead to suboptimal planning if : maintenance decisions are made without taking the u...

Planning a Stigmatized Nonvisible Illness Disclosure: Applying the Disclosure Decision-Making Model

PubMed Central

Choi, Soe Yoon; Venetis, Maria K.; Greene, Kathryn; Magsamen-Conrad, Kate; Checton, Maria G.; Banerjee, Smita C.

2016-01-01

This study applied the disclosure decision-making model (DD-MM) to explore how individuals plan to disclose nonvisible illness (Study 1), compared to planning to disclose personal information (Study 2). Study 1 showed that perceived stigma from the illness negatively predicted disclosure efficacy; closeness predicted anticipated response (i.e., provision of support) although it did not influence disclosure efficacy; disclosure efficacy led to reduced planning, with planning leading to scheduling. Study 2 demonstrated that when information was considered to be intimate, it negatively influenced disclosure efficacy. Unlike the model with stigma (Study 1), closeness positively predicted both anticipated response and disclosure efficacy. The rest of the hypothesized relationships showed a similar pattern to Study 1: disclosure efficacy reduced planning, which then positively influenced scheduling. Implications of understanding stages of planning for stigmatized information are discussed. PMID:27662447

Planning a Stigmatized Nonvisible Illness Disclosure: Applying the Disclosure Decision-Making Model.

PubMed

Choi, Soe Yoon; Venetis, Maria K; Greene, Kathryn; Magsamen-Conrad, Kate; Checton, Maria G; Banerjee, Smita C

2016-11-16

This study applied the disclosure decision-making model (DD-MM) to explore how individuals plan to disclose nonvisible illness (Study 1), compared to planning to disclose personal information (Study 2). Study 1 showed that perceived stigma from the illness negatively predicted disclosure efficacy; closeness predicted anticipated response (i.e., provision of support) although it did not influence disclosure efficacy; disclosure efficacy led to reduced planning, with planning leading to scheduling. Study 2 demonstrated that when information was considered to be intimate, it negatively influenced disclosure efficacy. Unlike the model with stigma (Study 1), closeness positively predicted both anticipated response and disclosure efficacy. The rest of the hypothesized relationships showed a similar pattern to Study 1: disclosure efficacy reduced planning, which then positively influenced scheduling. Implications of understanding stages of planning for stigmatized information are discussed.

Materials experiment carrier concepts definition study. Volume 3: Programmatics, part 2

NASA Technical Reports Server (NTRS)

1981-01-01

Project logic, schedule and funding information was derived to enable decisions to be made regarding implementation of MEC system development. A master schedule and cost and price estimates (ROM) were developed for a project that consists of development of an all-up MEC, its integration with payloads and its flight on one 90 day mission. In Part 2 of the study a simple initial MEC was defined to accommodate three MPS baseline payloads. The design of this initial MEC is illustrated. The project logic, detailed schedules, and ROM cost estimate relate to a project in which this initial MEC is developed, integrated with payloads and flown once for 180 days.

Optimization of Airport Surface Traffic: A Case-Study of Incheon International Airport

NASA Technical Reports Server (NTRS)

Eun, Yeonju; Jeon, Daekeun; Lee, Hanbong; Jung, Yoon C.; Zhu, Zhifan; Jeong, Myeongsook; Kim, Hyounkong; Oh, Eunmi; Hong, Sungkwon

2017-01-01

This study aims to develop a controllers decision support tool for departure and surface management of ICN. Airport surface traffic optimization for Incheon International Airport (ICN) in South Korea was studied based on the operational characteristics of ICN and airspace of Korea. For surface traffic optimization, a multiple runway scheduling problem and a taxi scheduling problem were formulated into two Mixed Integer Linear Programming (MILP) optimization models. The Miles-In-Trail (MIT) separation constraint at the departure fix shared by the departure flights from multiple runways and the runway crossing constraints due to the taxi route configuration specific to ICN were incorporated into the runway scheduling and taxiway scheduling problems, respectively. Since the MILP-based optimization model for the multiple runway scheduling problem may be computationally intensive, computation times and delay costs of different solving methods were compared for a practical implementation. This research was a collaboration between Korea Aerospace Research Institute (KARI) and National Aeronautics and Space Administration (NASA).

Optimization of Airport Surface Traffic: A Case-Study of Incheon International Airport

NASA Technical Reports Server (NTRS)

Eun, Yeonju; Jeon, Daekeun; Lee, Hanbong; Jung, Yoon Chul; Zhu, Zhifan; Jeong, Myeong-Sook; Kim, Hyoun Kyoung; Oh, Eunmi; Hong, Sungkwon

2017-01-01

This study aims to develop a controllers' decision support tool for departure and surface management of ICN. Airport surface traffic optimization for Incheon International Airport (ICN) in South Korea was studied based on the operational characteristics of ICN and airspace of Korea. For surface traffic optimization, a multiple runway scheduling problem and a taxi scheduling problem were formulated into two Mixed Integer Linear Programming (MILP) optimization models. The Miles-In-Trail (MIT) separation constraint at the departure fix shared by the departure flights from multiple runways and the runway crossing constraints due to the taxi route configuration specific to ICN were incorporated into the runway scheduling and taxiway scheduling problems, respectively. Since the MILP-based optimization model for the multiple runway scheduling problem may be computationally intensive, computation times and delay costs of different solving methods were compared for a practical implementation. This research was a collaboration between Korea Aerospace Research Institute (KARI) and National Aeronautics and Space Administration (NASA).

Visualizing and Integrating AFSCN Utilization into a Common Operational Picture

NASA Astrophysics Data System (ADS)

Hays, B.; Carlile, A.; Mitchell, T.

The Department of Defense (DoD) and the 50th Space Network Operations Group Studies and Analysis branch (50th SCS/SCXI), located at Schriever AFB Colorado, face the unique challenge of forecasting the expected near term and future utilization of the Air Force Satellite Control Network (AFSCN). The forecasting timeframe covers the planned load from the current date to ten years out. The various satellite missions, satellite requirements, orbital regions, and ground architecture dynamics provide the model inputs and constraints that are used in generating the forecasted load. The AFSCN is the largest network the Air Force uses to control satellites worldwide. Each day, network personnel perform over 500 scheduled events-from satellite maneuvers to critical data downloads. The Forecasting Objective is to provide leadership with the insights necessary to manage the network today and tomorrow. For both today's needs and future needs, SCXI develops AFSCN utilization forecasts to optimize the ground system's coverage and capacity to meet user satellite requirements. SCXI also performs satellite program specific studies to determine network support feasibility. STK and STK Scheduler form the core of the tools used by SCXI. To establish this tool suite, we had to evaluate, evolve, and validate both the COTS products and our own developed code and processes. This began with calibrating the network model to emulate the real life scheduling environment of the AFSCN. Multiple STK Scheduler optimizing (de-confliction) algorithms, including Multi-Pass, Sequential, Random, and Neural, were evaluated and adjusted to determine applicability to the model and the accuracy of the prediction. Additionally, the scheduling Figure of Merit (FOM), which permits custom weighting of various parameters, was analyzed and tested to achieve the most accurate real life result. With the inherent capabilities of STK and the ability to wrap and automate output, SCXI is now able to visually communicate satellite loads in a manner never seen before in AFSCN management meetings. Scenarios such as regional antenna load stress, satellite missed opportunities, and the overall network "big picture" can be visually displayed in 3D versus the textual and line graph methods used for many years. This is the first step towards an integrated space awareness picture with an operational focus. SCXI is working on taking the visual forecast concept farther and begin fusing multiple sources of data to build a 50 SW Common Operating Picture (COP). The vision is to integrate more effective orbital determination processes, resource outages, current and forecasted satellite mission requirements, and future architectural changes into a real-time visual status to enable quick and responsive decisions. This COP would be utilized in a Wing Operations Center to provide up to the minute network status on where satellites are, which ground resources are in contact with them, and what resources are down. The ability to quickly absorb and process this data will enhance decision analysis and save valuable time in both day to day operations and wartime scenarios.

Dynamics of rapid dopamine release in the nucleus accumbens during goal-directed behaviors for cocaine versus natural rewards

PubMed Central

Cameron, Courtney M.; Wightman, R. Mark; Carelli, Regina M.

2014-01-01

Electrophysiological studies show that distinct subsets of nucleus accumbens (NAc) neurons differentially encode information about goal-directed behaviors for intravenous cocaine versus natural (food/water) rewards. Further, NAc rapid dopamine signaling occurs on a timescale similar to phasic cell firing during cocaine and natural reward-seeking behaviors. However, it is not known whether dopamine signaling is reinforcer specific (i.e., is released during responding for only one type of reinforcer) within discrete NAc locations, similar to neural firing dynamics. Here, fast-scan cyclic voltammetry (FSCV) was used to measure rapid dopamine release during multiple schedules involving sucrose reward and cocaine self-administration (n=8 rats) and, in a separate group of rats (n = 6), during a sucrose/food multiple schedule. During the sucrose/cocaine multiple schedule, dopamine increased within seconds of operant responding for both reinforcers. Although dopamine release was not reinforcer specific, more subtle differences were observed in peak dopamine concentration [DA] across reinforcer conditions. Specifically, peak [DA] was higher during the first phase of the multiple schedule, regardless of reinforcer type. Further, the time to reach peak [DA] was delayed during cocaine-responding compared to sucrose. During the sucrose/food multiple schedule, increases in dopamine release were also observed relative to operant responding for both natural rewards. However, peak [DA] was higher relative to responding for sucrose than food, regardless of reinforcer order. Overall, the results reveal the dynamics of rapid dopamine signaling in discrete locations in the NAc across reward conditions, and provide novel insight into the functional role of this system in reward-seeking behaviors. PMID:25174553

Request-Driven Schedule Automation for the Deep Space Network

NASA Technical Reports Server (NTRS)

Johnston, Mark D.; Tran, Daniel; Arroyo, Belinda; Call, Jared; Mercado, Marisol

2010-01-01

The DSN Scheduling Engine (DSE) has been developed to increase the level of automated scheduling support available to users of NASA s Deep Space Network (DSN). We have adopted a request-driven approach to DSN scheduling, in contrast to the activity-oriented approach used up to now. Scheduling requests allow users to declaratively specify patterns and conditions on their DSN service allocations, including timing, resource requirements, gaps, overlaps, time linkages among services, repetition, priorities, and a wide range of additional factors and preferences. The DSE incorporates a model of the key constraints and preferences of the DSN scheduling domain, along with algorithms to expand scheduling requests into valid resource allocations, to resolve schedule conflicts, and to repair unsatisfied requests. We use time-bounded systematic search with constraint relaxation to return nearby solutions if exact ones cannot be found, where the relaxation options and order are under user control. To explore the usability aspects of our approach we have developed a graphical user interface incorporating some crucial features to make it easier to work with complex scheduling requests. Among these are: progressive revelation of relevant detail, immediate propagation and visual feedback from a user s decisions, and a meeting calendar metaphor for repeated patterns of requests. Even as a prototype, the DSE has been deployed and adopted as the initial step in building the operational DSN schedule, thus representing an important initial validation of our overall approach. The DSE is a core element of the DSN Service Scheduling Software (S(sup 3)), a web-based collaborative scheduling system now under development for deployment to all DSN users.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Edwards, Harold C.; Ibanez, Daniel Alejandro

This report documents the ASC/ATDM Kokkos deliverable "Production Portable Dy- namic Task DAG Capability." This capability enables applications to create and execute a dynamic task DAG ; a collection of heterogeneous computational tasks with a directed acyclic graph (DAG) of "execute after" dependencies where tasks and their dependencies are dynamically created and destroyed as tasks execute. The Kokkos task scheduler executes the dynamic task DAG on the target execution resource; e.g. a multicore CPU, a manycore CPU such as Intel's Knights Landing (KNL), or an NVIDIA GPU. Several major technical challenges had to be addressed during development of Kokkos' Taskmore » DAG capability: (1) portability to a GPU with it's simplified hardware and micro- runtime, (2) thread-scalable memory allocation and deallocation from a bounded pool of memory, (3) thread-scalable scheduler for dynamic task DAG, (4) usability by applications.« less

Using Grid Benchmarks for Dynamic Scheduling of Grid Applications

NASA Technical Reports Server (NTRS)

Frumkin, Michael; Hood, Robert

2003-01-01

Navigation or dynamic scheduling of applications on computational grids can be improved through the use of an application-specific characterization of grid resources. Current grid information systems provide a description of the resources, but do not contain any application-specific information. We define a GridScape as dynamic state of the grid resources. We measure the dynamic performance of these resources using the grid benchmarks. Then we use the GridScape for automatic assignment of the tasks of a grid application to grid resources. The scalability of the system is achieved by limiting the navigation overhead to a few percent of the application resource requirements. Our task submission and assignment protocol guarantees that the navigation system does not cause grid congestion. On a synthetic data mining application we demonstrate that Gridscape-based task assignment reduces the application tunaround time.

Resource Management in Constrained Dynamic Situations

NASA Astrophysics Data System (ADS)

Seok, Jinwoo

Resource management is considered in this dissertation for systems with limited resources, possibly combined with other system constraints, in unpredictably dynamic environments. Resources may represent fuel, power, capabilities, energy, and so on. Resource management is important for many practical systems; usually, resources are limited, and their use must be optimized. Furthermore, systems are often constrained, and constraints must be satisfied for safe operation. Simplistic resource management can result in poor use of resources and failure of the system. Furthermore, many real-world situations involve dynamic environments. Many traditional problems are formulated based on the assumptions of given probabilities or perfect knowledge of future events. However, in many cases, the future is completely unknown, and information on or probabilities about future events are not available. In other words, we operate in unpredictably dynamic situations. Thus, a method is needed to handle dynamic situations without knowledge of the future, but few formal methods have been developed to address them. Thus, the goal is to design resource management methods for constrained systems, with limited resources, in unpredictably dynamic environments. To this end, resource management is organized hierarchically into two levels: 1) planning, and 2) control. In the planning level, the set of tasks to be performed is scheduled based on limited resources to maximize resource usage in unpredictably dynamic environments. In the control level, the system controller is designed to follow the schedule by considering all the system constraints for safe and efficient operation. Consequently, this dissertation is mainly divided into two parts: 1) planning level design, based on finite state machines, and 2) control level methods, based on model predictive control. We define a recomposable restricted finite state machine to handle limited resource situations and unpredictably dynamic environments for the planning level. To obtain a policy, dynamic programing is applied, and to obtain a solution, limited breadth-first search is applied to the recomposable restricted finite state machine. A multi-function phased array radar resource management problem and an unmanned aerial vehicle patrolling problem are treated using recomposable restricted finite state machines. Then, we use model predictive control for the control level, because it allows constraint handling and setpoint tracking for the schedule. An aircraft power system management problem is treated that aims to develop an integrated control system for an aircraft gas turbine engine and electrical power system using rate-based model predictive control. Our results indicate that at the planning level, limited breadth-first search for recomposable restricted finite state machines generates good scheduling solutions in limited resource situations and unpredictably dynamic environments. The importance of cooperation in the planning level is also verified. At the control level, a rate-based model predictive controller allows good schedule tracking and safe operations. The importance of considering the system constraints and interactions between the subsystems is indicated. For the best resource management in constrained dynamic situations, the planning level and the control level need to be considered together.

Dynamic Management of Releases for the Delaware River Basin using NYC's Operations Support Tool

NASA Astrophysics Data System (ADS)

Weiss, W.; Wang, L.; Murphy, T.; Muralidhar, D.; Tarrier, B.

2011-12-01

The New York City Department of Environmental Protection (DEP) has initiated design of an Operations Support Tool (OST), a state-of-the-art decision support system to provide computational and predictive support for water supply operations and planning. Using an interim version of OST, DEP and the New York State Department of Environmental Conservation (DEC) have developed a provisional, one-year Delaware River Basin reservoir release program to succeed the existing Flexible Flow Management Program (FFMP) which expired on May 31, 2011. The FFMP grew out of the Good Faith Agreement of 1983 among the four Basin states (New York, New Jersey, Pennsylvania, and Delaware) that established modified diversions and flow targets during drought conditions. It provided a set of release schedules as a framework for managing diversions and releases from New York City's Delaware Basin reservoirs in order to support multiple objectives, including water supply, drought mitigation, flood mitigation, tailwaters fisheries, main stem habitat, recreation, and salinity repulsion. The provisional program (OST-FFMP) defines available water based on current Upper Delaware reservoir conditions and probabilistic forecasts of reservoir inflow. Releases are then set based on a set of release schedules keyed to the water availability. Additionally, OST-FFMP attempts to provide enhanced downstream flood protection by making spill mitigation releases to keep the Delaware System reservoirs at a seasonally varying conditional storage objective. The OST-FFMP approach represents a more robust way of managing downstream releases, accounting for predicted future hydrologic conditions by making more water available for release when conditions are forecasted to be wet and protecting water supply reliability when conditions are forecasted to be dry. Further, the dynamic nature of the program allows the release decision to be adjusted as hydrologic conditions change. OST simulations predict that this program can provide substantial benefits for downstream stakeholders while protecting DEP's ability to ensure a reliable water supply for 9 million customers in NYC and the surrounding communities. The one-year nature of the program will allow for DEP and the Decree Parties to evaluate and improve the program in the future. This paper will describe the OST-FFMP program and discuss preliminary observations on its performance based on key NYC and downstream stakeholder performance metrics.

MaGate Simulator: A Simulation Environment for a Decentralized Grid Scheduler

NASA Astrophysics Data System (ADS)

Huang, Ye; Brocco, Amos; Courant, Michele; Hirsbrunner, Beat; Kuonen, Pierre

This paper presents a simulator for of a decentralized modular grid scheduler named MaGate. MaGate’s design emphasizes scheduler interoperability by providing intelligent scheduling serving the grid community as a whole. Each MaGate scheduler instance is able to deal with dynamic scheduling conditions, with continuously arriving grid jobs. Received jobs are either allocated on local resources, or delegated to other MaGates for remote execution. The proposed MaGate simulator is based on GridSim toolkit and Alea simulator, and abstracts the features and behaviors of complex fundamental grid elements, such as grid jobs, grid resources, and grid users. Simulation of scheduling tasks is supported by a grid network overlay simulator executing distributed ant-based swarm intelligence algorithms to provide services such as group communication and resource discovery. For evaluation, a comparison of behaviors of different collaborative policies among a community of MaGates is provided. Results support the use of the proposed approach as a functional ready grid scheduler simulator.

Performance analysis of a large-grain dataflow scheduling paradigm

NASA Technical Reports Server (NTRS)

Young, Steven D.; Wills, Robert W.

1993-01-01

A paradigm for scheduling computations on a network of multiprocessors using large-grain data flow scheduling at run time is described and analyzed. The computations to be scheduled must follow a static flow graph, while the schedule itself will be dynamic (i.e., determined at run time). Many applications characterized by static flow exist, and they include real-time control and digital signal processing. With the advent of computer-aided software engineering (CASE) tools for capturing software designs in dataflow-like structures, macro-dataflow scheduling becomes increasingly attractive, if not necessary. For parallel implementations, using the macro-dataflow method allows the scheduling to be insulated from the application designer and enables the maximum utilization of available resources. Further, by allowing multitasking, processor utilizations can approach 100 percent while they maintain maximum speedup. Extensive simulation studies are performed on 4-, 8-, and 16-processor architectures that reflect the effects of communication delays, scheduling delays, algorithm class, and multitasking on performance and speedup gains.

A definition of high-level decisions in the engineering of systems

NASA Astrophysics Data System (ADS)

Powell, Robert Anthony

The role of the systems engineer defines that he or she be proactive and guide the program manager and their customers through their decisions to enhance the effectiveness of system development---producing faster, better, and cheaper systems. The present lack of coverage in literature on what these decisions are and how they relate to each other may be a contributing factor to the high rate of failure among system projects. At the onset of the system development process, decisions have an integral role in the design of a system that meets stakeholders' needs. This is apparent during the design and qualification of both the Development System and the Operational System. The performance, cost and schedule of the Development System affect the performance of the Operational System and are affected by decisions that influence physical elements of the Development System. The performance, cost, and schedule of the Operational System is affected by decisions that influence physical elements of the Operational System. Traditionally, product and process have been designed using know-how and trial and error. However, the empiricism of engineers and program managers is limited which can, and has led to costly mistakes. To date, very little research has explored decisions made in the engineering of a system. In government, literature exists on procurement processes for major system development; but in general literature on decisions, how they relate to each other, and the key information requirements within one of two systems and across the two systems is not readily available. This research hopes to improve the processes inherent in the engineering of systems. The primary focus of this research is on department of defense (DoD) military systems, specifically aerospace systems and may generalize more broadly. The result of this research is a process tool, a Decision System Model, which can be used by systems engineers to guide the program manager and their customers through the decisions about concurrently designing and qualifying both the Development and Operational systems.

On-Line Scheduling of Parallel Machines

DTIC Science & Technology

1990-11-01

machine without losing any work; this is referred to as the preemptive model. In contrast to the nonpreemptive model which we have considered in this paper...that there exists no schedule of length d. The 2-relaxed decision procedure is as follows. Put each job into the queue of the slowest machine Mk such...in their queues . If a machine’s queue is empty it takes jobs to process from the queue of the first machine that is slower than it and that has a

Options for Parallelizing a Planning and Scheduling Algorithm

NASA Technical Reports Server (NTRS)

Clement, Bradley J.; Estlin, Tara A.; Bornstein, Benjamin D.

2011-01-01

Space missions have a growing interest in putting multi-core processors onboard spacecraft. For many missions processing power significantly slows operations. We investigate how continual planning and scheduling algorithms can exploit multi-core processing and outline different potential design decisions for a parallelized planning architecture. This organization of choices and challenges helps us with an initial design for parallelizing the CASPER planning system for a mesh multi-core processor. This work extends that presented at another workshop with some preliminary results.

Causes of catastrophic failure in complex systems

NASA Astrophysics Data System (ADS)

Thomas, David A.

2010-08-01

Root causes of mission critical failures and major cost and schedule overruns in complex systems and programs are studied through the post-mortem analyses compiled for several examples, including the Hubble Space Telescope, the Challenger and Columbia Shuttle accidents, and the Three Mile Island nuclear power plant accident. The roles of organizational complexity, cognitive biases in decision making, the display of quantitative data, and cost and schedule pressure are all considered. Recommendations for mitigating the risk of similar failures in future programs are also provided.

Conflict-Aware Scheduling Algorithm

NASA Technical Reports Server (NTRS)

Wang, Yeou-Fang; Borden, Chester

2006-01-01

conflict-aware scheduling algorithm is being developed to help automate the allocation of NASA s Deep Space Network (DSN) antennas and equipment that are used to communicate with interplanetary scientific spacecraft. The current approach for scheduling DSN ground resources seeks to provide an equitable distribution of tracking services among the multiple scientific missions and is very labor intensive. Due to the large (and increasing) number of mission requests for DSN services, combined with technical and geometric constraints, the DSN is highly oversubscribed. To help automate the process, and reduce the DSN and spaceflight project labor effort required for initiating, maintaining, and negotiating schedules, a new scheduling algorithm is being developed. The scheduling algorithm generates a "conflict-aware" schedule, where all requests are scheduled based on a dynamic priority scheme. The conflict-aware scheduling algorithm allocates all requests for DSN tracking services while identifying and maintaining the conflicts to facilitate collaboration and negotiation between spaceflight missions. These contrast with traditional "conflict-free" scheduling algorithms that assign tracks that are not in conflict and mark the remainder as unscheduled. In the case where full schedule automation is desired (based on mission/event priorities, fairness, allocation rules, geometric constraints, and ground system capabilities/ constraints), a conflict-free schedule can easily be created from the conflict-aware schedule by removing lower priority items that are in conflict.

Scheduling for energy and reliability management on multiprocessor real-time systems

NASA Astrophysics Data System (ADS)

Qi, Xuan

Scheduling algorithms for multiprocessor real-time systems have been studied for years with many well-recognized algorithms proposed. However, it is still an evolving research area and many problems remain open due to their intrinsic complexities. With the emergence of multicore processors, it is necessary to re-investigate the scheduling problems and design/develop efficient algorithms for better system utilization, low scheduling overhead, high energy efficiency, and better system reliability. Focusing cluster schedulings with optimal global schedulers, we study the utilization bound and scheduling overhead for a class of cluster-optimal schedulers. Then, taking energy/power consumption into consideration, we developed energy-efficient scheduling algorithms for real-time systems, especially for the proliferating embedded systems with limited energy budget. As the commonly deployed energy-saving technique (e.g. dynamic voltage frequency scaling (DVFS)) will significantly affect system reliability, we study schedulers that have intelligent mechanisms to recuperate system reliability to satisfy the quality assurance requirements. Extensive simulation is conducted to evaluate the performance of the proposed algorithms on reduction of scheduling overhead, energy saving, and reliability improvement. The simulation results show that the proposed reliability-aware power management schemes could preserve the system reliability while still achieving substantial energy saving.

Non preemptive soft real time scheduler: High deadline meeting rate on overload

NASA Astrophysics Data System (ADS)

Khalib, Zahereel Ishwar Abdul; Ahmad, R. Badlishah; El-Shaikh, Mohamed

2015-05-01

While preemptive scheduling has gain more attention among researchers, current work in non preemptive scheduling had shown promising result in soft real time jobs scheduling. In this paper we present a non preemptive scheduling algorithm meant for soft real time applications, which is capable of producing better performance during overload while maintaining excellent performance during normal load. The approach taken by this algorithm has shown more promising results compared to other algorithms including its immediate predecessor. We will present the analysis made prior to inception of the algorithm as well as simulation results comparing our algorithm named gutEDF with EDF and gEDF. We are convinced that grouping jobs utilizing pure dynamic parameters would produce better performance.

Choosing Mars-Time: Analysis of the Mars Exploration Rover Experience

NASA Technical Reports Server (NTRS)

Bass, Deborah S.; Wales,Roxana C.; Shalin, Valerie L.

2004-01-01

This paper focuses on the Mars Exploration Rover (MER) mission decision to work on Mars Time and the implications of that decision on the tactical surface operations process as personnel planned activities and created a new command load for work on each Martian sol. The paper also looks at tools that supported the complexities of Mars Time work, and makes some comparisons between Earth and Mars time scheduling.

How do strategic decisions and operative practices affect operating room productivity?

PubMed

Peltokorpi, Antti

2011-12-01

Surgical operating rooms are cost-intensive parts of health service production. Managing operating units efficiently is essential when hospitals and healthcare systems aim to maximize health outcomes with limited resources. Previous research about operating room management has focused on studying the effect of management practices and decisions on efficiency by utilizing mainly modeling approach or before-after analysis in single hospital case. The purpose of this research is to analyze the synergic effect of strategic decisions and operative management practices on operating room productivity and to use a multiple case study method enabling statistical hypothesis testing with empirical data. 11 hypotheses that propose connections between the use of strategic and operative practices and productivity were tested in a multi-hospital study that included 26 units. The results indicate that operative practices, such as personnel management, case scheduling and performance measurement, affect productivity more remarkably than do strategic decisions that relate to, e.g., units' size, scope or academic status. Units with different strategic positions should apply different operative practices: Focused hospital units benefit most from sophisticated case scheduling and parallel processing whereas central and ambulatory units should apply flexible working hours, incentives and multi-skilled personnel. Operating units should be more active in applying management practices which are adequate for their strategic orientation.

Taxi Time Prediction at Charlotte Airport Using Fast-Time Simulation and Machine Learning Techniques

NASA Technical Reports Server (NTRS)

Lee, Hanbong

2016-01-01

Accurate taxi time prediction is required for enabling efficient runway scheduling that can increase runway throughput and reduce taxi times and fuel consumptions on the airport surface. Currently NASA and American Airlines are jointly developing a decision-support tool called Spot and Runway Departure Advisor (SARDA) that assists airport ramp controllers to make gate pushback decisions and improve the overall efficiency of airport surface traffic. In this presentation, we propose to use Linear Optimized Sequencing (LINOS), a discrete-event fast-time simulation tool, to predict taxi times and provide the estimates to the runway scheduler in real-time airport operations. To assess its prediction accuracy, we also introduce a data-driven analytical method using machine learning techniques. These two taxi time prediction methods are evaluated with actual taxi time data obtained from the SARDA human-in-the-loop (HITL) simulation for Charlotte Douglas International Airport (CLT) using various performance measurement metrics. Based on the taxi time prediction results, we also discuss how the prediction accuracy can be affected by the operational complexity at this airport and how we can improve the fast time simulation model before implementing it with an airport scheduling algorithm in a real-time environment.

New scheduling rules for a dynamic flexible flow line problem with sequence-dependent setup times

NASA Astrophysics Data System (ADS)

Kia, Hamidreza; Ghodsypour, Seyed Hassan; Davoudpour, Hamid

2017-09-01

In the literature, the application of multi-objective dynamic scheduling problem and simple priority rules are widely studied. Although these rules are not efficient enough due to simplicity and lack of general insight, composite dispatching rules have a very suitable performance because they result from experiments. In this paper, a dynamic flexible flow line problem with sequence-dependent setup times is studied. The objective of the problem is minimization of mean flow time and mean tardiness. A 0-1 mixed integer model of the problem is formulated. Since the problem is NP-hard, four new composite dispatching rules are proposed to solve it by applying genetic programming framework and choosing proper operators. Furthermore, a discrete-event simulation model is made to examine the performances of scheduling rules considering four new heuristic rules and the six adapted heuristic rules from the literature. It is clear from the experimental results that composite dispatching rules that are formed from genetic programming have a better performance in minimization of mean flow time and mean tardiness than others.

CLIVAR Mode Water Dynamics Experiment (CLIMODE), Fall 2006 R/V Oceanus Voyage 434, November 16, 2006-December 3, 2006

DTIC Science & Technology

2007-12-01

except for the dive zero time which needed to be programmed during the cruise when the deployment schedule dates were confirmed. _ ACM - Aanderaa ACM...guards bolted on to complete the frame prior to deployment. Sound Source - Sound sources were scheduled to be redeployed. Sound sources were originally...battery voltages and a vacuum. A +27 second time drift was noted and the time was reset. The sound source was scheduled to go to full power on November

Population dynamics of Varroa destructor (Acari: Varroidae) in commercial honey bee colonies and implications for control

USDA-ARS?s Scientific Manuscript database

Treatment schedules to maintain low levels of Varroa mites in honey bee colonies were tested in hives started from either package bees or splits of larger colonies. The schedules were developed based on predictions of Varroa population growth generated from a mathematical model of honey bee colony ...

A Scheduling Algorithm for the Distributed Student Registration System in Transaction-Intensive Environment

ERIC Educational Resources Information Center

Li, Wenhao

2011-01-01

Distributed workflow technology has been widely used in modern education and e-business systems. Distributed web applications have shown cross-domain and cooperative characteristics to meet the need of current distributed workflow applications. In this paper, the author proposes a dynamic and adaptive scheduling algorithm PCSA (Pre-Calculated…

Energy-saving framework for passive optical networks with ONU sleep/doze mode.

PubMed

Van, Dung Pham; Valcarenghi, Luca; Dias, Maluge Pubuduni Imali; Kondepu, Koteswararao; Castoldi, Piero; Wong, Elaine

2015-02-09

This paper proposes an energy-saving passive optical network framework (ESPON) that aims to incorporate optical network unit (ONU) sleep/doze mode into dynamic bandwidth allocation (DBA) algorithms to reduce ONU energy consumption. In the ESPON, the optical line terminal (OLT) schedules both downstream (DS) and upstream (US) transmissions in the same slot in an online and dynamic fashion whereas the ONU enters sleep mode outside the slot. The ONU sleep time is maximized based on both DS and US traffic. Moreover, during the slot, the ONU might enter doze mode when only its transmitter is idle to further improve energy efficiency. The scheduling order of data transmission, control message exchange, sleep period, and doze period defines an energy-efficient scheme under the ESPON. Three schemes are designed and evaluated in an extensive FPGA-based evaluation. Results show that whilst all the schemes significantly save ONU energy for different evaluation scenarios, the scheduling order has great impact on their performance. In addition, the ESPON allows for a scheduling order that saves ONU energy independently of the network reach.

Design Considerations for a New Terminal Area Arrival Scheduler

NASA Technical Reports Server (NTRS)

Thipphavong, Jane; Mulfinger, Daniel

2010-01-01

Design of a terminal area arrival scheduler depends on the interrelationship between throughput, delay and controller intervention. The main contribution of this paper is an analysis of the above interdependence for several stochastic behaviors of expected system performance distributions in the aircraft s time of arrival at the meter fix and runway. Results of this analysis serve to guide the scheduler design choices for key control variables. Two types of variables are analyzed, separation buffers and terminal delay margins. The choice for these decision variables was tested using sensitivity analysis. Analysis suggests that it is best to set the separation buffer at the meter fix to its minimum and adjust the runway buffer to attain the desired system performance. Delay margin was found to have the least effect. These results help characterize the variables most influential in the scheduling operations of terminal area arrivals.

Efficient operation scheduling for adsorption chillers using predictive optimization-based control methods

NASA Astrophysics Data System (ADS)

Bürger, Adrian; Sawant, Parantapa; Bohlayer, Markus; Altmann-Dieses, Angelika; Braun, Marco; Diehl, Moritz

2017-10-01

Within this work, the benefits of using predictive control methods for the operation of Adsorption Cooling Machines (ACMs) are shown on a simulation study. Since the internal control decisions of series-manufactured ACMs often cannot be influenced, the work focuses on optimized scheduling of an ACM considering its internal functioning as well as forecasts for load and driving energy occurrence. For illustration, an assumed solar thermal climate system is introduced and a system model suitable for use within gradient-based optimization methods is developed. The results of a system simulation using a conventional scheme for ACM scheduling are compared to the results of a predictive, optimization-based scheduling approach for the same exemplary scenario of load and driving energy occurrence. The benefits of the latter approach are shown and future actions for application of these methods for system control are addressed.

Research on crude oil storage and transportation based on optimization algorithm

NASA Astrophysics Data System (ADS)

Yuan, Xuhua

2018-04-01

At present, the optimization theory and method have been widely used in the optimization scheduling and optimal operation scheme of complex production systems. Based on C++Builder 6 program development platform, the theoretical research results are implemented by computer. The simulation and intelligent decision system of crude oil storage and transportation inventory scheduling are designed. The system includes modules of project management, data management, graphics processing, simulation of oil depot operation scheme. It can realize the optimization of the scheduling scheme of crude oil storage and transportation system. A multi-point temperature measuring system for monitoring the temperature field of floating roof oil storage tank is developed. The results show that by optimizing operating parameters such as tank operating mode and temperature, the total transportation scheduling costs of the storage and transportation system can be reduced by 9.1%. Therefore, this method can realize safe and stable operation of crude oil storage and transportation system.

Coordination of appointments for anesthesia care outside of operating rooms using an enterprise-wide scheduling system.

PubMed

Dexter, Franklin; Xiao, Yan; Dow, Angella J; Strader, Melissa M; Ho, Danny; Wachtel, Ruth E

2007-12-01

An anesthesia department implemented scheduling of anesthetics outside of operating rooms (non-OR) by clerks and nurses from other departments using its hospital's enterprise-wide scheduling system. Observational studies chronicled the change over 2 yr as non-OR time was allocated by specialty, and nonanesthesia clerks and nurses scheduled anesthesia teams. Experimental studies investigated how tabular and graphical displays affected the scheduling of milestones (e.g., NPO times) and appointments before anesthetics. Anesthetics performed in allocated time increased progressively from 0% to 75%. Scheduling of anesthetics by nonanesthesia clerks and nurses increased progressively from 0% to 77%. Consistency of patient instructions was improved. The quality of resulting schedules was good. Implementation was not associated with worsening of multiple operational measures of performance such as cancellation rates, turnover times, or complaints. However, schedulers struggled to understand fasting and arrival times of patients, despite using a web site with statistically generated values in tabular formats. Experiments revealed that people ignored their knowledge that anesthetics can start earlier than scheduled. Participants made good decisions with both tabular and graphical displays when scheduling appointments preceding anesthesia. Enterprise-wide scheduling can coordinate anesthetics with other appointments on the same date and improve consistency and accuracy of patient instructions customized to the probability of an anesthetic starting early. The usefulness of implementation depends on the value in having more patient-centered care and/or in having patients arrive just in time for non-OR anesthesia, surgery, or regional block placement (e.g., at facilities with limited physical space).

Dynamic Divisive Normalization Predicts Time-Varying Value Coding in Decision-Related Circuits

PubMed Central

LoFaro, Thomas; Webb, Ryan; Glimcher, Paul W.

2014-01-01

Normalization is a widespread neural computation, mediating divisive gain control in sensory processing and implementing a context-dependent value code in decision-related frontal and parietal cortices. Although decision-making is a dynamic process with complex temporal characteristics, most models of normalization are time-independent and little is known about the dynamic interaction of normalization and choice. Here, we show that a simple differential equation model of normalization explains the characteristic phasic-sustained pattern of cortical decision activity and predicts specific normalization dynamics: value coding during initial transients, time-varying value modulation, and delayed onset of contextual information. Empirically, we observe these predicted dynamics in saccade-related neurons in monkey lateral intraparietal cortex. Furthermore, such models naturally incorporate a time-weighted average of past activity, implementing an intrinsic reference-dependence in value coding. These results suggest that a single network mechanism can explain both transient and sustained decision activity, emphasizing the importance of a dynamic view of normalization in neural coding. PMID:25429145

Quantum decision-maker theory and simulation

NASA Astrophysics Data System (ADS)

Zak, Michail; Meyers, Ronald E.; Deacon, Keith S.

2000-07-01

A quantum device simulating the human decision making process is introduced. It consists of quantum recurrent nets generating stochastic processes which represent the motor dynamics, and of classical neural nets describing the evolution of probabilities of these processes which represent the mental dynamics. The autonomy of the decision making process is achieved by a feedback from the mental to motor dynamics which changes the stochastic matrix based upon the probability distribution. This feedback replaces unavailable external information by an internal knowledge- base stored in the mental model in the form of probability distributions. As a result, the coupled motor-mental dynamics is described by a nonlinear version of Markov chains which can decrease entropy without an external source of information. Applications to common sense based decisions as well as to evolutionary games are discussed. An example exhibiting self-organization is computed using quantum computer simulation. Force on force and mutual aircraft engagements using the quantum decision maker dynamics are considered.

Integrating Solar PV in Utility System Operations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mills, A.; Botterud, A.; Wu, J.

2013-10-31

This study develops a systematic framework for estimating the increase in operating costs due to uncertainty and variability in renewable resources, uses the framework to quantify the integration costs associated with sub-hourly solar power variability and uncertainty, and shows how changes in system operations may affect these costs. Toward this end, we present a statistical method for estimating the required balancing reserves to maintain system reliability along with a model for commitment and dispatch of the portfolio of thermal and renewable resources at different stages of system operations. We estimate the costs of sub-hourly solar variability, short-term forecast errors, andmore » day-ahead (DA) forecast errors as the difference in production costs between a case with “realistic” PV (i.e., subhourly solar variability and uncertainty are fully included in the modeling) and a case with “well behaved” PV (i.e., PV is assumed to have no sub-hourly variability and can be perfectly forecasted). In addition, we highlight current practices that allow utilities to compensate for the issues encountered at the sub-hourly time frame with increased levels of PV penetration. In this analysis we use the analytical framework to simulate utility operations with increasing deployment of PV in a case study of Arizona Public Service Company (APS), a utility in the southwestern United States. In our analysis, we focus on three processes that are important in understanding the management of PV variability and uncertainty in power system operations. First, we represent the decisions made the day before the operating day through a DA commitment model that relies on imperfect DA forecasts of load and wind as well as PV generation. Second, we represent the decisions made by schedulers in the operating day through hour-ahead (HA) scheduling. Peaking units can be committed or decommitted in the HA schedules and online units can be redispatched using forecasts that are improved relative to DA forecasts, but still imperfect. Finally, we represent decisions within the operating hour by schedulers and transmission system operators as real-time (RT) balancing. We simulate the DA and HA scheduling processes with a detailed unit-commitment (UC) and economic dispatch (ED) optimization model. This model creates a least-cost dispatch and commitment plan for the conventional generating units using forecasts and reserve requirements as inputs. We consider only the generation units and load of the utility in this analysis; we do not consider opportunities to trade power with neighboring utilities. We also do not consider provision of reserves from renewables or from demand-side options. We estimate dynamic reserve requirements in order to meet reliability requirements in the RT operations, considering the uncertainty and variability in load, solar PV, and wind resources. Balancing reserve requirements are based on the 2.5th and 97.5th percentile of 1-min deviations from the HA schedule in a previous year. We then simulate RT deployment of balancing reserves using a separate minute-by-minute simulation of deviations from the HA schedules in the operating year. In the simulations we assume that balancing reserves can be fully deployed in 10 min. The minute-by-minute deviations account for HA forecasting errors and the actual variability of the load, wind, and solar generation. Using these minute-by-minute deviations and deployment of balancing reserves, we evaluate the impact of PV on system reliability through the calculation of the standard reliability metric called Control Performance Standard 2 (CPS2). Broadly speaking, the CPS2 score measures the percentage of 10-min periods in which a balancing area is able to balance supply and demand within a specific threshold. Compliance with the North American Electric Reliability Corporation (NERC) reliability standards requires that the CPS2 score must exceed 90% (i.e., the balancing area must maintain adequate balance for 90% of the 10-min periods). The combination of representing DA forecast errors in the DA commitments, using 1-min PV data to simulate RT balancing, and estimates of reliability performance through the CPS2 metric, all factors that are important to operating systems with increasing amounts of PV, makes this study unique in its scope.« less

Integrated Traffic Flow Management Decision Making

NASA Technical Reports Server (NTRS)

Grabbe, Shon R.; Sridhar, Banavar; Mukherjee, Avijit

2009-01-01

A generalized approach is proposed to support integrated traffic flow management decision making studies at both the U.S. national and regional levels. It can consider tradeoffs between alternative optimization and heuristic based models, strategic versus tactical flight controls, and system versus fleet preferences. Preliminary testing was accomplished by implementing thirteen unique traffic flow management models, which included all of the key components of the system and conducting 85, six-hour fast-time simulation experiments. These experiments considered variations in the strategic planning look-ahead times, the replanning intervals, and the types of traffic flow management control strategies. Initial testing indicates that longer strategic planning look-ahead times and re-planning intervals result in steadily decreasing levels of sector congestion for a fixed delay level. This applies when accurate estimates of the air traffic demand, airport capacities and airspace capacities are available. In general, the distribution of the delays amongst the users was found to be most equitable when scheduling flights using a heuristic scheduling algorithm, such as ration-by-distance. On the other hand, equity was the worst when using scheduling algorithms that took into account the number of seats aboard each flight. Though the scheduling algorithms were effective at alleviating sector congestion, the tactical rerouting algorithm was the primary control for avoiding en route weather hazards. Finally, the modeled levels of sector congestion, the number of weather incursions, and the total system delays, were found to be in fair agreement with the values that were operationally observed on both good and bad weather days.

Evaluation of the Terminal Precision Scheduling and Spacing System for Near-Term NAS Application

NASA Technical Reports Server (NTRS)

Thipphavong, Jane; Martin, Lynne Hazel; Swenson, Harry N.; Lin, Paul; Nguyen, Jimmy

2012-01-01

NASA has developed a capability for terminal area precision scheduling and spacing (TAPSS) to provide higher capacity and more efficiently manage arrivals during peak demand periods. This advanced technology is NASA's vision for the NextGen terminal metering capability. A set of human-in-the-loop experiments was conducted to evaluate the performance of the TAPSS system for near-term implementation. The experiments evaluated the TAPSS system under the current terminal routing infrastructure to validate operational feasibility. A second goal of the study was to measure the benefit of the Center and TRACON advisory tools to help prioritize the requirements for controller radar display enhancements. Simulation results indicate that using the TAPSS system provides benefits under current operations, supporting a 10% increase in airport throughput. Enhancements to Center decision support tools had limited impact on improving the efficiency of terminal operations, but did provide more fuel-efficient advisories to achieve scheduling conformance within 20 seconds. The TRACON controller decision support tools were found to provide the most benefit, by improving the precision in schedule conformance to within 20 seconds, reducing the number of arrivals having lateral path deviations by 50% and lowering subjective controller workload. Overall, the TAPSS system was found to successfully develop an achievable terminal arrival metering plan that was sustainable under heavy traffic demand levels and reduce the complexity of terminal operations when coupled with the use of the terminal controller advisory tools.

Evaluation and Selection of Best Priority Sequencing Rule in Job Shop Scheduling using Hybrid MCDM Technique

NASA Astrophysics Data System (ADS)

Kiran Kumar, Kalla; Nagaraju, Dega; Gayathri, S.; Narayanan, S.

2017-05-01

Priority Sequencing Rules provide the guidance for the order in which the jobs are to be processed at a workstation. The application of different priority rules in job shop scheduling gives different order of scheduling. More experimentation needs to be conducted before a final choice is made to know the best priority sequencing rule. Hence, a comprehensive method of selecting the right choice is essential in managerial decision making perspective. This paper considers seven different priority sequencing rules in job shop scheduling. For evaluation and selection of the best priority sequencing rule, a set of eight criteria are considered. The aim of this work is to demonstrate the methodology of evaluating and selecting the best priority sequencing rule by using hybrid multi criteria decision making technique (MCDM), i.e., analytical hierarchy process (AHP) with technique for order preference by similarity to ideal solution (TOPSIS). The criteria weights are calculated by using AHP whereas the relative closeness values of all priority sequencing rules are computed based on TOPSIS with the help of data acquired from the shop floor of a manufacturing firm. Finally, from the findings of this work, the priority sequencing rules are ranked from most important to least important. The comprehensive methodology presented in this paper is very much essential for the management of a workstation to choose the best priority sequencing rule among the available alternatives for processing the jobs with maximum benefit.

Mirtazapine and ketanserin alter preference for gambling-like schedules of reinforcement in rats.

PubMed

Persons, Amanda L; Tedford, Stephanie E; Celeste Napier, T

2017-07-03

Drug and behavioral addictions have overlapping features, e.g., both manifest preference for larger, albeit costlier, reinforcement options in cost/benefit decision-making tasks. Our prior work revealed that the mixed-function serotonergic compound, mirtazapine, attenuates behaviors by rats motivated by abused drugs. To extend this work to behavioral addictions, here we determined if mirtazapine and/or ketanserin, another mixed-function serotonin-acting compound, can alter decision-making in rats that is independent of drug (or food)-motivated reward. Accordingly, we developed a novel variable-ratio task in rats wherein intracranial self-stimulation was used as the positive reinforcer. Using lever pressing for various levels of brain stimulation, the operant task provided choices between a small brain stimulation current delivered on a fixed-ratio schedule (i.e., a predictable reward) and a large brain stimulation delivered following an unpredictable number of responses (i.e., a variable-ratio schedule). This task allowed for demonstration of individualized preference and detection of shifts in motivational influences during a pharmacological treatment. Once baseline preference was established, we determined that pretreatment with mirtazapine or ketanserin significantly decreased preference for the large reinforcer presented after gambling-like schedules of reinforcement. When the rats were tested the next day without drug, preference for the unpredictable large reinforcer option was restored. These data demonstrate that mirtazapine and ketanserin can reduce preference for larger, costlier reinforcement options, and illustrate the potential for these drugs to alter behavior. Copyright © 2017 Elsevier Inc. All rights reserved.

Flexible Demand Management under Time-Varying Prices

NASA Astrophysics Data System (ADS)

Liang, Yong

In this dissertation, the problem of flexible demand management under time-varying prices is studied. This generic problem has many applications, which usually have multiple periods in which decisions on satisfying demand need to be made, and prices in these periods are time-varying. Examples of such applications include multi-period procurement problem, operating room scheduling, and user-end demand scheduling in the Smart Grid, where the last application is used as the main motivating story throughout the dissertation. The current grid is experiencing an upgrade with lots of new designs. What is of particular interest is the idea of passing time-varying prices that reflect electricity market conditions to end users as incentives for load shifting. One key component, consequently, is the demand management system at the user-end. The objective of the system is to find the optimal trade-off between cost saving and discomfort increment resulted from load shifting. In this dissertation, we approach this problem from the following aspects: (1) construct a generic model, solve for Pareto optimal solutions, and analyze the robust solution that optimizes the worst-case payoffs, (2) extend to a distribution-free model for multiple types of demand (appliances), for which an approximate dynamic programming (ADP) approach is developed, and (3) design other efficient algorithms for practical purposes of the flexible demand management system. We first construct a novel multi-objective flexible demand management model, in which there are a finite number of periods with time-varying prices, and demand arrives in each period. In each period, the decision maker chooses to either satisfy or defer outstanding demand to minimize costs and discomfort over a certain number of periods. We consider both the deterministic model, models with stochastic demand or prices, and when only partial information about the stochastic demand or prices is known. We first analyze the stochastic optimization problem when the objective is to minimize the expected total cost and discomfort, then since the decision maker is likely to be risk-averse, and she wants to protect herself from price spikes, we study the robust optimization problem to address the risk-aversion of the decision maker. We conduct numerical studies to evaluate the price of robustness. Next, we present a detailed model that manages multiple types of flexible demand in the absence of knowledge regarding the distributions of related stochastic processes. Specifically, we consider the case in which time-varying prices with general structures are offered to users, and an energy management system for each household makes optimal energy usage, storage, and trading decisions according to the preferences of users. Because of the uncertainties associated with electricity prices, local generation, and the arrival processes of demand, we formulate a stochastic dynamic programming model, and outline a novel and tractable ADP approach to overcome the curses of dimensionality. Then, we perform numerical studies, whose results demonstrate the effectiveness of the ADP approach. At last, we propose another approximation approach based on Q-learning. In addition, we also develop another decentralization-based heuristic. Both the Q-learning approach and the heuristic make necessary assumptions on the knowledge of information, and each of them has unique advantages. We conduct numerical studies on a testing problem. The simulation results show that both the Q-learning and the decentralization based heuristic approaches work well. Lastly, we conclude the paper with some discussions on future extension directions.

Investigations into Generalization of Constraint-Based Scheduling Theories with Applications to Space Telescope Observation Scheduling

NASA Technical Reports Server (NTRS)

Muscettola, Nicola; Smith, Steven S.

1996-01-01

This final report summarizes research performed under NASA contract NCC 2-531 toward generalization of constraint-based scheduling theories and techniques for application to space telescope observation scheduling problems. Our work into theories and techniques for solution of this class of problems has led to the development of the Heuristic Scheduling Testbed System (HSTS), a software system for integrated planning and scheduling. Within HSTS, planning and scheduling are treated as two complementary aspects of the more general process of constructing a feasible set of behaviors of a target system. We have validated the HSTS approach by applying it to the generation of observation schedules for the Hubble Space Telescope. This report summarizes the HSTS framework and its application to the Hubble Space Telescope domain. First, the HSTS software architecture is described, indicating (1) how the structure and dynamics of a system is modeled in HSTS, (2) how schedules are represented at multiple levels of abstraction, and (3) the problem solving machinery that is provided. Next, the specific scheduler developed within this software architecture for detailed management of Hubble Space Telescope operations is presented. Finally, experimental performance results are given that confirm the utility and practicality of the approach.

A decision support tool for synchronizing technology advances with strategic mission objectives

NASA Technical Reports Server (NTRS)

Hornstein, Rhoda S.; Willoughby, John K.

1992-01-01

Successful accomplishment of the objectives of many long-range future missions in areas such as space systems, land-use planning, and natural resource management requires significant technology developments. This paper describes the development of a decision-support data-derived tool called MisTec for helping strategic planners to determine technology development alternatives and to synchronize the technology development schedules with the performance schedules of future long-term missions. Special attention is given to the operations, concept, design, and functional capabilities of the MisTec. The MisTec was initially designed for manned Mars mission, but can be adapted to support other high-technology long-range strategic planning situations, making it possible for a mission analyst, planner, or manager to describe a mission scenario, determine the technology alternatives for making the mission achievable, and to plan the R&D activity necessary to achieve the required technology advances.

Clinic Workflow Simulations using Secondary EHR Data

PubMed Central

Hribar, Michelle R.; Biermann, David; Read-Brown, Sarah; Reznick, Leah; Lombardi, Lorinna; Parikh, Mansi; Chamberlain, Winston; Yackel, Thomas R.; Chiang, Michael F.

2016-01-01

Clinicians today face increased patient loads, decreased reimbursements and potential negative productivity impacts of using electronic health records (EHR), but have little guidance on how to improve clinic efficiency. Discrete event simulation models are powerful tools for evaluating clinical workflow and improving efficiency, particularly when they are built from secondary EHR timing data. The purpose of this study is to demonstrate that these simulation models can be used for resource allocation decision making as well as for evaluating novel scheduling strategies in outpatient ophthalmology clinics. Key findings from this study are that: 1) secondary use of EHR timestamp data in simulation models represents clinic workflow, 2) simulations provide insight into the best allocation of resources in a clinic, 3) simulations provide critical information for schedule creation and decision making by clinic managers, and 4) simulation models built from EHR data are potentially generalizable. PMID:28269861

Test and Evaluation for Enhanced Security: A Quantitative Method to Incorporate Expert Knowledge into Test Planning Decisions.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rizzo, Davinia; Blackburn, Mark

Complex systems are comprised of technical, social, political and environmental factors as well as the programmatic factors of cost, schedule and risk. Testing these systems for enhanced security requires expert knowledge in many different fields. It is important to test these systems to ensure effectiveness, but testing is limited to due cost, schedule, safety, feasibility and a myriad of other reasons. Without an effective decision framework for Test and Evaluation (T&E) planning that can take into consideration technical as well as programmatic factors and leverage expert knowledge, security in complex systems may not be assessed effectively. Therefore, this paper coversmore » the identification of the current T&E planning problem and an approach to include the full variety of factors and leverage expert knowledge in T&E planning through the use of Bayesian Networks (BN).« less

Framing of task performance strategies: effects on performance in a multiattribute dynamic decision making environment.

PubMed

Nygren, T E

1997-09-01

It is well documented that the way a static choice task is "framed" can dramatically alter choice behavior, often leading to observable preference reversals. This framing effect appears to result from perceived changes in the nature or location of a person's initial reference point, but it is not clear how framing effects might generalize to performance on dynamic decision making tasks that are characterized by high workload, time constraints, risk, or stress. A study was conducted to examine the hypothesis that framing can introduce affective components to the decision making process and can influence, either favorably (positive frame) or adversely (negative frame), the implementation and use of decision making strategies in dynamic high-workload environments. Results indicated that negative frame participants were significantly impaired in developing and employing a simple optimal decision strategy relative to a positive frame group. Discussion focuses on implications of these results for models of dynamic decision making.

Dynamic Integration of Value Information into a Common Probability Currency as a Theory for Flexible Decision Making

PubMed Central

Christopoulos, Vassilios; Schrater, Paul R.

2015-01-01

Decisions involve two fundamental problems, selecting goals and generating actions to pursue those goals. While simple decisions involve choosing a goal and pursuing it, humans evolved to survive in hostile dynamic environments where goal availability and value can change with time and previous actions, entangling goal decisions with action selection. Recent studies suggest the brain generates concurrent action-plans for competing goals, using online information to bias the competition until a single goal is pursued. This creates a challenging problem of integrating information across diverse types, including both the dynamic value of the goal and the costs of action. We model the computations underlying dynamic decision-making with disparate value types, using the probability of getting the highest pay-off with the least effort as a common currency that supports goal competition. This framework predicts many aspects of decision behavior that have eluded a common explanation. PMID:26394299

How do current irrigation practices perform? Evaluation of different irrigation scheduling approaches based on experiements and crop model simulations

NASA Astrophysics Data System (ADS)

Seidel, Sabine J.; Werisch, Stefan; Barfus, Klemens; Wagner, Michael; Schütze, Niels; Laber, Hermann

2014-05-01

The increasing worldwide water scarcity, costs and negative off-site effects of irrigation are leading to the necessity of developing methods of irrigation that increase water productivity. Various approaches are available for irrigation scheduling. Traditionally schedules are calculated based on soil water balance (SWB) calculations using some measure of reference evaporation and empirical crop coeffcients. These crop-specific coefficients are provided by the FAO but are also available for different regions (e.g. Germany). The approach is simple but there are several inaccuracies due to simplifications and limitations such as poor transferability. Crop growth models - which simulate the main physiological plant processes through a set of assumptions and calibration parameter - are widely used to support decision making, but also for yield gap or scenario analyses. One major advantage of mechanistic models compared to empirical approaches is their spatial and temporal transferability. Irrigation scheduling can also be based on measurements of soil water tension which is closely related to plant stress. Advantages of precise and easy measurements are able to be automated but face difficulties of finding the place where to probe especially in heterogenous soils. In this study, a two-year field experiment was used to extensively evaluate the three mentioned irrigation scheduling approaches regarding their efficiency on irrigation water application with the aim to promote better agronomic practices in irrigated horticulture. To evaluate the tested irrigation scheduling approaches, an extensive plant and soil water data collection was used to precisely calibrate the mechanistic crop model Daisy. The experiment was conducted with white cabbage (Brassica oleracea L.) on a sandy loamy field in 2012/13 near Dresden, Germany. Hereby, three irrigation scheduling approaches were tested: (i) two schedules were estimated based on SWB calculations using different crop coefficients, and (ii) one treatment was automatically drip irrigated using tensiometers (irrigation of 15 mm at a soil tension of -250 hPa at 30 cm soil depth). In treatment (iii), the irrigation schedule was estimated (using the same critera as in the tension-based treatment) applying the model Daisy partially calibrated against data of 2012. Moreover, one control treatment was minimally irrigated. Measured yield was highest for the tension-based treatment with a low irrigation water input (8.5 DM t/ha, 120 mm). Both SWB treatments showed lower yields and higher irrigation water input (both 8.3 DM t/ha, 306 and 410 mm). The simulation model based treatment yielded lower (7.5 DM t/ha, 106 mm) mainly due to drought stress caused by inaccurate simulation of the soil water dynamics and thus an overestimation of the soil moisture. The evaluation using the calibrated model estimated heavy deep percolation under both SWB treatments. Targeting the challenge to increase water productivity, soil water tension-based irrigation should be favoured. Irrigation scheduling based on SWB calculation requires accurate estimates of crop coefficients. A robust calibration of mechanistic crop models implies a high effort and can be recommended to farmers only to some extent but enables comprehensive crop growth and site analyses.

Chandra mission scheduling on-orbit experience

NASA Astrophysics Data System (ADS)

Bucher, Sabina; Williams, Brent; Pendexter, Misty; Balke, David

2008-07-01

Scheduling observatory time to maximize both day-to-day science target integration time and the lifetime of the observatory is a formidable challenge. Furthermore, it is not a static problem. Of course, every schedule brings a new set of observations, but the boundaries of the problem change as well. As spacecraft ages, its capabilities may degrade. As in-flight experience grows, capabilities may expand. As observing programs are completed, the needs and expectations of the science community may evolve. Changes such as these impact the rules by which a mission scheduled. In eight years on orbit, the Chandra X-Ray Observatory Mission Planning process has adapted to meet the challenge of maximizing day-to-day and mission lifetime science return, despite a consistently evolving set of scheduling constraints. The success of the planning team has been achieved, not through the use of complex algorithms and optimization routines, but through processes and home grown tools that help individuals make smart short term and long term Mission Planning decisions. This paper walks through the processes and tools used to plan and produce mission schedules for the Chandra X-Ray Observatory. Nominal planning and scheduling, target of opportunity response, and recovery from on-board autonomous safing actions are all addressed. Evolution of tools and processes, best practices, and lessons learned are highlighted along the way.

What we were asked to do

NASA Technical Reports Server (NTRS)

1991-01-01

Recommendations are made after 32 interviews, lesson identification, lesson analysis, and mission characteristics identification. The major recommendations are as follows: (1) to develop end-to-end planning and scheduling operations concepts by mission class and to ensure their consideration in system life cycle documentation; (2) to create an organizational infrastructure at the Code 500 level, supported by a Directorate level steering committee with project representation, responsible for systems engineering of end-to-end planning and scheduling systems; (3) to develop and refine mission capabilities to assess impacts of early mission design decisions on planning and scheduling; and (4) to emphasize operational flexibility in the development of the Advanced Space Network, other institutional resources, external (e.g., project) capabilities and resources, operational software and support tools.

T-L Plane Abstraction-Based Energy-Efficient Real-Time Scheduling for Multi-Core Wireless Sensors.

PubMed

Kim, Youngmin; Lee, Ki-Seong; Pham, Ngoc-Son; Lee, Sun-Ro; Lee, Chan-Gun

2016-07-08

Energy efficiency is considered as a critical requirement for wireless sensor networks. As more wireless sensor nodes are equipped with multi-cores, there are emerging needs for energy-efficient real-time scheduling algorithms. The T-L plane-based scheme is known to be an optimal global scheduling technique for periodic real-time tasks on multi-cores. Unfortunately, there has been a scarcity of studies on extending T-L plane-based scheduling algorithms to exploit energy-saving techniques. In this paper, we propose a new T-L plane-based algorithm enabling energy-efficient real-time scheduling on multi-core sensor nodes with dynamic power management (DPM). Our approach addresses the overhead of processor mode transitions and reduces fragmentations of the idle time, which are inherent in T-L plane-based algorithms. Our experimental results show the effectiveness of the proposed algorithm compared to other energy-aware scheduling methods on T-L plane abstraction.

Comparison of 2-Dose and 3-Dose 9-Valent Human Papillomavirus Vaccine Schedules in the United States: A Cost-effectiveness Analysis.

PubMed

Laprise, Jean-François; Markowitz, Lauri E; Chesson, Harrell W; Drolet, Mélanie; Brisson, Marc

2016-09-01

A recent clinical trial using the 9-valent human papillomavirus virus (HPV) vaccine has shown that antibody responses after 2 doses are noninferior to those after 3 doses, suggesting that 2 and 3 doses may have comparable vaccine efficacy. We used an individual-based transmission-dynamic model to compare the population-level effectiveness and cost-effectiveness of 2- and 3-dose schedules of 9-valent HPV vaccine in the United States. Our model predicts that if 2 doses of 9-valent vaccine protect for ≥20 years, the additional benefits of a 3-dose schedule are small as compared to those of 2-dose schedules, and 2-dose schedules are likely much more cost-efficient than 3-dose schedules. © The Author 2016. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail journals.permissions@oup.com.

Coordinated scheduling for dynamic real-time systems

NASA Technical Reports Server (NTRS)

Natarajan, Swaminathan; Zhao, Wei

1994-01-01

In this project, we addressed issues in coordinated scheduling for dynamic real-time systems. In particular, we concentrated on design and implementation of a new distributed real-time system called R-Shell. The design objective of R-Shell is to provide computing support for space programs that have large, complex, fault-tolerant distributed real-time applications. In R-shell, the approach is based on the concept of scheduling agents, which reside in the application run-time environment, and are customized to provide just those resource management functions which are needed by the specific application. With this approach, we avoid the need for a sophisticated OS which provides a variety of generalized functionality, while still not burdening application programmers with heavy responsibility for resource management. In this report, we discuss the R-Shell approach, summarize the achievement of the project, and describe a preliminary prototype of R-Shell system.

Dynamics of rapid dopamine release in the nucleus accumbens during goal-directed behaviors for cocaine versus natural rewards.

PubMed

Cameron, Courtney M; Wightman, R Mark; Carelli, Regina M

2014-11-01

Electrophysiological studies show that distinct subsets of nucleus accumbens (NAc) neurons differentially encode information about goal-directed behaviors for intravenous cocaine versus natural (food/water) rewards. Further, NAc rapid dopamine signaling occurs on a timescale similar to phasic cell firing during cocaine and natural reward-seeking behaviors. However, it is not known whether dopamine signaling is reinforcer specific (i.e., is released during responding for only one type of reinforcer) within discrete NAc locations, similar to neural firing dynamics. Here, fast-scan cyclic voltammetry (FSCV) was used to measure rapid dopamine release during multiple schedules involving sucrose reward and cocaine self-administration (n = 8 rats) and, in a separate group of rats (n = 6), during a sucrose/food multiple schedule. During the sucrose/cocaine multiple schedule, dopamine increased within seconds of operant responding for both reinforcers. Although dopamine release was not reinforcer specific, more subtle differences were observed in peak dopamine concentration [DA] across reinforcer conditions. Specifically, peak [DA] was higher during the first phase of the multiple schedule, regardless of reinforcer type. Further, the time to reach peak [DA] was delayed during cocaine-responding compared to sucrose. During the sucrose/food multiple schedule, increases in dopamine release were also observed relative to operant responding for both natural rewards. However, peak [DA] was higher relative to responding for sucrose than food, regardless of reinforcer order. Overall, the results reveal the dynamics of rapid dopamine signaling in discrete locations in the NAc across reward conditions, and provide novel insight into the functional role of this system in reward-seeking behaviors. Copyright © 2014 Elsevier Ltd. All rights reserved.

Organizational Linkages: Understanding the Productivity Paradox,

DTIC Science & Technology

1994-01-01

students were asked to make a decision regarding a production scheduling. Some used a Lotus spreadsheet’s what-if capacity, which enabled them to...the degree to which managers and MBA students believed that they make better decisions using what-if spreadsheet models, despite the fact that their...for this system is Naylor et al.’s (1980) view of behavior in organizations. When Pritchard and his students (Pritchard et al., 1988) applied this

Short-term scheduling of crude oil operations in refinery with high-fusion-point oil and two transportation pipelines

NASA Astrophysics Data System (ADS)

Wu, NaiQi; Zhu, MengChu; Bai, LiPing; Li, ZhiWu

2016-07-01

In some refineries, storage tanks are located at two different sites, one for low-fusion-point crude oil and the other for high one. Two pipelines are used to transport different oil types. Due to the constraints resulting from the high-fusion-point oil transportation, it is challenging to schedule such a system. This work studies the scheduling problem from a control-theoretic perspective. It proposes to use a hybrid Petri net method to model the system. It then finds the schedulability conditions by analysing the dynamic behaviour of the net model. Next, it proposes an efficient scheduling method to minimize the cost of high-fusion-point oil transportation. Finally, it gives a complex industrial case study to show its application.

Predicting Scheduling and Attending for an Oral Cancer Examination

PubMed Central

Shepperd, James A.; Emanuel, Amber S.; Howell, Jennifer L.; Logan, Henrietta L.

2015-01-01

Background Oral and pharyngeal cancer is highly treatable if diagnosed early, yet late diagnosis is commonplace apparently because of delays in undergoing an oral cancer examination. Purpose We explored predictors of scheduling and attending an oral cancer examination among a sample of Black and White men who were at high risk for oral cancer because they smoked. Methods During an in-person interview, participants (N = 315) from rural Florida learned about oral and pharyngeal cancer, completed survey measures, and were offered a free examination in the next week. Later, participants received a follow-up phone call to explore why they did or did not attend their examination. Results Consistent with the notion that scheduling and attending an oral cancer exam represent distinct decisions, we found that the two outcomes had different predictors. Defensive avoidance and exam efficacy predicted scheduling an examination; exam efficacy and having coping resources, time, and transportation predicted attending the examination. Open-ended responses revealed that the dominant reasons participants offered for missing a scheduled examination was conflicting obligations, forgetting, and confusion or misunderstanding about the examination. Conclusions The results suggest interventions to increase scheduling and attending an oral cancer examination. PMID:26152644

Multi-Objective Approach for Energy-Aware Workflow Scheduling in Cloud Computing Environments

PubMed Central

Kadima, Hubert; Granado, Bertrand

2013-01-01

We address the problem of scheduling workflow applications on heterogeneous computing systems like cloud computing infrastructures. In general, the cloud workflow scheduling is a complex optimization problem which requires considering different criteria so as to meet a large number of QoS (Quality of Service) requirements. Traditional research in workflow scheduling mainly focuses on the optimization constrained by time or cost without paying attention to energy consumption. The main contribution of this study is to propose a new approach for multi-objective workflow scheduling in clouds, and present the hybrid PSO algorithm to optimize the scheduling performance. Our method is based on the Dynamic Voltage and Frequency Scaling (DVFS) technique to minimize energy consumption. This technique allows processors to operate in different voltage supply levels by sacrificing clock frequencies. This multiple voltage involves a compromise between the quality of schedules and energy. Simulation results on synthetic and real-world scientific applications highlight the robust performance of the proposed approach. PMID:24319361

Multi-objective approach for energy-aware workflow scheduling in cloud computing environments.

PubMed

Yassa, Sonia; Chelouah, Rachid; Kadima, Hubert; Granado, Bertrand

2013-01-01

We address the problem of scheduling workflow applications on heterogeneous computing systems like cloud computing infrastructures. In general, the cloud workflow scheduling is a complex optimization problem which requires considering different criteria so as to meet a large number of QoS (Quality of Service) requirements. Traditional research in workflow scheduling mainly focuses on the optimization constrained by time or cost without paying attention to energy consumption. The main contribution of this study is to propose a new approach for multi-objective workflow scheduling in clouds, and present the hybrid PSO algorithm to optimize the scheduling performance. Our method is based on the Dynamic Voltage and Frequency Scaling (DVFS) technique to minimize energy consumption. This technique allows processors to operate in different voltage supply levels by sacrificing clock frequencies. This multiple voltage involves a compromise between the quality of schedules and energy. Simulation results on synthetic and real-world scientific applications highlight the robust performance of the proposed approach.

Interactive Dynamic Mission Scheduling for ASCA

NASA Astrophysics Data System (ADS)

Antunes, A.; Nagase, F.; Isobe, T.

The Japanese X-ray astronomy satellite ASCA (Advanced Satellite for Cosmology and Astrophysics) mission requires scheduling for each 6-month observation phase, further broken down into weekly schedules at a few minutes resolution. Two tools, SPIKE and NEEDLE, written in Lisp and C, use artificial intelligence (AI) techniques combined with a graphic user interface for fast creation and alteration of mission schedules. These programs consider viewing and satellite attitude constraints as well as observer-requested criteria and present an optimized set of solutions for review by the planner. Six-month schedules at 1 day resolution are created for an oversubscribed set of targets by the SPIKE software, originally written for HST and presently being adapted for EUVE, XTE and AXAF. The NEEDLE code creates weekly schedules at 1 min resolution using in-house orbital routines and creates output for processing by the command generation software. Schedule creation on both the long- and short-term scale is rapid, less than 1 day for long-term, and one hour for short-term.

Novel Hybrid Scheduling Technique for Sensor Nodes with Mixed Criticality Tasks

PubMed Central

Micea, Mihai-Victor; Stangaciu, Cristina-Sorina; Stangaciu, Valentin; Curiac, Daniel-Ioan

2017-01-01

Sensor networks become increasingly a key technology for complex control applications. Their potential use in safety- and time-critical domains has raised the need for task scheduling mechanisms specially adapted to sensor node specific requirements, often materialized in predictable jitter-less execution of tasks characterized by different criticality levels. This paper offers an efficient scheduling solution, named Hybrid Hard Real-Time Scheduling (H2RTS), which combines a static, clock driven method with a dynamic, event driven scheduling technique, in order to provide high execution predictability, while keeping a high node Central Processing Unit (CPU) utilization factor. From the detailed, integrated schedulability analysis of the H2RTS, a set of sufficiency tests are introduced and demonstrated based on the processor demand and linear upper bound metrics. The performance and correct behavior of the proposed hybrid scheduling technique have been extensively evaluated and validated both on a simulator and on a sensor mote equipped with ARM7 microcontroller. PMID:28672856

FASTER - A tool for DSN forecasting and scheduling

NASA Technical Reports Server (NTRS)

Werntz, David; Loyola, Steven; Zendejas, Silvino

1993-01-01

FASTER (Forecasting And Scheduling Tool for Earth-based Resources) is a suite of tools designed for forecasting and scheduling JPL's Deep Space Network (DSN). The DSN is a set of antennas and other associated resources that must be scheduled for satellite communications, astronomy, maintenance, and testing. FASTER consists of MS-Windows based programs that replace two existing programs (RALPH and PC4CAST). FASTER was designed to be more flexible, maintainable, and user friendly. FASTER makes heavy use of commercial software to allow for customization by users. FASTER implements scheduling as a two pass process: the first pass calculates a predictive profile of resource utilization; the second pass uses this information to calculate a cost function used in a dynamic programming optimization step. This information allows the scheduler to 'look ahead' at activities that are not as yet scheduled. FASTER has succeeded in allowing wider access to data and tools, reducing the amount of effort expended and increasing the quality of analysis.

DBMS as a Tool for Project Management

NASA Technical Reports Server (NTRS)

Linder, H.

1984-01-01

Scientific objectives of crustal dynamics are listed as well as the contents of the centralized data information system for the crustal dynamics project. The system provides for project observation schedules, gives project configuration control information and project site information.

Dynamic Scheduling for Web Monitoring Crawler

DTIC Science & Technology

2009-02-27

researches on static scheduling methods , but they are not included in this project, because this project mainly focuses on the event-driven...pages from public search engines. This research aims to propose various query generation methods using MCRDR knowledge base and evaluates them to...South Wales Professor Hiroshi Motoda/Osaka University Dr. John Salerno, Air Force Research Laboratory/Information Directorate Report

Evaluation of dose reduction versus standard dosing for maintenance of remission in patients with spondyloarthritis and clinical remission with anti-TNF (REDES-TNF): study protocol for a randomized controlled trial.

PubMed

Pontes, Caridad; Gratacós, Jordi; Torres, Ferran; Avendaño, Cristina; Sanz, Jesús; Vallano, Antoni; Juanola, Xavier; de Miguel, Eugenio; Sanmartí, Raimon; Calvo, Gonzalo

2015-08-20

Dose reduction schedules of tumor necrosis factor antagonists (anti-TNF) as maintenance therapy in patients with spondyloarthritis are used empirically in clinical practice, despite the lack of clinical trials providing evidence for this practice. To address this issue the Spanish Society of Rheumatology (SER) and Spanish Society of Clinical Pharmacology (SEFC) designed a 3-year multicenter, randomized, open-label, controlled clinical trial (2 years for inclusion and 1 year of follow-up). The study is expected to include 190 patients with axial spondyloarthritis on stable maintenance treatment (≥4 months) with any anti-TNF agent at doses recommended in the summary of product characteristics. Patients will be randomized to either a dose reduction arm or maintenance of the dosing regimen as per the official labelling recommendations. Randomization will be stratified according to the anti-TNF agent received before study inclusion. Patient follow-up, visit schedule, and examinations will be maintained as per normal clinical practice recommendations according to SER guidelines. The study aims to test the hypothesis of noninferiority of the dose reduction strategy compared with standard treatment. The first patients were recruited in July 2012, and study completion is scheduled for the end of April 2015. The REDES-TNF study is a pragmatic clinical trial that aims to provide evidence to support a medical decision now made empirically. The study results may help inform clinical decisions relevant to both patients and healthcare decision makers. EudraCT 2011-005871-18 (21 December 2011).

DELPHI AND VALUES,

DTIC Science & Technology

MANAGEMENT PLANNING AND CONTROL, DECISION MAKING), (* DECISION MAKING , GROUP DYNAMICS), (*GROUP DYNAMICS, ATTITUDES(PSYCHOLOGY)), REASONING, REACTION(PSYCHOLOGY), PUBLIC OPINION, PERFORMANCE(HUMAN), QUESTIONNAIRES, FEEDBACK

Negotiating Decisions during Informed Consent for Pediatric Phase I Oncology Trials

PubMed Central

Marshall, Patricia A.; Magtanong, Ruth V.; Leek, Angela C.; Hizlan, Sabahat; Yamokoski, Amy D.; Kodish, Eric D.

2012-01-01

During informed consent conferences (ICCs) for Phase I trials, oncologists must present complex information while addressing concerns. Research on communication that evolves during ICCs remains largely unexplored. We examined communication during ICCs for pediatric Phase I cancer trials using a stratified random sample from six pediatric cancer centers. A grounded theory approach identified key communication steps and factors influencing the negotiation of decisions for trial participation. Analysis suggests that during ICCs, families, patients, and clinicians exercise choice and control by negotiating micro-decisions in two broad domains: drug logic and logistics, and administration/scheduling. Micro-decisions unfold in a four-step communication process: (1) introduction of an issue; (2) response; (3) negotiation of the issue; and (4) resolution and decision. Negotiation over smaller micro-decisions is prominent in ICCs and merits further study. PMID:22565583

Negotiating decisions during informed consent for pediatric Phase I oncology trials.

PubMed

Marshall, Patricia A; Magtanong, Ruth V; Leek, Angela C; Hizlan, Sabahat; Yamokoski, Amy D; Kodish, Eric D

2012-04-01

During informed consent conferences (ICCs) for Phase I trials, oncologists must present complex information while addressing concerns. Research on communication that evolves during ICCs remains largely unexplored. We examined communication during ICCs for pediatric Phase I cancer trials using a stratified random sample from six pediatric cancer centers. A grounded theory approach identified key communication steps and factors influencing the negotiation of decisions for trial participation. Analysis suggests that during ICCs, families, patients, and clinicians exercise choice and control by negotiating micro-decisions in two broad domains: drug logic and logistics, and administration/scheduling. Micro-decisions unfold in a four-step communication process: (1) introduction of an issue; (2) response; (3) negotiation of the issue; and (4) resolution and decision. Negotiation over smaller micro-decisions is prominent in ICCs and merits further study.

Confronting dynamics and uncertainty in optimal decision making for conservation

USGS Publications Warehouse

Williams, Byron K.; Johnson, Fred A.

2013-01-01

The effectiveness of conservation efforts ultimately depends on the recognition that decision making, and the systems that it is designed to affect, are inherently dynamic and characterized by multiple sources of uncertainty. To cope with these challenges, conservation planners are increasingly turning to the tools of decision analysis, especially dynamic optimization methods. Here we provide a general framework for optimal, dynamic conservation and then explore its capacity for coping with various sources and degrees of uncertainty. In broadest terms, the dynamic optimization problem in conservation is choosing among a set of decision options at periodic intervals so as to maximize some conservation objective over the planning horizon. Planners must account for immediate objective returns, as well as the effect of current decisions on future resource conditions and, thus, on future decisions. Undermining the effectiveness of such a planning process are uncertainties concerning extant resource conditions (partial observability), the immediate consequences of decision choices (partial controllability), the outcomes of uncontrolled, environmental drivers (environmental variation), and the processes structuring resource dynamics (structural uncertainty). Where outcomes from these sources of uncertainty can be described in terms of probability distributions, a focus on maximizing the expected objective return, while taking state-specific actions, is an effective mechanism for coping with uncertainty. When such probability distributions are unavailable or deemed unreliable, a focus on maximizing robustness is likely to be the preferred approach. Here the idea is to choose an action (or state-dependent policy) that achieves at least some minimum level of performance regardless of the (uncertain) outcomes. We provide some examples of how the dynamic optimization problem can be framed for problems involving management of habitat for an imperiled species, conservation of a critically endangered population through captive breeding, control of invasive species, construction of biodiversity reserves, design of landscapes to increase habitat connectivity, and resource exploitation. Although these decision making problems and their solutions present significant challenges, we suggest that a systematic and effective approach to dynamic decision making in conservation need not be an onerous undertaking. The requirements are shared with any systematic approach to decision making--a careful consideration of values, actions, and outcomes.

Confronting dynamics and uncertainty in optimal decision making for conservation

NASA Astrophysics Data System (ADS)

Williams, Byron K.; Johnson, Fred A.

2013-06-01

The effectiveness of conservation efforts ultimately depends on the recognition that decision making, and the systems that it is designed to affect, are inherently dynamic and characterized by multiple sources of uncertainty. To cope with these challenges, conservation planners are increasingly turning to the tools of decision analysis, especially dynamic optimization methods. Here we provide a general framework for optimal, dynamic conservation and then explore its capacity for coping with various sources and degrees of uncertainty. In broadest terms, the dynamic optimization problem in conservation is choosing among a set of decision options at periodic intervals so as to maximize some conservation objective over the planning horizon. Planners must account for immediate objective returns, as well as the effect of current decisions on future resource conditions and, thus, on future decisions. Undermining the effectiveness of such a planning process are uncertainties concerning extant resource conditions (partial observability), the immediate consequences of decision choices (partial controllability), the outcomes of uncontrolled, environmental drivers (environmental variation), and the processes structuring resource dynamics (structural uncertainty). Where outcomes from these sources of uncertainty can be described in terms of probability distributions, a focus on maximizing the expected objective return, while taking state-specific actions, is an effective mechanism for coping with uncertainty. When such probability distributions are unavailable or deemed unreliable, a focus on maximizing robustness is likely to be the preferred approach. Here the idea is to choose an action (or state-dependent policy) that achieves at least some minimum level of performance regardless of the (uncertain) outcomes. We provide some examples of how the dynamic optimization problem can be framed for problems involving management of habitat for an imperiled species, conservation of a critically endangered population through captive breeding, control of invasive species, construction of biodiversity reserves, design of landscapes to increase habitat connectivity, and resource exploitation. Although these decision making problems and their solutions present significant challenges, we suggest that a systematic and effective approach to dynamic decision making in conservation need not be an onerous undertaking. The requirements are shared with any systematic approach to decision making—a careful consideration of values, actions, and outcomes.

North Cascades Stehekin Valley Vehicle Decision Document.

DOT National Transportation Integrated Search

2007-08-31

This document serves as technical substantiation in support of a procurement for a fleet of vehicles to be used to operate a scheduled shuttle operation with multiple stops at North Cascades National Park Service Complex (NOCA), in the Stehekin Valle...

76 FR 57023 - Science Advisory Board

Federal Register 2010, 2011, 2012, 2013, 2014

2011-09-15

... DEPARTMENT OF COMMERCE National Oceanic and Atmospheric Administration (NOAA) Science Advisory... forth the schedule and proposed agenda of a forthcoming meeting of the NOAA Science Advisory Board. The... date. SUPPLEMENTARY INFORMATION: The Science Advisory Board (SAB) was established by a Decision...

7 CFR 1470.22 - Conservation stewardship plan.

Code of Federal Regulations, 2010 CFR

2010-01-01

..., DEPARTMENT OF AGRICULTURE LOANS, PURCHASES, AND OTHER OPERATIONS CONSERVATION STEWARDSHIP PROGRAM Contracts... process as outlined in the National Planning Procedures Handbook to encourage participants to address... the participant's decisions that describes the schedule of conservation activities to be implemented...

A decision support system for real-time hydropower scheduling in a competitive power market environment

NASA Astrophysics Data System (ADS)

Shawwash, Ziad Khaled Elias

2000-10-01

The electricity supply market is rapidly changing from a monopolistic to a competitive environment. Being able to operate their system of reservoirs and generating facilities to get maximum benefits out of existing assets and resources is important to the British Columbia Hydro Authority (B.C. Hydro). A decision support system has been developed to help B.C. Hydro operate their system in an optimal way. The system is operational and is one of the tools that are currently used by the B.C. Hydro system operations engineers to determine optimal schedules that meet the hourly domestic load and also maximize the value B.C. Hydro obtains from spot transactions in the Western U.S. and Alberta electricity markets. This dissertation describes the development and implementation of the decision support system in production mode. The decision support system consists of six components: the input data preparation routines, the graphical user interface (GUI), the communication protocols, the hydraulic simulation model, the optimization model, and the results display software. A major part of this work involved the development and implementation of a practical and detailed large-scale optimization model that determines the optimal tradeoff between the long-term value of water and the returns from spot trading transactions in real-time operations. The postmortem-testing phase showed that the gains in value from using the model accounted for 0.25% to 1.0% of the revenues obtained. The financial returns from using the decision support system greatly outweigh the costs of building it. Other benefits are the savings in the time needed to prepare the generation and trading schedules. The system operations engineers now can use the time saved to focus on other important aspects of their job. The operators are currently experimenting with the system in production mode, and are gradually gaining confidence that the advice it provides is accurate, reliable and sensible. The main lesson learned from developing and implementing the system was that there is no alternative to working very closely with the intended end-users of the system, and with the people who have deep knowledge, experience and understanding of how the system is and should be operated.

Optimized Hypervisor Scheduler for Parallel Discrete Event Simulations on Virtual Machine Platforms

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yoginath, Srikanth B; Perumalla, Kalyan S

2013-01-01

With the advent of virtual machine (VM)-based platforms for parallel computing, it is now possible to execute parallel discrete event simulations (PDES) over multiple virtual machines, in contrast to executing in native mode directly over hardware as is traditionally done over the past decades. While mature VM-based parallel systems now offer new, compelling benefits such as serviceability, dynamic reconfigurability and overall cost effectiveness, the runtime performance of parallel applications can be significantly affected. In particular, most VM-based platforms are optimized for general workloads, but PDES execution exhibits unique dynamics significantly different from other workloads. Here we first present results frommore » experiments that highlight the gross deterioration of the runtime performance of VM-based PDES simulations when executed using traditional VM schedulers, quantitatively showing the bad scaling properties of the scheduler as the number of VMs is increased. The mismatch is fundamental in nature in the sense that any fairness-based VM scheduler implementation would exhibit this mismatch with PDES runs. We also present a new scheduler optimized specifically for PDES applications, and describe its design and implementation. Experimental results obtained from running PDES benchmarks (PHOLD and vehicular traffic simulations) over VMs show over an order of magnitude improvement in the run time of the PDES-optimized scheduler relative to the regular VM scheduler, with over 20 reduction in run time of simulations using up to 64 VMs. The observations and results are timely in the context of emerging systems such as cloud platforms and VM-based high performance computing installations, highlighting to the community the need for PDES-specific support, and the feasibility of significantly reducing the runtime overhead for scalable PDES on VM platforms.« less

Footing the bill: the introduction of Medicare Benefits Schedule rebates for podiatry services in Australia.

PubMed

Short, Anthony J

2009-12-07

The introduction of Medicare Benefits Schedule items for allied health professionals in 2004 was a pivotal event in the public funding of non-medical primary care services. This commentary seeks to provide supplementary discussion of the article by Menz (Utilisation of podiatry services in Australia under the Medicare Enhanced Primary Care program, 2004-2008 Journal of Foot and Ankle Research 2009, 2:30), by placing these findings within the context of the podiatry profession, clinical decision making and the broader health workforce and government policy.

Automatic Scheduling and Planning (ASAP) in future ground control systems

NASA Technical Reports Server (NTRS)

Matlin, Sam

1988-01-01

This report describes two complementary approaches to the problem of space mission planning and scheduling. The first is an Expert System or Knowledge-Based System for automatically resolving most of the activity conflicts in a candidate plan. The second is an Interactive Graphics Decision Aid to assist the operator in manually resolving the residual conflicts which are beyond the scope of the Expert System. The two system designs are consistent with future ground control station activity requirements, support activity timing constraints, resource limits and activity priority guidelines.

Emergency material allocation and scheduling for the application to chemical contingency spills under multiple scenarios.

PubMed

Liu, Jie; Guo, Liang; Jiang, Jiping; Jiang, Dexun; Wang, Peng

2017-01-01

In the emergency management relevant to chemical contingency spills, efficiency emergency rescue can be deeply influenced by a reasonable assignment of the available emergency materials to the related risk sources. In this study, an emergency material scheduling model (EMSM) with time-effective and cost-effective objectives is developed to coordinate both allocation and scheduling of the emergency materials. Meanwhile, an improved genetic algorithm (IGA) which includes a revision operation for EMSM is proposed to identify the emergency material scheduling schemes. Then, scenario analysis is used to evaluate optimal emergency rescue scheme under different emergency pollution conditions associated with different threat degrees based on analytic hierarchy process (AHP) method. The whole framework is then applied to a computational experiment based on south-to-north water transfer project in China. The results demonstrate that the developed method not only could guarantee the implementation of the emergency rescue to satisfy the requirements of chemical contingency spills but also help decision makers identify appropriate emergency material scheduling schemes in a balance between time-effective and cost-effective objectives.

Approximation algorithms for scheduling unrelated parallel machines with release dates

NASA Astrophysics Data System (ADS)

Avdeenko, T. V.; Mesentsev, Y. A.; Estraykh, I. V.

2017-01-01

In this paper we propose approaches to optimal scheduling of unrelated parallel machines with release dates. One approach is based on the scheme of dynamic programming modified with adaptive narrowing of search domain ensuring its computational effectiveness. We discussed complexity of the exact schedules synthesis and compared it with approximate, close to optimal, solutions. Also we explain how the algorithm works for the example of two unrelated parallel machines and five jobs with release dates. Performance results that show the efficiency of the proposed approach have been given.

Autonomous scheduling technology for Earth orbital missions

NASA Technical Reports Server (NTRS)

Srivastava, S.

1982-01-01

The development of a dynamic autonomous system (DYASS) of resources for the mission support of near-Earth NASA spacecraft is discussed and the current NASA space data system is described from a functional perspective. The future (late 80's and early 90's) NASA space data system is discussed. The DYASS concept, the autonomous process control, and the NASA space data system are introduced. Scheduling and related disciplines are surveyed. DYASS as a scheduling problem is also discussed. Artificial intelligence and knowledge representation is considered as well as the NUDGE system and the I-Space system.

Dynamic divisive normalization predicts time-varying value coding in decision-related circuits.

PubMed

Louie, Kenway; LoFaro, Thomas; Webb, Ryan; Glimcher, Paul W

2014-11-26

Normalization is a widespread neural computation, mediating divisive gain control in sensory processing and implementing a context-dependent value code in decision-related frontal and parietal cortices. Although decision-making is a dynamic process with complex temporal characteristics, most models of normalization are time-independent and little is known about the dynamic interaction of normalization and choice. Here, we show that a simple differential equation model of normalization explains the characteristic phasic-sustained pattern of cortical decision activity and predicts specific normalization dynamics: value coding during initial transients, time-varying value modulation, and delayed onset of contextual information. Empirically, we observe these predicted dynamics in saccade-related neurons in monkey lateral intraparietal cortex. Furthermore, such models naturally incorporate a time-weighted average of past activity, implementing an intrinsic reference-dependence in value coding. These results suggest that a single network mechanism can explain both transient and sustained decision activity, emphasizing the importance of a dynamic view of normalization in neural coding. Copyright © 2014 the authors 0270-6474/14/3416046-12$15.00/0.

Dynamics of Sequential Decision Making

NASA Astrophysics Data System (ADS)

Rabinovich, Mikhail I.; Huerta, Ramón; Afraimovich, Valentin

2006-11-01

We suggest a new paradigm for intelligent decision-making suitable for dynamical sequential activity of animals or artificial autonomous devices that depends on the characteristics of the internal and external world. To do it we introduce a new class of dynamical models that are described by ordinary differential equations with a finite number of possibilities at the decision points, and also include rules solving this uncertainty. Our approach is based on the competition between possible cognitive states using their stable transient dynamics. The model controls the order of choosing successive steps of a sequential activity according to the environment and decision-making criteria. Two strategies (high-risk and risk-aversion conditions) that move the system out of an erratic environment are analyzed.

Expert system for on-board satellite scheduling and control

NASA Technical Reports Server (NTRS)

Barry, John M.; Sary, Charisse

1988-01-01

An Expert System is described which Rockwell Satellite and Space Electronics Division (S&SED) is developing to dynamically schedule the allocation of on-board satellite resources and activities. This expert system is the Satellite Controller. The resources to be scheduled include power, propellant and recording tape. The activities controlled include scheduling satellite functions such as sensor checkout and operation. The scheduling of these resources and activities is presently a labor intensive and time consuming ground operations task. Developing a schedule requires extensive knowledge of the system and subsystems operations, operational constraints, and satellite design and configuration. This scheduling process requires highly trained experts anywhere from several hours to several weeks to accomplish. The process is done through brute force, that is examining cryptic mnemonic data off line to interpret the health and status of the satellite. Then schedules are formulated either as the result of practical operator experience or heuristics - that is rules of thumb. Orbital operations must become more productive in the future to reduce life cycle costs and decrease dependence on ground control. This reduction is required to increase autonomy and survivability of future systems. The design of future satellites require that the scheduling function be transferred from ground to on board systems.

DisTeam: A decision support tool for surgical team selection

PubMed Central

Ebadi, Ashkan; Tighe, Patrick J.; Zhang, Lei; Rashidi, Parisa

2018-01-01

Objective Surgical service providers play a crucial role in the healthcare system. Amongst all the influencing factors, surgical team selection might affect the patients’ outcome significantly. The performance of a surgical team not only can depend on the individual members, but it can also depend on the synergy among team members, and could possibly influence patient outcome such as surgical complications. In this paper, we propose a tool for facilitating decision making in surgical team selection based on considering history of the surgical team, as well as the specific characteristics of each patient. Methods DisTeam (a decision support tool for surgical team selection) is a metaheuristic framework for objective evaluation of surgical teams and finding the optimal team for a given patient, in terms of number of complications. It identifies a ranked list of surgical teams personalized for each patient, based on prior performance of the surgical teams. DisTeam takes into account the surgical complications associated with teams and their members, their teamwork history, as well as patient’s specific characteristics such as age, body mass index (BMI) and Charlson comorbidity index score. Results We tested DisTeam using intra-operative data from 6065 unique orthopedic surgery cases. Our results suggest high effectiveness of the proposed system in a health-care setting. The proposed framework converges quickly to the optimal solution and provides two sets of answers: a) The best surgical team over all the generations, and b) The best population which consists of different teams that can be used as an alternative solution. This increases the flexibility of the system as a complementary decision support tool. Conclusion DisTeam is a decision support tool for assisting in surgical team selection. It can facilitate the job of scheduling personnel in the hospital which involves an overwhelming number of factors pertaining to patients, individual team members, and team dynamics and can be used to compose patient-personalized surgical teams with minimum (potential) surgical complications. PMID:28363285

DisTeam: A decision support tool for surgical team selection.

PubMed

Ebadi, Ashkan; Tighe, Patrick J; Zhang, Lei; Rashidi, Parisa

2017-02-01

Surgical service providers play a crucial role in the healthcare system. Amongst all the influencing factors, surgical team selection might affect the patients' outcome significantly. The performance of a surgical team not only can depend on the individual members, but it can also depend on the synergy among team members, and could possibly influence patient outcome such as surgical complications. In this paper, we propose a tool for facilitating decision making in surgical team selection based on considering history of the surgical team, as well as the specific characteristics of each patient. DisTeam (a decision support tool for surgical team selection) is a metaheuristic framework for objective evaluation of surgical teams and finding the optimal team for a given patient, in terms of number of complications. It identifies a ranked list of surgical teams personalized for each patient, based on prior performance of the surgical teams. DisTeam takes into account the surgical complications associated with teams and their members, their teamwork history, as well as patient's specific characteristics such as age, body mass index (BMI) and Charlson comorbidity index score. We tested DisTeam using intra-operative data from 6065 unique orthopedic surgery cases. Our results suggest high effectiveness of the proposed system in a health-care setting. The proposed framework converges quickly to the optimal solution and provides two sets of answers: a) The best surgical team over all the generations, and b) The best population which consists of different teams that can be used as an alternative solution. This increases the flexibility of the system as a complementary decision support tool. DisTeam is a decision support tool for assisting in surgical team selection. It can facilitate the job of scheduling personnel in the hospital which involves an overwhelming number of factors pertaining to patients, individual team members, and team dynamics and can be used to compose patient-personalized surgical teams with minimum (potential) surgical complications. Copyright © 2017 Elsevier B.V. All rights reserved.

Strategic planning: a biomedical communications model.

PubMed

Barrett, J E

1991-01-01

This article describes a biomedical communications approach to strategic planning. This model produces a short-term plan that allows a department to take the competitive advantage, react to technological change, and make timely decisions on new courses of action. The model calls for self-study, involving staff in brainstorming sessions where options are identified and ideas are prioritized into possible strategies for success. The article recommends that an evaluation and monitoring schedule be implemented after decisions have been made.

A scalable approach to solving dense linear algebra problems on hybrid CPU-GPU systems

DOE PAGES

Song, Fengguang; Dongarra, Jack

2014-10-01

Aiming to fully exploit the computing power of all CPUs and all graphics processing units (GPUs) on hybrid CPU-GPU systems to solve dense linear algebra problems, in this paper we design a class of heterogeneous tile algorithms to maximize the degree of parallelism, to minimize the communication volume, and to accommodate the heterogeneity between CPUs and GPUs. The new heterogeneous tile algorithms are executed upon our decentralized dynamic scheduling runtime system, which schedules a task graph dynamically and transfers data between compute nodes automatically. The runtime system uses a new distributed task assignment protocol to solve data dependencies between tasksmore » without any coordination between processing units. By overlapping computation and communication through dynamic scheduling, we are able to attain scalable performance for the double-precision Cholesky factorization and QR factorization. Finally, our approach demonstrates a performance comparable to Intel MKL on shared-memory multicore systems and better performance than both vendor (e.g., Intel MKL) and open source libraries (e.g., StarPU) in the following three environments: heterogeneous clusters with GPUs, conventional clusters without GPUs, and shared-memory systems with multiple GPUs.« less

Runway Scheduling Using Generalized Dynamic Programming

NASA Technical Reports Server (NTRS)

Montoya, Justin; Wood, Zachary; Rathinam, Sivakumar

2011-01-01

A generalized dynamic programming method for finding a set of pareto optimal solutions for a runway scheduling problem is introduced. The algorithm generates a set of runway fight sequences that are optimal for both runway throughput and delay. Realistic time-based operational constraints are considered, including miles-in-trail separation, runway crossings, and wake vortex separation. The authors also model divergent runway takeoff operations to allow for reduced wake vortex separation. A modeled Dallas/Fort Worth International airport and three baseline heuristics are used to illustrate preliminary benefits of using the generalized dynamic programming method. Simulated traffic levels ranged from 10 aircraft to 30 aircraft with each test case spanning 15 minutes. The optimal solution shows a 40-70 percent decrease in the expected delay per aircraft over the baseline schedulers. Computational results suggest that the algorithm is promising for real-time application with an average computation time of 4.5 seconds. For even faster computation times, two heuristics are developed. As compared to the optimal, the heuristics are within 5% of the expected delay per aircraft and 1% of the expected number of runway operations per hour ad can be 100x faster.

A scalable approach to solving dense linear algebra problems on hybrid CPU-GPU systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Song, Fengguang; Dongarra, Jack

Aiming to fully exploit the computing power of all CPUs and all graphics processing units (GPUs) on hybrid CPU-GPU systems to solve dense linear algebra problems, in this paper we design a class of heterogeneous tile algorithms to maximize the degree of parallelism, to minimize the communication volume, and to accommodate the heterogeneity between CPUs and GPUs. The new heterogeneous tile algorithms are executed upon our decentralized dynamic scheduling runtime system, which schedules a task graph dynamically and transfers data between compute nodes automatically. The runtime system uses a new distributed task assignment protocol to solve data dependencies between tasksmore » without any coordination between processing units. By overlapping computation and communication through dynamic scheduling, we are able to attain scalable performance for the double-precision Cholesky factorization and QR factorization. Finally, our approach demonstrates a performance comparable to Intel MKL on shared-memory multicore systems and better performance than both vendor (e.g., Intel MKL) and open source libraries (e.g., StarPU) in the following three environments: heterogeneous clusters with GPUs, conventional clusters without GPUs, and shared-memory systems with multiple GPUs.« less

RELATING ACCUMULATOR MODEL PARAMETERS AND NEURAL DYNAMICS

PubMed Central

Purcell, Braden A.; Palmeri, Thomas J.

2016-01-01

Accumulator models explain decision-making as an accumulation of evidence to a response threshold. Specific model parameters are associated with specific model mechanisms, such as the time when accumulation begins, the average rate of evidence accumulation, and the threshold. These mechanisms determine both the within-trial dynamics of evidence accumulation and the predicted behavior. Cognitive modelers usually infer what mechanisms vary during decision-making by seeing what parameters vary when a model is fitted to observed behavior. The recent identification of neural activity with evidence accumulation suggests that it may be possible to directly infer what mechanisms vary from an analysis of how neural dynamics vary. However, evidence accumulation is often noisy, and noise complicates the relationship between accumulator dynamics and the underlying mechanisms leading to those dynamics. To understand what kinds of inferences can be made about decision-making mechanisms based on measures of neural dynamics, we measured simulated accumulator model dynamics while systematically varying model parameters. In some cases, decision- making mechanisms can be directly inferred from dynamics, allowing us to distinguish between models that make identical behavioral predictions. In other cases, however, different parameterized mechanisms produce surprisingly similar dynamics, limiting the inferences that can be made based on measuring dynamics alone. Analyzing neural dynamics can provide a powerful tool to resolve model mimicry at the behavioral level, but we caution against drawing inferences based solely on neural analyses. Instead, simultaneous modeling of behavior and neural dynamics provides the most powerful approach to understand decision-making and likely other aspects of cognition and perception. PMID:28392584

[Toward a New Immunization Schedule in Spain, 2016 (Part 1)].

PubMed

Limia-Sánchez, Aurora; Andreu, María Mar; Torres de Mier, María de Viarce; Navarro-Alonso, José Antonio

2016-03-08

The immunization Schedule is a dynamic public health tool that has incorporated different changes over the years influenced by the epidemiologic situation and the scientific evidence. The Immunization Advisory Committee [Ponencia de Programa y Registro de Vacunaciones], as the Interterritorial Council scientific and technical advisory body, carries out assessments of different programmes and vaccines and proposes changes that after approval will be introduced in the Regions schedule. This article is divided into two parts presenting the rationale followed to propose a new schedule for the immunization against diphtheria, tetanus, pertussis, hepatitis B and invasive disease by Haemophilus influenzae type b. This first part is focused in the reasoning to undertake the assessment, the review of the immunization policy and the impact of immunization in Spain, as well as a review of the immunization schedules in similar countries.

A nurse-led model at public academic hospitals maintains high adherence to colorectal cancer surveillance guidelines.

PubMed

Symonds, Erin L; Simpson, Kalindra; Coats, Michelle; Chaplin, Angela; Saxty, Karen; Sandford, Jayne; Young Am, Graeme P; Cock, Charles; Fraser, Robert; Bampton, Peter A

2018-06-18

To examine the compliance of colorectal cancer surveillance decisions for individuals at greater risk with current evidence-based guidelines and to determine whether compliance differs between surveillance models. Prospective auditing of compliance of surveillance decisions with evidence-based guidelines (NHMRC) in two decision-making models: nurse coordinator-led decision making in public academic hospitals and physician-led decision making in private non-academic hospitals. Selected South Australian hospitals participating in the Southern Co-operative Program for the Prevention of Colorectal Cancer (SCOOP). Proportions of recall recommendations that matched NHMRC guideline recommendations (March-May 2015); numbers of surveillance colonoscopies undertaken more than 6 months ahead of schedule (January-December 2015); proportions of significant neoplasia findings during the 15 years of SCOOP operation (2000-2015). For the nurse-led/public academic hospital model, the recall interval recommendation following 398 of 410 colonoscopies (97%) with findings covered by NHMRC guidelines corresponded to the guideline recommendations; for the physician-led/private non-academic hospital model, this applied to 257 of 310 colonoscopies (83%) (P < 0.001). During 2015, 27% of colonoscopies in public academic hospitals (mean, 27 months; SD, 13 months) and 20% of those in private non-academic hospitals (mean, 23 months; SD, 12 months) were performed more than 6 months earlier than scheduled, in most cases because of patient-related factors (symptoms, faecal occult blood test results). The ratio of the numbers of high risk adenomas to cancers increased from 6.6:1 during 2001-2005 to 16:1 during 2011-2015. The nurse-led/public academic hospital model for decisions about colorectal cancer surveillance intervals achieves a high degree of compliance with guideline recommendations, which should relieve burdening of colonoscopy resources.

Offside Decisions by Expert Assistant Referees in Association Football: Perception and Recall of Spatial Positions in Complex Dynamic Events

ERIC Educational Resources Information Center

Gilis, Bart; Helsen, Werner; Catteeuw, Peter; Wagemans, Johan

2008-01-01

This study investigated the offside decision-making process in association football. The first aim was to capture the specific offside decision-making skills in complex dynamic events. Second, we analyzed the type of errors to investigate the factors leading to incorrect decisions. Federation Internationale de Football Association (FIFA; n = 29)…

Optimizing Flight Schedules by an Automated Decision Support System

DTIC Science & Technology

2014-03-01

18 Figure 5-Equation-1 of Grading Pilot-Mission Matches ( Yavuz , 2010) .......................... 22 Figure 6-Equation...2 of Grading Pilot-Mission Matches ( Yavuz , 2010) .......................... 22 Figure 7-Implementation of GRASP ( Yavuz , 2010...23 Figure 8-Overall Process ( Yavuz , 2010

77 FR 46528 - Sunshine Act Meeting

Federal Register 2010, 2011, 2012, 2013, 2014

2012-08-03

... Suspend Final Decisions on Reactor License Applications Pending Completion of Remanded Waste Confidence...-nrc/policy-making/schedule.html . * * * * * The NRC provides reasonable accommodation to individuals... Benefits Branch, at 301-415-6200, TDD: 301-415-2100, or by email at [email protected] . Determinations...

78 FR 21150 - Notice of Lodging of Proposed Amendment to Consent Decree Under the Clean Water Act

Federal Register 2010, 2011, 2012, 2013, 2014

2013-04-09

... forth a phased sequence and schedule for the decision-making process of HRSD and the Localities as they... \\1\\ are evaluating the potential benefits and feasibility of regionalization and consolidation of the...

77 FR 476 - Science Advisory Board

Federal Register 2010, 2011, 2012, 2013, 2014

2012-01-05

... DEPARTMENT OF COMMERCE National Oceanic and Atmospheric Administration (NOAA) Science Advisory... forth the schedule and proposed agenda of a forthcoming meeting of the NOAA Science Advisory Board. The... INFORMATION: The Science Advisory Board (SAB) was established by a Decision Memorandum dated September 25...

Category Learning by Clustering with Extension to Dynamic Environments

DTIC Science & Technology

2010-03-05

and decision making when short- and long-term rewards are in conflict. In a paper published in Psychonomic Bulletin & Review , we examined whether...Navigating through Abstract Decision Spaces: Evaluating the Role of State Generalization in a Dynamic Decision-Making Task. Psychonomic Bulletin & Review , 16

Occupancy schedules learning process through a data mining framework

DOE Office of Scientific and Technical Information (OSTI.GOV)

D'Oca, Simona; Hong, Tianzhen

Building occupancy is a paramount factor in building energy simulations. Specifically, lighting, plug loads, HVAC equipment utilization, fresh air requirements and internal heat gain or loss greatly depends on the level of occupancy within a building. Developing the appropriate methodologies to describe and reproduce the intricate network responsible for human-building interactions are needed. Extrapolation of patterns from big data streams is a powerful analysis technique which will allow for a better understanding of energy usage in buildings. A three-step data mining framework is applied to discover occupancy patterns in office spaces. First, a data set of 16 offices with 10more » minute interval occupancy data, over a two year period is mined through a decision tree model which predicts the occupancy presence. Then a rule induction algorithm is used to learn a pruned set of rules on the results from the decision tree model. Finally, a cluster analysis is employed in order to obtain consistent patterns of occupancy schedules. Furthermore, the identified occupancy rules and schedules are representative as four archetypal working profiles that can be used as input to current building energy modeling programs, such as EnergyPlus or IDA-ICE, to investigate impact of occupant presence on design, operation and energy use in office buildings.« less

Occupancy schedules learning process through a data mining framework

DOE PAGES

D'Oca, Simona; Hong, Tianzhen

2014-12-17

Building occupancy is a paramount factor in building energy simulations. Specifically, lighting, plug loads, HVAC equipment utilization, fresh air requirements and internal heat gain or loss greatly depends on the level of occupancy within a building. Developing the appropriate methodologies to describe and reproduce the intricate network responsible for human-building interactions are needed. Extrapolation of patterns from big data streams is a powerful analysis technique which will allow for a better understanding of energy usage in buildings. A three-step data mining framework is applied to discover occupancy patterns in office spaces. First, a data set of 16 offices with 10more » minute interval occupancy data, over a two year period is mined through a decision tree model which predicts the occupancy presence. Then a rule induction algorithm is used to learn a pruned set of rules on the results from the decision tree model. Finally, a cluster analysis is employed in order to obtain consistent patterns of occupancy schedules. Furthermore, the identified occupancy rules and schedules are representative as four archetypal working profiles that can be used as input to current building energy modeling programs, such as EnergyPlus or IDA-ICE, to investigate impact of occupant presence on design, operation and energy use in office buildings.« less

SARDA Surface Schedulers

NASA Technical Reports Server (NTRS)

Malik, Waqar

2016-01-01

Provide an overview of algorithms used in SARDA (Spot and Runway Departure Advisor) HITL (Human-in-the-Loop) simulation for Dallas Fort-Worth International Airport and Charlotte Douglas International airport. Outline a multi-objective dynamic programming (DP) based algorithm that finds the exact solution to the single runway scheduling (SRS) problem, and discuss heuristics to restrict the search space for the DP based algorithm and provide improvements.

Development of a Dynamic Time Sharing Scheduled Environment Final Report CRADA No. TC-824-94E

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jette, M.; Caliga, D.

Massively parallel computers, such as the Cray T3D, have historically supported resource sharing solely with space sharing. In that method, multiple problems are solved by executing them on distinct processors. This project developed a dynamic time- and space-sharing scheduler to achieve greater interactivity and throughput than could be achieved with space-sharing alone. CRI and LLNL worked together on the design, testing, and review aspects of this project. There were separate software deliverables. CFU implemented a general purpose scheduling system as per the design specifications. LLNL ported the local gang scheduler software to the LLNL Cray T3D. In this approach, processorsmore » are allocated simultaneously to aU components of a parallel program (in a “gang”). Program execution is preempted as needed to provide for interactivity. Programs are also reIocated to different processors as needed to efficiently pack the computer’s torus of processors. In phase one, CRI developed an interface specification after discussions with LLNL for systemlevel software supporting a time- and space-sharing environment on the LLNL T3D. The two parties also discussed interface specifications for external control tools (such as scheduling policy tools, system administration tools) and applications programs. CRI assumed responsibility for the writing and implementation of all the necessary system software in this phase. In phase two, CRI implemented job-rolling on the Cray T3D, a mechanism for preempting a program, saving its state to disk, and later restoring its state to memory for continued execution. LLNL ported its gang scheduler to the LLNL T3D utilizing the CRI interface implemented in phases one and two. During phase three, the functionality and effectiveness of the LLNL gang scheduler was assessed to provide input to CRI time- and space-sharing, efforts. CRI will utilize this information in the development of general schedulers suitable for other sites and future architectures.« less

Decision Model for Planning and Scheduling of Seafood Product Considering Traceability

NASA Astrophysics Data System (ADS)

Agustin; Mawengkang, Herman; Mathelinea, Devy

2018-01-01

Due to the global challenges, it is necessary for an industrial company to integrate production scheduling and distribution planning, in order to be more efficient and to get more economics advantages. This paper presents seafood production planning and scheduling of a seafood manufacture company which produces simultaneously multi kind of seafood products, located at Aceh Province, Indonesia. The perishability nature of fish highly restricts its storage duration and delivery conditions. Traceability is a tracking requirement to check whether the quality of the product is satisfied. The production and distribution planning problem aims to meet customer demand subject to traceability of the seafood product and other restrictions. The problem is modeled as a mixed integer linear program, and then it is solved using neighborhood search approach.

Using the Networked Fire Chief for ego-depletion research: measuring dynamic decision-making effort and performance.

PubMed

Barber, Larissa K; Smit, Brandon W

2014-01-01

This study replicated ego-depletion predictions from the self-control literature in a computer simulation task that requires ongoing decision-making in relation to constantly changing environmental information: the Network Fire Chief (NFC). Ego-depletion led to decreased self-regulatory effort, but not performance, on the NFC task. These effects were also buffered by task enjoyment so that individuals who enjoyed the dynamic decision-making task did not experience ego-depletion effects. These findings confirm that past ego-depletion effects on decision-making are not limited to static or isolated decision-making tasks and can be extended to dynamic, naturalistic decision-making processes more common to naturalistic settings. Furthermore, the NFC simulation provides a methodological mechanism for independently measuring effort and performance when studying ego-depletion.

Modeling Common-Sense Decisions

NASA Astrophysics Data System (ADS)

Zak, Michail

This paper presents a methodology for efficient synthesis of dynamical model simulating a common-sense decision making process. The approach is based upon the extension of the physics' First Principles that includes behavior of living systems. The new architecture consists of motor dynamics simulating actual behavior of the object, and mental dynamics representing evolution of the corresponding knowledge-base and incorporating it in the form of information flows into the motor dynamics. The autonomy of the decision making process is achieved by a feedback from mental to motor dynamics. This feedback replaces unavailable external information by an internal knowledgebase stored in the mental model in the form of probability distributions.

Development of a Just-in-Time Adaptive Intervention for Smoking Cessation Among Korean American Emerging Adults

PubMed Central

Cerrada, Christian Jules; Dzubur, Eldin; Blackman, Kacie C. A.; Mays, Vickie; Shoptaw, Steven; Huh, Jimi

2017-01-01

Purpose Cigarette smoking is a preventable risk factor that contributes to unnecessary lung cancer burden among Korean Americans and there is limited research on effective smoking cessation strategies for this population. Smartphone-based smoking cessation apps that leverage just-in-time adaptive interventions (JITAIs) hold promise for smokers attempting to quit. However, little is known about how to develop and tailor a smoking cessation JITAI for Korean American emerging adult (KAEA) smokers. Method This paper documents the development process of MyQuit USC according to design guidelines for JITAI. Our development process builds on findings from a prior ecological momentary assessment study by using qualitative research methods. Semi-structured interviews and a focus group were conducted to inform which intervention options to offer and the decision rules that dictate their delivery. Results Qualitative findings highlighted that (1) smoking episodes are highly context-driven and that (2) KAEA smokers believe they need personalized cessation strategies tailored to different contexts. Thus, MyQuit USC operates via decision rules that guide the delivery of personalized implementation intentions, which are contingent on dynamic factors, to be delivered “just in time” at user-scheduled, high-risk smoking situations. Conclusion Through an iterative design process, informed by quantitative and qualitative formative research, we developed a smoking cessation JITAI tailored specifically for KAEA smokers. Further testing is under way to optimize future versions of the app with the most effective intervention strategies and decision rules. MyQuit USC has the potential to provide cessation support in real-world settings, when KAEAs need them the most. PMID:28070868

Development of a Just-in-Time Adaptive Intervention for Smoking Cessation Among Korean American Emerging Adults.

PubMed

Cerrada, Christian Jules; Dzubur, Eldin; Blackman, Kacie C A; Mays, Vickie; Shoptaw, Steven; Huh, Jimi

2017-10-01

Cigarette smoking is a preventable risk factor that contributes to unnecessary lung cancer burden among Korean Americans and there is limited research on effective smoking cessation strategies for this population. Smartphone-based smoking cessation apps that leverage just-in-time adaptive interventions (JITAIs) hold promise for smokers attempting to quit. However, little is known about how to develop and tailor a smoking cessation JITAI for Korean American emerging adult (KAEA) smokers. This paper documents the development process of MyQuit USC according to design guidelines for JITAI. Our development process builds on findings from a prior ecological momentary assessment study by using qualitative research methods. Semi-structured interviews and a focus group were conducted to inform which intervention options to offer and the decision rules that dictate their delivery. Qualitative findings highlighted that (1) smoking episodes are highly context-driven and that (2) KAEA smokers believe they need personalized cessation strategies tailored to different contexts. Thus, MyQuit USC operates via decision rules that guide the delivery of personalized implementation intentions, which are contingent on dynamic factors, to be delivered "just in time" at user-scheduled, high-risk smoking situations. Through an iterative design process, informed by quantitative and qualitative formative research, we developed a smoking cessation JITAI tailored specifically for KAEA smokers. Further testing is under way to optimize future versions of the app with the most effective intervention strategies and decision rules. MyQuit USC has the potential to provide cessation support in real-world settings, when KAEAs need them the most.

Covariance-based synaptic plasticity in an attractor network model accounts for fast adaptation in free operant learning.

PubMed

Neiman, Tal; Loewenstein, Yonatan

2013-01-23

In free operant experiments, subjects alternate at will between targets that yield rewards stochastically. Behavior in these experiments is typically characterized by (1) an exponential distribution of stay durations, (2) matching of the relative time spent at a target to its relative share of the total number of rewards, and (3) adaptation after a change in the reward rates that can be very fast. The neural mechanism underlying these regularities is largely unknown. Moreover, current decision-making neural network models typically aim at explaining behavior in discrete-time experiments in which a single decision is made once in every trial, making these models hard to extend to the more natural case of free operant decisions. Here we show that a model based on attractor dynamics, in which transitions are induced by noise and preference is formed via covariance-based synaptic plasticity, can account for the characteristics of behavior in free operant experiments. We compare a specific instance of such a model, in which two recurrently excited populations of neurons compete for higher activity, to the behavior of rats responding on two levers for rewarding brain stimulation on a concurrent variable interval reward schedule (Gallistel et al., 2001). We show that the model is consistent with the rats' behavior, and in particular, with the observed fast adaptation to matching behavior. Further, we show that the neural model can be reduced to a behavioral model, and we use this model to deduce a novel "conservation law," which is consistent with the behavior of the rats.

Robust Gain-Scheduled Fault Tolerant Control for a Transport Aircraft

NASA Technical Reports Server (NTRS)

Shin, Jong-Yeob; Gregory, Irene

2007-01-01

This paper presents an application of robust gain-scheduled control concepts using a linear parameter-varying (LPV) control synthesis method to design fault tolerant controllers for a civil transport aircraft. To apply the robust LPV control synthesis method, the nonlinear dynamics must be represented by an LPV model, which is developed using the function substitution method over the entire flight envelope. The developed LPV model associated with the aerodynamic coefficient uncertainties represents nonlinear dynamics including those outside the equilibrium manifold. Passive and active fault tolerant controllers (FTC) are designed for the longitudinal dynamics of the Boeing 747-100/200 aircraft in the presence of elevator failure. Both FTC laws are evaluated in the full nonlinear aircraft simulation in the presence of the elevator fault and the results are compared to show pros and cons of each control law.

Design Principles and Algorithms for Air Traffic Arrival Scheduling

NASA Technical Reports Server (NTRS)

Erzberger, Heinz; Itoh, Eri

2014-01-01

This report presents design principles and algorithms for building a real-time scheduler of arrival aircraft based on a first-come-first-served (FCFS) scheduling protocol. The algorithms provide the conceptual and computational foundation for the Traffic Management Advisor (TMA) of the Center/terminal radar approach control facilities (TRACON) automation system, which comprises a set of decision support tools for managing arrival traffic at major airports in the United States. The primary objective of the scheduler is to assign arrival aircraft to a favorable landing runway and schedule them to land at times that minimize delays. A further objective of the scheduler is to allocate delays between high-altitude airspace far away from the airport and low-altitude airspace near the airport. A method of delay allocation is described that minimizes the average operating cost in the presence of errors in controlling aircraft to a specified landing time. This report is a revision of an earlier paper first presented as part of an Advisory Group for Aerospace Research and Development (AGARD) lecture series in September 1995. The authors, during vigorous discussions over the details of this paper, felt it was important to the air-trafficmanagement (ATM) community to revise and extend the original 1995 paper, providing more detail and clarity and thereby allowing future researchers to understand this foundational work as the basis for the TMA's scheduling algorithms.

Stochastic Optimization for Unit Commitment-A Review

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zheng, Qipeng P.; Wang, Jianhui; Liu, Andrew L.

2015-07-01

Optimization models have been widely used in the power industry to aid the decision-making process of scheduling and dispatching electric power generation resources, a process known as unit commitment (UC). Since UC's birth, there have been two major waves of revolution on UC research and real life practice. The first wave has made mixed integer programming stand out from the early solution and modeling approaches for deterministic UC, such as priority list, dynamic programming, and Lagrangian relaxation. With the high penetration of renewable energy, increasing deregulation of the electricity industry, and growing demands on system reliability, the next wave ismore » focused on transitioning from traditional deterministic approaches to stochastic optimization for unit commitment. Since the literature has grown rapidly in the past several years, this paper is to review the works that have contributed to the modeling and computational aspects of stochastic optimization (SO) based UC. Relevant lines of future research are also discussed to help transform research advances into real-world applications.« less

A Robust and Energy-Efficient Transport Protocol for Cognitive Radio Sensor Networks

PubMed Central

Salim, Shelly; Moh, Sangman

2014-01-01

A cognitive radio sensor network (CRSN) is a wireless sensor network in which sensor nodes are equipped with cognitive radio. CRSNs benefit from cognitive radio capabilities such as dynamic spectrum access and transmission parameters reconfigurability; but cognitive radio also brings additional challenges and leads to higher energy consumption. Motivated to improve the energy efficiency in CRSNs, we propose a robust and energy-efficient transport protocol (RETP). The novelties of RETP are two-fold: (I) it combines distributed channel sensing and channel decision with centralized schedule-based data transmission; and (II) it differentiates the types of data transmission on the basis of data content and adopts different acknowledgment methods for different transmission types. To the best of our knowledge, no transport layer protocols have yet been designed for CRSNs. Simulation results show that the proposed protocol achieves remarkably longer network lifetime and shorter event-detection delay compared to those achieved with a conventional transport protocol, while simultaneously preserving event-detection reliability. PMID:25333288

Uncertainty exposure causes behavioural sensitization and increases risky decision-making in male rats: toward modelling gambling disorder.

PubMed

Zeeb, Fiona D; Li, Zhaoxia; Fisher, Daniel C; Zack, Martin H; Fletcher, Paul J

2017-11-01

An animal model of gambling disorder, previously known as pathological gambling, could advance our understanding of the disorder and help with treatment development. We hypothesized that repeated exposure to uncertainty during gambling induces behavioural and dopamine (DA) sensitization - similar to chronic exposure to drugs of abuse. Uncertainty exposure (UE) may also increase risky decision-making in an animal model of gambling disorder. Male Sprague Dawley rats received 56 UE sessions, during which animals responded for saccharin according to an unpredictable, variable ratio schedule of reinforcement (VR group). Control animals responded on a predictable, fixed ratio schedule (FR group). Rats yoked to receive unpredictable reward were also included (Y group). Animals were then tested on the Rat Gambling Task (rGT), an analogue of the Iowa Gambling Task, to measure decision-making. Compared with the FR group, the VR and Y groups experienced a greater locomotor response following administration of amphetamine. On the rGT, the FR and Y groups preferred the advantageous options over the risky, disadvantageous options throughout testing (40 sessions). However, rats in the VR group did not have a significant preference for the advantageous options during sessions 20-40. Amphetamine had a small, but significant, effect on decision-making only in the VR group. After rGT testing, only the VR group showed greater hyperactivity following administration of amphetamine compared with the FR group. Reward uncertainty was the only gambling feature modelled. Actively responding for uncertain reward likely sensitized the DA system and impaired the ability to make optimal decisions, modelling some aspects of gambling disorder.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shahidehpour, Mohammad

Integrating 20% or more wind energy into the system and transmitting large sums of wind energy over long distances will require a decision making capability that can handle very large scale power systems with tens of thousands of buses and lines. There is a need to explore innovative analytical and implementation solutions for continuing reliable operations with the most economical integration of additional wind energy in power systems. A number of wind integration solution paths involve the adoption of new operating policies, dynamic scheduling of wind power across interties, pooling integration services, and adopting new transmission scheduling practices. Such practicesmore » can be examined by the decision tool developed by this project. This project developed a very efficient decision tool called Wind INtegration Simulator (WINS) and applied WINS to facilitate wind energy integration studies. WINS focused on augmenting the existing power utility capabilities to support collaborative planning, analysis, and wind integration project implementations. WINS also had the capability of simulating energy storage facilities so that feasibility studies of integrated wind energy system applications can be performed for systems with high wind energy penetrations. The development of WINS represents a major expansion of a very efficient decision tool called POwer Market Simulator (POMS), which was developed by IIT and has been used extensively for power system studies for decades. Specifically, WINS provides the following superiorities; (1) An integrated framework is included in WINS for the comprehensive modeling of DC transmission configurations, including mono-pole, bi-pole, tri-pole, back-to-back, and multi-terminal connection, as well as AC/DC converter models including current source converters (CSC) and voltage source converters (VSC); (2) An existing shortcoming of traditional decision tools for wind integration is the limited availability of user interface, i.e., decision results are often text-based demonstrations. WINS includes a powerful visualization tool and user interface capability for transmission analyses, planning, and assessment, which will be of great interest to power market participants, power system planners and operators, and state and federal regulatory entities; and (3) WINS can handle extended transmission models for wind integration studies. WINS models include limitations on transmission flow as well as bus voltage for analyzing power system states. The existing decision tools often consider transmission flow constraints (dc power flow) alone which could result in the over-utilization of existing resources when analyzing wind integration. WINS can be used to assist power market participants including transmission companies, independent system operators, power system operators in vertically integrated utilities, wind energy developers, and regulatory agencies to analyze economics, security, and reliability of various options for wind integration including transmission upgrades and the planning of new transmission facilities. WINS can also be used by industry for the offline training of reliability and operation personnel when analyzing wind integration uncertainties, identifying critical spots in power system operation, analyzing power system vulnerabilities, and providing credible decisions for examining operation and planning options for wind integration. Researches in this project on wind integration included (1) Development of WINS; (2) Transmission Congestion Analysis in the Eastern Interconnection; (3) Analysis of 2030 Large-Scale Wind Energy Integration in the Eastern Interconnection; (4) Large-scale Analysis of 2018 Wind Energy Integration in the Eastern U.S. Interconnection. The research resulted in 33 papers, 9 presentations, 9 PhD degrees, 4 MS degrees, and 7 awards. The education activities in this project on wind energy included (1) Wind Energy Training Facility Development; (2) Wind Energy Course Development.« less

Relative influence on total cancelled operating room time from patients who are inpatients or outpatients preoperatively.

PubMed

Dexter, Franklin; Maxbauer, Tina; Stout, Carole; Archbold, Laura; Epstein, Richard H

2014-05-01

In previous studies, hospitals' operating room (OR) schedules were influenced markedly by decisions made within a few days of surgery. At least half of ORs had their last case scheduled or changed within 2 working days of surgery. In the current investigation, we studied whether many of these changes were due to patients who were admitted before surgery. We differentiated these "inpatients" from "outpatients" having ambulatory surgery or admitted on the day of surgery. From 21 facilities of a nonacademic health system throughout the United States, N = 5 eight-week periods of cancellation data were obtained. From an academic hospital, N = 8 thirteen-week periods of cancellation data were obtained, including detailed audit data with timestamps of the entire scheduling/rescheduling/cancellation history for each case. (1) In the non-academic health system, outpatients accounted for 1.6% ± 0.1% (SEM) of the scheduled minutes that were cancelled, whereas inpatients accounted for 8.1% ± 0.4%. Consequently, even though inpatients represented much less than half the total scheduled minutes of surgery (16.2% ± 0.5%, P < 0.0001), they accounted for approximately half of the total cancelled minutes (overall P = 0.55, 49% ± 2%; hospitals only P = 0.062, 57% ± 3%). (2) In the nonacademic health system, each 10% increase in a facility's percentage of outpatients making a physical visit to a preoperative clinic (versus only a preoperative phone call) was associated with a 0.0% ± 0.1% absolute decrease in cancelled minutes (P = 0.58). (3) In the academic hospital, inpatients accounted for 22.3% ± 0.4% of the scheduled minutes but most of the total cancelled minutes (70% ± 2%, P < 0.0001). Slightly more than half the total inpatient cancelled minutes (54% ± 1%, P = 0.006) were due to cases scheduled within 1 workday prior to the day of surgery (e.g., Friday for Monday, Monday for Tuesday). During this period, inpatient cancellation rates, measured in minutes, were several-fold larger than outpatient rates (P < 0.0001). Facilities can achieve a ≤2% cancellation rate for patients who are outpatient preoperatively with very few attending a preoperative clinic, when a virtual evaluation is carried out by phone. At least half of the cancelled time at health systems and hospitals is attributable to inpatients, and these patients principally are scheduled within 1 workday of the day of surgery. This is why there are so many changes to the OR schedule within 1 workday before the day of surgery. Hospitals should evaluate the cost-effectiveness of earlier assessments of inpatients. In addition, scheduling office decision-making within 1 workday before surgery should be based on statistical forecasts that include the risks of cancellation and of inpatient add-on cases being scheduled. Hospitals should monitor the performance of their perioperative managers with respect to such behavior.

A De-centralized Scheduling and Load Balancing Algorithm for Heterogeneous Grid Environments

NASA Technical Reports Server (NTRS)

Arora, Manish; Das, Sajal K.; Biswas, Rupak

2002-01-01

In the past two decades, numerous scheduling and load balancing techniques have been proposed for locally distributed multiprocessor systems. However, they all suffer from significant deficiencies when extended to a Grid environment: some use a centralized approach that renders the algorithm unscalable, while others assume the overhead involved in searching for appropriate resources to be negligible. Furthermore, classical scheduling algorithms do not consider a Grid node to be N-resource rich and merely work towards maximizing the utilization of one of the resources. In this paper, we propose a new scheduling and load balancing algorithm for a generalized Grid model of N-resource nodes that not only takes into account the node and network heterogeneity, but also considers the overhead involved in coordinating among the nodes. Our algorithm is decentralized, scalable, and overlaps the node coordination time with that of the actual processing of ready jobs, thus saving valuable clock cycles needed for making decisions. The proposed algorithm is studied by conducting simulations using the Message Passing Interface (MPI) paradigm.

A De-Centralized Scheduling and Load Balancing Algorithm for Heterogeneous Grid Environments

NASA Technical Reports Server (NTRS)

Arora, Manish; Das, Sajal K.; Biswas, Rupak; Biegel, Bryan (Technical Monitor)

2002-01-01

In the past two decades, numerous scheduling and load balancing techniques have been proposed for locally distributed multiprocessor systems. However, they all suffer from significant deficiencies when extended to a Grid environment: some use a centralized approach that renders the algorithm unscalable, while others assume the overhead involved in searching for appropriate resources to be negligible. Furthermore, classical scheduling algorithms do not consider a Grid node to be N-resource rich and merely work towards maximizing the utilization of one of the resources. In this paper we propose a new scheduling and load balancing algorithm for a generalized Grid model of N-resource nodes that not only takes into account the node and network heterogeneity, but also considers the overhead involved in coordinating among the nodes. Our algorithm is de-centralized, scalable, and overlaps the node coordination time of the actual processing of ready jobs, thus saving valuable clock cycles needed for making decisions. The proposed algorithm is studied by conducting simulations using the Message Passing Interface (MPI) paradigm.

Integrated production and distribution scheduling problems related to fixed delivery departure dates and weights of late orders.

PubMed

Li, Shanlin; Li, Maoqin

2015-01-01

We consider an integrated production and distribution scheduling problem faced by a typical make-to-order manufacturer which relies on a third-party logistics (3PL) provider for finished product delivery to customers. In the beginning of a planning horizon, the manufacturer has received a set of orders to be processed on a single production line. Completed orders are delivered to customers by a finite number of vehicles provided by the 3PL company which follows a fixed daily or weekly shipping schedule such that the vehicles have fixed departure dates which are not part of the decisions. The problem is to find a feasible schedule that minimizes one of the following objective functions when processing times and weights are oppositely ordered: (1) the total weight of late orders and (2) the number of vehicles used subject to the condition that the total weight of late orders is minimum. We show that both problems are solvable in polynomial time.

Integrated Production and Distribution Scheduling Problems Related to Fixed Delivery Departure Dates and Weights of Late Orders

PubMed Central

Li, Shanlin; Li, Maoqin

2015-01-01

We consider an integrated production and distribution scheduling problem faced by a typical make-to-order manufacturer which relies on a third-party logistics (3PL) provider for finished product delivery to customers. In the beginning of a planning horizon, the manufacturer has received a set of orders to be processed on a single production line. Completed orders are delivered to customers by a finite number of vehicles provided by the 3PL company which follows a fixed daily or weekly shipping schedule such that the vehicles have fixed departure dates which are not part of the decisions. The problem is to find a feasible schedule that minimizes one of the following objective functions when processing times and weights are oppositely ordered: (1) the total weight of late orders and (2) the number of vehicles used subject to the condition that the total weight of late orders is minimum. We show that both problems are solvable in polynomial time. PMID:25785285

An approach to rescheduling activities based on determination of priority and disruptivity

NASA Technical Reports Server (NTRS)

Sponsler, Jeffrey L.; Johnston, Mark D.

1990-01-01

A constraint-based scheduling system called SPIKE is being used to create long term schedules for the Hubble Space Telescope. Feedback for the spacecraft or from other ground support systems may invalidate some scheduling decisions and those activities concerned must be reconsidered. A function rescheduling priority is defined which for a given activity performs a heuristic analysis and produces a relative numerical value which is used to rank all such entities in the order that they should be rescheduled. A function disruptivity is also defined that is used to place a relative numeric value on how much a pre-existing schedule would be changed in order to reschedule an activity. Using these functions, two algorithms (a stochastic neural network approach and an exhaustive search approach) are proposed to find the best place to reschedule an activity. Prototypes were implemented and preliminary testing reveals that the exhaustive technique produces only marginally better results at much greater computational cost.

Introduction of Sequential Inactivated Polio Vaccine–Oral Polio Vaccine Schedule for Routine Infant Immunization in Brazil’s National Immunization Program

PubMed Central

Domingues, Carla Magda Allan S.; de Fátima Pereira, Sirlene; Marreiros, Ana Carolina Cunha; Menezes, Nair; Flannery, Brendan

2015-01-01

In August 2012, the Brazilian Ministry of Health introduced inactivated polio vaccine (IPV) as part of sequential polio vaccination schedule for all infants beginning their primary vaccination series. The revised childhood immunization schedule included 2 doses of IPV at 2 and 4 months of age followed by 2 doses of oral polio vaccine (OPV) at 6 and 15 months of age. One annual national polio immunization day was maintained to provide OPV to all children aged 6 to 59 months. The decision to introduce IPV was based on preventing rare cases of vaccine-associated paralytic polio, financially sustaining IPV introduction, ensuring equitable access to IPV, and preparing for future OPV cessation following global eradication. Introducing IPV during a national multivaccination campaign led to rapid uptake, despite challenges with local vaccine supply due to high wastage rates. Continuous monitoring is required to achieve high coverage with the sequential polio vaccine schedule. PMID:25316829

Metroplex Optimization Model Expansion and Analysis: The Airline Fleet, Route, and Schedule Optimization Model (AFRS-OM)

NASA Technical Reports Server (NTRS)

Sherry, Lance; Ferguson, John; Hoffman, Karla; Donohue, George; Beradino, Frank

2012-01-01

This report describes the Airline Fleet, Route, and Schedule Optimization Model (AFRS-OM) that is designed to provide insights into airline decision-making with regards to markets served, schedule of flights on these markets, the type of aircraft assigned to each scheduled flight, load factors, airfares, and airline profits. The main inputs to the model are hedged fuel prices, airport capacity limits, and candidate markets. Embedded in the model are aircraft performance and associated cost factors, and willingness-to-pay (i.e. demand vs. airfare curves). Case studies demonstrate the application of the model for analysis of the effects of increased capacity and changes in operating costs (e.g. fuel prices). Although there are differences between airports (due to differences in the magnitude of travel demand and sensitivity to airfare), the system is more sensitive to changes in fuel prices than capacity. Further, the benefits of modernization in the form of increased capacity could be undermined by increases in hedged fuel prices

78 FR 9451 - Academy Express, L.L.C.-Acquisition of Property-Golden Ring Travel & Transportation, Inc.

Federal Register 2010, 2011, 2012, 2013, 2014

2013-02-08

... decision can be made on the record as developed, a procedural schedule will be adopted to reconsider the... Justice, Antitrust Division, 10th Street & Pennsylvania Avenue NW., Washington, DC 20530; and (3) the U.S...

A Novel Decision Support Tool to Develop Link Driving Schedules for Moves.

DOT National Transportation Integrated Search

2015-01-01

A system or user level strategy that aims to reduce emissions from transportation networks requires a rigorous assessment of emissions inventory for the system to justify its effectiveness. It is important to estimate the total emissions for a transp...

How to Choose a Media Retrieval System.

ERIC Educational Resources Information Center

Huber, Joe

1995-01-01

Provides guidelines for schools choosing a media retrieval system. Topics include broadband, baseband, coaxial cable, or fiber optic decisions; the control network; selecting scheduling software; presentation software; device control; control from the classroom; and a comparison of systems offered by five companies. (LRW)

75 FR 19608 - Recreation Resource Advisory Committees

Federal Register 2010, 2011, 2012, 2013, 2014

2010-04-15

...;and investigations, committee meetings, agency decisions and rulings, #0;delegations of authority... tourism official to represent the State; b. A person who represents affected Indian tribes; and c. A... reimbursed for travel and per diem expenses for regularly scheduled committee meetings. All Recreation RAC...

49 CFR 80.5 - Limitations on assistance.

Code of Federal Regulations, 2010 CFR

2010-10-01

... extended construction periods and financing needs. The TIFIA's effectiveness in stimulating private... Significant Impact, or Record of Decision. (g) The Secretary shall fund a secured loan based on the project's financing needs. The credit agreement shall include the anticipated schedule for such loan disbursements...

'Shockley park' stirs racism row

NASA Astrophysics Data System (ADS)

Gwynne, Peter

2009-07-01

A local authority in Northern California has encountered unexpected resistance to its decision to name a park after the Nobel-prize-winning physicist William Shockley, with a coalition of churches and civic groups preparing to petition against the name at a meeting scheduled for 23 July.

5 CFR 9901.222 - Review of classification decisions.

Code of Federal Regulations, 2010 CFR

2010-01-01

....222 Section 9901.222 Administrative Personnel DEPARTMENT OF DEFENSE HUMAN RESOURCES MANAGEMENT AND LABOR RELATIONS SYSTEMS (DEPARTMENT OF DEFENSE-OFFICE OF PERSONNEL MANAGEMENT) DEPARTMENT OF DEFENSE...., pay system, career group, occupational series, official title, pay schedule, or pay band) of his or...

77 FR 58356 - Science Advisory Board

Federal Register 2010, 2011, 2012, 2013, 2014

2012-09-20

... DEPARTMENT OF COMMERCE National Oceanic and Atmospheric Administration Science Advisory Board... the schedule and proposed agenda of a forthcoming meeting of the NOAA Science Advisory Board. The... Science Advisory Board (SAB) was established by a Decision Memorandum dated September 25, 1997, and is the...

Exploiting Vector and Multicore Parallelsim for Recursive, Data- and Task-Parallel Programs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ren, Bin; Krishnamoorthy, Sriram; Agrawal, Kunal

Modern hardware contains parallel execution resources that are well-suited for data-parallelism-vector units-and task parallelism-multicores. However, most work on parallel scheduling focuses on one type of hardware or the other. In this work, we present a scheduling framework that allows for a unified treatment of task- and data-parallelism. Our key insight is an abstraction, task blocks, that uniformly handles data-parallel iterations and task-parallel tasks, allowing them to be scheduled on vector units or executed independently as multicores. Our framework allows us to define schedulers that can dynamically select between executing task- blocks on vector units or multicores. We show that thesemore » schedulers are asymptotically optimal, and deliver the maximum amount of parallelism available in computation trees. To evaluate our schedulers, we develop program transformations that can convert mixed data- and task-parallel pro- grams into task block-based programs. Using a prototype instantiation of our scheduling framework, we show that, on an 8-core system, we can simultaneously exploit vector and multicore parallelism to achieve 14×-108× speedup over sequential baselines.« less

Cost and schedule estimation study report

NASA Technical Reports Server (NTRS)

Condon, Steve; Regardie, Myrna; Stark, Mike; Waligora, Sharon

1993-01-01

This report describes the analysis performed and the findings of a study of the software development cost and schedule estimation models used by the Flight Dynamics Division (FDD), Goddard Space Flight Center. The study analyzes typical FDD projects, focusing primarily on those developed since 1982. The study reconfirms the standard SEL effort estimation model that is based on size adjusted for reuse; however, guidelines for the productivity and growth parameters in the baseline effort model have been updated. The study also produced a schedule prediction model based on empirical data that varies depending on application type. Models for the distribution of effort and schedule by life-cycle phase are also presented. Finally, this report explains how to use these models to plan SEL projects.

Dynamic Modeling of Solar Dynamic Components and Systems

NASA Technical Reports Server (NTRS)

Hochstein, John I.; Korakianitis, T.

1992-01-01

The purpose of this grant was to support NASA in modeling efforts to predict the transient dynamic and thermodynamic response of the space station solar dynamic power generation system. In order to meet the initial schedule requirement of providing results in time to support installation of the system as part of the initial phase of space station, early efforts were executed with alacrity and often in parallel. Initially, methods to predict the transient response of a Rankine as well as a Brayton cycle were developed. Review of preliminary design concepts led NASA to select a regenerative gas-turbine cycle using a helium-xenon mixture as the working fluid and, from that point forward, the modeling effort focused exclusively on that system. Although initial project planning called for a three year period of performance, revised NASA schedules moved system installation to later and later phases of station deployment. Eventually, NASA selected to halt development of the solar dynamic power generation system for space station and to reduce support for this project to two-thirds of the original level.

T-L Plane Abstraction-Based Energy-Efficient Real-Time Scheduling for Multi-Core Wireless Sensors

PubMed Central

Kim, Youngmin; Lee, Ki-Seong; Pham, Ngoc-Son; Lee, Sun-Ro; Lee, Chan-Gun

2016-01-01

Energy efficiency is considered as a critical requirement for wireless sensor networks. As more wireless sensor nodes are equipped with multi-cores, there are emerging needs for energy-efficient real-time scheduling algorithms. The T-L plane-based scheme is known to be an optimal global scheduling technique for periodic real-time tasks on multi-cores. Unfortunately, there has been a scarcity of studies on extending T-L plane-based scheduling algorithms to exploit energy-saving techniques. In this paper, we propose a new T-L plane-based algorithm enabling energy-efficient real-time scheduling on multi-core sensor nodes with dynamic power management (DPM). Our approach addresses the overhead of processor mode transitions and reduces fragmentations of the idle time, which are inherent in T-L plane-based algorithms. Our experimental results show the effectiveness of the proposed algorithm compared to other energy-aware scheduling methods on T-L plane abstraction. PMID:27399722

Nonstandard Work Schedules, Family Dynamics, and Mother-Child Interactions During Early Childhood.

PubMed

Prickett, Kate C

2018-03-01

The rising number of parents who work nonstandard schedules has led to a growing body of research concerned with what this trend means for children. The negative outcomes for children of parents who work nonstandard schedules are thought to arise from the disruptions these schedules place on family life, and thus, the types of parenting that support their children's development, particularly when children are young. Using a nationally representative sample of two-parent families (Early Childhood Longitudinal Study-Birth cohort, n = 3,650), this study examined whether mothers' and their partners' nonstandard work schedules were associated with mothers' parenting when children were 2 and 4 years old. Structural equation models revealed that mothers' and their partners' nonstandard work schedules were associated with mothers' lower scores on measures of positive and involved parenting. These associations were mediated by fathers' lower levels of participation in cognitively supportive parenting and greater imbalance in cognitively supportive tasks conducted by mothers versus fathers.

77 FR 3752 - Commission Information Collection Activities (FERC-725I); Comment Request

Federal Register 2010, 2011, 2012, 2013, 2014

2012-01-25

... the Bulk-Power System to system disturbances, including scheduled and unscheduled outages; requires each reliability coordinator to establish requirements for its area's dynamic disturbance recording... Retention--10.... 10 acquisition and installation of dynamic disturbance recorders. GO, TO, and RC to...

A bicriteria heuristic for an elective surgery scheduling problem.

PubMed

Marques, Inês; Captivo, M Eugénia; Vaz Pato, Margarida

2015-09-01

Resource rationalization and reduction of waiting lists for surgery are two main guidelines for hospital units outlined in the Portuguese National Health Plan. This work is dedicated to an elective surgery scheduling problem arising in a Lisbon public hospital. In order to increase the surgical suite's efficiency and to reduce the waiting lists for surgery, two objectives are considered: maximize surgical suite occupation and maximize the number of surgeries scheduled. This elective surgery scheduling problem consists of assigning an intervention date, an operating room and a starting time for elective surgeries selected from the hospital waiting list. Accordingly, a bicriteria surgery scheduling problem arising in the hospital under study is presented. To search for efficient solutions of the bicriteria optimization problem, the minimization of a weighted Chebyshev distance to a reference point is used. A constructive and improvement heuristic procedure specially designed to address the objectives of the problem is developed and results of computational experiments obtained with empirical data from the hospital are presented. This study shows that by using the bicriteria approach presented here it is possible to build surgical plans with very good performance levels. This method can be used within an interactive approach with the decision maker. It can also be easily adapted to other hospitals with similar scheduling conditions.

Scheduling algorithms for rapid imaging using agile Cubesat constellations

NASA Astrophysics Data System (ADS)

Nag, Sreeja; Li, Alan S.; Merrick, James H.

2018-02-01

Distributed Space Missions such as formation flight and constellations, are being recognized as important Earth Observation solutions to increase measurement samples over space and time. Cubesats are increasing in size (27U, ∼40 kg in development) with increasing capabilities to host imager payloads. Given the precise attitude control systems emerging in the commercial market, Cubesats now have the ability to slew and capture images within short notice. We propose a modular framework that combines orbital mechanics, attitude control and scheduling optimization to plan the time-varying, full-body orientation of agile Cubesats in a constellation such that they maximize the number of observed images and observation time, within the constraints of Cubesat hardware specifications. The attitude control strategy combines bang-bang and PD control, with constraints such as power consumption, response time, and stability factored into the optimality computations and a possible extension to PID control to account for disturbances. Schedule optimization is performed using dynamic programming with two levels of heuristics, verified and improved upon using mixed integer linear programming. The automated scheduler is expected to run on ground station resources and the resultant schedules uplinked to the satellites for execution, however it can be adapted for onboard scheduling, contingent on Cubesat hardware and software upgrades. The framework is generalizable over small steerable spacecraft, sensor specifications, imaging objectives and regions of interest, and is demonstrated using multiple 20 kg satellites in Low Earth Orbit for two case studies - rapid imaging of Landsat's land and coastal images and extended imaging of global, warm water coral reefs. The proposed algorithm captures up to 161% more Landsat images than nadir-pointing sensors with the same field of view, on a 2-satellite constellation over a 12-h simulation. Integer programming was able to verify that optimality of the dynamic programming solution for single satellites was within 10%, and find up to 5% more optimal solutions. The optimality gap for constellations was found to be 22% at worst, but the dynamic programming schedules were found at nearly four orders of magnitude better computational speed than integer programming. The algorithm can include cloud cover predictions, ground downlink windows or any other spatial, temporal or angular constraints into the orbital module and be integrated into planning tools for agile constellations.

Algorithm for decision support as the tool for control system of industries with variable assortment of products

NASA Astrophysics Data System (ADS)

Ladaniuk, Anatolii; Ivashchuk, Viacheslav; Kisała, Piotr; Askarova, Nursanat; Sagymbekova, Azhar

2015-12-01

Conditions of diversification of enterprise products are involving for changes of higher levels of management hierarchy, so it's leading by tasks correcting and changing schedule for operating of production plans. Ordinary solve by combination of enterprise resource are planning and management execution system often has exclusively statistical content. So, the development of decision support system, that helps to use knowledge about subject for capabilities estimating and order of operation of production object is relevant in this time.

Lunar-Ultraviolet Telescope Experiment (LUTE) integrated program plan

NASA Technical Reports Server (NTRS)

Smith, Janice F. (Compiler); Forrest, Larry

1993-01-01

A detailed Lunar Ultraviolet Telescope Experiment (LUTE) program plan representing major decisions and tasks leading to those decisions for program execution are presented. The purpose of this task was to develop an integrated plan of project activities for the LUTE project, and to display the plan as an integrated network that shows the project activities, all critical interfaces, and schedules. The integrated network will provide the project manager with a frame work for strategic planning and risk management throughout the life of the project.

Intelligent data management for real-time spacecraft monitoring

NASA Technical Reports Server (NTRS)

Schwuttke, Ursula M.; Gasser, Les; Abramson, Bruce

1992-01-01

Real-time AI systems have begun to address the challenge of restructuring problem solving to meet real-time constraints by making key trade-offs that pursue less than optimal strategies with minimal impact on system goals. Several approaches for adapting to dynamic changes in system operating conditions are known. However, simultaneously adapting system decision criteria in a principled way has been difficult. Towards this end, a general technique for dynamically making such trade-offs using a combination of decision theory and domain knowledge has been developed. Multi-attribute utility theory (MAUT), a decision theoretic approach for making one-time decisions is discussed and dynamic trade-off evaluation is described as a knowledge-based extension of MAUT that is suitable for highly dynamic real-time environments, and provides an example of dynamic trade-off evaluation applied to a specific data management trade-off in a real-world spacecraft monitoring application.

Sleep Disruption Medical Intervention Forecasting (SDMIF) Module for the Integrated Medical Model

NASA Technical Reports Server (NTRS)

Lewandowski, Beth; Brooker, John; Mallis, Melissa; Hursh, Steve; Caldwell, Lynn; Myers, Jerry

2011-01-01

The NASA Integrated Medical Model (IMM) assesses the risk, including likelihood and impact of occurrence, of all credible in-flight medical conditions. Fatigue due to sleep disruption is a condition that could lead to operational errors, potentially resulting in loss of mission or crew. Pharmacological consumables are mitigation strategies used to manage the risks associated with sleep deficits. The likelihood of medical intervention due to sleep disruption was estimated with a well validated sleep model and a Monte Carlo computer simulation in an effort to optimize the quantity of consumables. METHODS: The key components of the model are the mission parameter program, the calculation of sleep intensity and the diagnosis and decision module. The mission parameter program was used to create simulated daily sleep/wake schedules for an ISS increment. The hypothetical schedules included critical events such as dockings and extravehicular activities and included actual sleep time and sleep quality. The schedules were used as inputs to the Sleep, Activity, Fatigue and Task Effectiveness (SAFTE) Model (IBR Inc., Baltimore MD), which calculated sleep intensity. Sleep data from an ISS study was used to relate calculated sleep intensity to the probability of sleep medication use, using a generalized linear model for binomial regression. A human yes/no decision process using a binomial random number was also factored into sleep medication use probability. RESULTS: These probability calculations were repeated 5000 times resulting in an estimate of the most likely amount of sleep aids used during an ISS mission and a 95% confidence interval. CONCLUSIONS: These results were transferred to the parent IMM for further weighting and integration with other medical conditions, to help inform operational decisions. This model is a potential planning tool for ensuring adequate sleep during sleep disrupted periods of a mission.

Environmental hedging: A theory and method for reconciling reservoir operations for downstream ecology and water supply

NASA Astrophysics Data System (ADS)

Adams, L. E.; Lund, J. R.; Moyle, P. B.; Quiñones, R. M.; Herman, J. D.; O'Rear, T. A.

2017-09-01

Building reservoir release schedules to manage engineered river systems can involve costly trade-offs between storing and releasing water. As a result, the design of release schedules requires metrics that quantify the benefit and damages created by releases to the downstream ecosystem. Such metrics should support making operational decisions under uncertain hydrologic conditions, including drought and flood seasons. This study addresses this need and develops a reservoir operation rule structure and method to maximize downstream environmental benefit while meeting human water demands. The result is a general approach for hedging downstream environmental objectives. A multistage stochastic mixed-integer nonlinear program with Markov Chains, identifies optimal "environmental hedging," releases to maximize environmental benefits subject to probabilistic seasonal hydrologic conditions, current, past, and future environmental demand, human water supply needs, infrastructure limitations, population dynamics, drought storage protection, and the river's carrying capacity. Environmental hedging "hedges bets" for drought by reducing releases for fish, sometimes intentionally killing some fish early to reduce the likelihood of large fish kills and storage crises later. This approach is applied to Folsom reservoir in California to support survival of fall-run Chinook salmon in the lower American River for a range of carryover and initial storage cases. Benefit is measured in terms of fish survival; maintaining self-sustaining native fish populations is a significant indicator of ecosystem function. Environmental hedging meets human demand and outperforms other operating rules, including the current Folsom operating strategy, based on metrics of fish extirpation and water supply reliability.

Collaborative Resource Allocation

NASA Technical Reports Server (NTRS)

Wang, Yeou-Fang; Wax, Allan; Lam, Raymond; Baldwin, John; Borden, Chester

2007-01-01

Collaborative Resource Allocation Networking Environment (CRANE) Version 0.5 is a prototype created to prove the newest concept of using a distributed environment to schedule Deep Space Network (DSN) antenna times in a collaborative fashion. This program is for all space-flight and terrestrial science project users and DSN schedulers to perform scheduling activities and conflict resolution, both synchronously and asynchronously. Project schedulers can, for the first time, participate directly in scheduling their tracking times into the official DSN schedule, and negotiate directly with other projects in an integrated scheduling system. A master schedule covers long-range, mid-range, near-real-time, and real-time scheduling time frames all in one, rather than the current method of separate functions that are supported by different processes and tools. CRANE also provides private workspaces (both dynamic and static), data sharing, scenario management, user control, rapid messaging (based on Java Message Service), data/time synchronization, workflow management, notification (including emails), conflict checking, and a linkage to a schedule generation engine. The data structure with corresponding database design combines object trees with multiple associated mortal instances and relational database to provide unprecedented traceability and simplify the existing DSN XML schedule representation. These technologies are used to provide traceability, schedule negotiation, conflict resolution, and load forecasting from real-time operations to long-range loading analysis up to 20 years in the future. CRANE includes a database, a stored procedure layer, an agent-based middle tier, a Web service wrapper, a Windows Integrated Analysis Environment (IAE), a Java application, and a Web page interface.

Robust Decision Making: The Cognitive and Computational Modeling of Team Problem Solving for Decision Making under Complex and Dynamic Conditions

DTIC Science & Technology

2015-07-14

AFRL-OSR-VA-TR-2015-0202 Robust Decision Making: The Cognitive and Computational Modeling of Team Problem Solving for Decision Making under Complex...Computational Modeling of Team Problem Solving for Decision Making Under Complex and Dynamic Conditions 5a. CONTRACT NUMBER 5b. GRANT NUMBER FA9550-12-1...functioning as they solve complex problems, and propose the means to improve the performance of teams, under changing or adversarial conditions. By

Multiobjective Resource-Constrained Project Scheduling with a Time-Varying Number of Tasks

PubMed Central

Abello, Manuel Blanco

2014-01-01

In resource-constrained project scheduling (RCPS) problems, ongoing tasks are restricted to utilizing a fixed number of resources. This paper investigates a dynamic version of the RCPS problem where the number of tasks varies in time. Our previous work investigated a technique called mapping of task IDs for centroid-based approach with random immigrants (McBAR) that was used to solve the dynamic problem. However, the solution-searching ability of McBAR was investigated over only a few instances of the dynamic problem. As a consequence, only a small number of characteristics of McBAR, under the dynamics of the RCPS problem, were found. Further, only a few techniques were compared to McBAR with respect to its solution-searching ability for solving the dynamic problem. In this paper, (a) the significance of the subalgorithms of McBAR is investigated by comparing McBAR to several other techniques; and (b) the scope of investigation in the previous work is extended. In particular, McBAR is compared to a technique called, Estimation Distribution Algorithm (EDA). As with McBAR, EDA is applied to solve the dynamic problem, an application that is unique in the literature. PMID:24883398

The dynamics of behavior in modified dictator games

PubMed Central

2017-01-01

We investigate the dynamics of individual pro-social behavior over time. The dynamics are tested by running the same experiment with the same subjects at several points in time. To exclude learning and reputation building, we employ non-strategic decision tasks and a sequential prisoners-dilemma as a control treatment. In the first wave, pro-social concerns explain a high share of individual decisions. Pro-social decisions decrease over time, however. In the final wave, most decisions can be accounted for by assuming pure selfishness. Stable behavior in the sense that subjects stick to their decisions over time is observed predominantly for purely selfish subjects. We offer two explanation for our results: diminishing experimenter demand effects and moral self-licensing. PMID:28448506

Uncertainty management by relaxation of conflicting constraints in production process scheduling

NASA Technical Reports Server (NTRS)

Dorn, Juergen; Slany, Wolfgang; Stary, Christian

1992-01-01

Mathematical-analytical methods as used in Operations Research approaches are often insufficient for scheduling problems. This is due to three reasons: the combinatorial complexity of the search space, conflicting objectives for production optimization, and the uncertainty in the production process. Knowledge-based techniques, especially approximate reasoning and constraint relaxation, are promising ways to overcome these problems. A case study from an industrial CIM environment, namely high-grade steel production, is presented to demonstrate how knowledge-based scheduling with the desired capabilities could work. By using fuzzy set theory, the applied knowledge representation technique covers the uncertainty inherent in the problem domain. Based on this knowledge representation, a classification of jobs according to their importance is defined which is then used for the straightforward generation of a schedule. A control strategy which comprises organizational, spatial, temporal, and chemical constraints is introduced. The strategy supports the dynamic relaxation of conflicting constraints in order to improve tentative schedules.

White Paper on studying the safety of the childhood immunization schedule in the Vaccine Safety Datalink.

PubMed

Glanz, Jason M; Newcomer, Sophia R; Jackson, Michael L; Omer, Saad B; Bednarczyk, Robert A; Shoup, Jo Ann; DeStefano, Frank; Daley, Matthew F

2016-02-15

While the large majority of parents in the U.S. vaccinate their children according to the recommended immunization schedule, some parents have refused or delayed vaccinating, often citing safety concerns. In response to public concern, the U.S. Institute of Medicine (IOM) evaluated existing research regarding the safety of the recommended immunization schedule. The IOM concluded that although available evidence strongly supported the safety of the currently recommended schedule as a whole, additional observational research was warranted to compare health outcomes between fully vaccinated children and those on a delayed or alternative schedule. In addition, the IOM identified the Vaccine Safety Datalink (VSD) as an important resource for conducting this research. Guided by the IOM findings, the Centers for Disease Control and Prevention (CDC) commissioned a White Paper to assess how the VSD could be used to study the safety of the childhood immunization schedule. Guided by subject matter expert engagement, the resulting White Paper outlines a 4 stage approach for identifying exposure groups of undervaccinated children, presents a list of health outcomes of highest priority to examine in this context, and describes various study designs and statistical methods that could be used to analyze the safety of the schedule. While it appears feasible to study the safety of the recommended immunization schedule in settings such as the VSD, these studies will be inherently complex, and as with all observational studies, will need to carefully address issues of confounding and bias. In light of these considerations, decisions about conducting studies of the safety of the schedule will also need to assess epidemiological evidence of potential adverse events that could be related to the schedule, the biological plausibility of an association between an adverse event and the schedule, and public concern about the safety of the schedule. Copyright © 2015 Elsevier Ltd. All rights reserved.

A New Distributed Optimization for Community Microgrids Scheduling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Starke, Michael R; Tomsovic, Kevin

This paper proposes a distributed optimization model for community microgrids considering the building thermal dynamics and customer comfort preference. The microgrid central controller (MCC) minimizes the total cost of operating the community microgrid, including fuel cost, purchasing cost, battery degradation cost and voluntary load shedding cost based on the customers' consumption, while the building energy management systems (BEMS) minimize their electricity bills as well as the cost associated with customer discomfort due to room temperature deviation from the set point. The BEMSs and the MCC exchange information on energy consumption and prices. When the optimization converges, the distributed generation scheduling,more » energy storage charging/discharging and customers' consumption as well as the energy prices are determined. In particular, we integrate the detailed thermal dynamic characteristics of buildings into the proposed model. The heating, ventilation and air-conditioning (HVAC) systems can be scheduled intelligently to reduce the electricity cost while maintaining the indoor temperature in the comfort range set by customers. Numerical simulation results show the effectiveness of proposed model.« less

The GBT Dynamic Scheduling System: Development and Testing

NASA Astrophysics Data System (ADS)

McCarty, M.; Clark, M.; Marganian, P.; O'Neil, K.; Shelton, A.; Sessoms, E.

2009-09-01

During the summer trimester of 2008, all observations on the Robert C. Byrd Green Bank Telescope (GBT) were scheduled using the new Dynamic Scheduling System (DSS). Beta testing exercised the policies, algorithms, and software developed for the DSS project. Since observers are located all over the world, the DSS was implemented as a web application. Technologies such as iCalendar, Really Simple Syndication (RSS) feeds, email, and instant messaging are used to transfer as much or as little information to observers as they request. We discuss the software engineering challenges leading to our implementation such as information distribution and building rich user interfaces in the web browser. We also relate our adaptation of agile development practices to design and develop the DSS. Additionally, we describe handling differences in expected versus actual initial conditions in the pool of project proposals for the 08B trimester. We then identify lessons learned from beta testing and present statistics on how the DSS was used during the trimester.

The Influence of Information Acquisition on the Complex Dynamics of Market Competition

NASA Astrophysics Data System (ADS)

Guo, Zhanbing; Ma, Junhai

In this paper, we build a dynamical game model with three bounded rational players (firms) to study the influence of information on the complex dynamics of market competition, where useful information is about rival’s real decision. In this dynamical game model, one information-sharing team is composed of two firms, they acquire and share the information about their common competitor, however, they make their own decisions separately, where the amount of information acquired by this information-sharing team will determine the estimation accuracy about the rival’s real decision. Based on this dynamical game model and some creative 3D diagrams, the influence of the amount of information on the complex dynamics of market competition such as local dynamics, global dynamics and profits is studied. These results have significant theoretical and practical values to realize the influence of information.

77 FR 64444 - VOR Federal Airway V-595; Oregon

Federal Register 2010, 2011, 2012, 2013, 2014

2012-10-22

... Aviation Administration (FAA), DOT. ACTION: Notice of proposed rulemaking (NPRM). SUMMARY: This action... this action to redescribe the route due to the scheduled decommissioning of the Portland, OR, VOR/DME... suggestions presented are particularly helpful in developing reasoned regulatory decisions on the proposal...

Have Your Computer Call My Computer.

ERIC Educational Resources Information Center

Carabi, Peter

1992-01-01

As more school systems adopt site-based management, local decision makers need greater access to all kinds of information. Microcomputer-based networks can help with classroom management, scheduling, student program design, counselor recommendations, and financial reporting operations. Administrators are provided with planning tips and a sample…

Paroxysmal Atrial Fibrillation in a Mission-Assigned Astronaut

NASA Technical Reports Server (NTRS)

Bauer, Peter A.; Polk, J. D.

2010-01-01

This presentation will explore the clinical and administrative conundrums faced by the flight surgeon upon discovering asymptomatic paroxysmal atrial fibrillation seven months prior to scheduled long duration spaceflight. The presenter will discuss the decision-making process as well as the clinical and operational outcomes.

ATD-1 ATM Technology Demonstration-1 and Integrated Scheduling

NASA Technical Reports Server (NTRS)

Quon, Leighton

2014-01-01

Enabling efficient arrivals for the NextGen Air Traffic Management System and developing a set of integrated decision support tools to reduce the high cognitive workload so that controllers are able to simultaneously achieve safe, efficient, and expedient operations at high traffic demand levels.

Self-balancing dynamic scheduling of electrical energy for energy-intensive enterprises

NASA Astrophysics Data System (ADS)

Gao, Yunlong; Gao, Feng; Zhai, Qiaozhu; Guan, Xiaohong

2013-06-01

Balancing production and consumption with self-generation capacity in energy-intensive enterprises has huge economic and environmental benefits. However, balancing production and consumption with self-generation capacity is a challenging task since the energy production and consumption must be balanced in real time with the criteria specified by power grid. In this article, a mathematical model for minimising the production cost with exactly realisable energy delivery schedule is formulated. And a dynamic programming (DP)-based self-balancing dynamic scheduling algorithm is developed to obtain the complete solution set for such a multiple optimal solutions problem. For each stage, a set of conditions are established to determine whether a feasible control trajectory exists. The state space under these conditions is partitioned into subsets and each subset is viewed as an aggregate state, the cost-to-go function is then expressed as a function of initial and terminal generation levels of each stage and is proved to be a staircase function with finite steps. This avoids the calculation of the cost-to-go of every state to resolve the issue of dimensionality in DP algorithm. In the backward sweep process of the algorithm, an optimal policy is determined to maximise the realisability of energy delivery schedule across the entire time horizon. And then in the forward sweep process, the feasible region of the optimal policy with the initial and terminal state at each stage is identified. Different feasible control trajectories can be identified based on the region; therefore, optimising for the feasible control trajectory is performed based on the region with economic and reliability objectives taken into account.

The Analysis of Forward and Backward Dynamic Programming for Multistage Graph

NASA Astrophysics Data System (ADS)

Sitinjak, Anna Angela; Pasaribu, Elvina; Simarmata, Justin E.; Putra, Tedy; Mawengkang, Herman

2018-01-01

Dynamic programming is an optimization approach that divides the complex problems into the simple sequences of problems in which they are interrelated leading to decisions. In the dynamic programming, there is no standard formula that can be used to make a certain formulation. In this paper we use forward and backward method to find path which have the minimum cost and to know whether they make the same final decision. Convert the problem into several successive sequential stages starting on from stages 1,2,3 and 4 for forward dynamic programming and the step back from stage 4.3,2,1 for backward dynamic programming and interconnected with a decision rule in each stage. Find the optimal solution with cost principle at next stage. Based on the characteristics of the dynamic programming, the case is divided into several stages and the decision is has to be made (xk) at each stage. The results obtained at a stage are used for the states in the next stage so that at the forward stage 1, f1 (s) is obtained and used as a consideration of the decision in the next stage. In the backward, used firstly stage 4, f4 (s) is obtained and used as a consideration of the decision in the next stage. Cost forward and backward always increase steadily, because the cost in the next stage depends on the cost in the previous stage and formed the decision of each stage by taking the smallest fk value. Therefore the forward and backward approaches have the same result.

The System Dynamics Model User Sustainability Explorer (SD-MUSE) user interface: a user-friendly tool for interpreting system dynamic models

EPA Science Inventory

Sustainability-based decision making is a challenging process that requires balancing trade-offs among social, economic, and environmental components. System Dynamic (SD) models can be useful tools to inform sustainability-based decision making because they provide a holistic co...

The System Dynamics Model User Sustainability Explorer (SD-MUSE): a user-friendly tool for interpreting system dynamic models

EPA Science Inventory

System Dynamics (SD) models are useful for holistic integration of data to evaluate indirect and cumulative effects and inform decisions. Complex SD models can provide key insights into how decisions affect the three interconnected pillars of sustainability. However, the complexi...

Design and specification of a centralized manufacturing data management and scheduling system

NASA Technical Reports Server (NTRS)

Farrington, Phillip A.

1993-01-01

As was revealed in a previous study, the Materials and Processes Laboratory's Productivity Enhancement Complex (PEC) has a number of automated production areas/cells that are not effectively integrated, limiting the ability of users to readily share data. The recent decision to utilize the PEC for the fabrication of flight hardware has focused new attention on the problem and brought to light the need for an integrated data management and scheduling system. This report addresses this need by developing preliminary designs specifications for a centralized manufacturing data management and scheduling system for managing flight hardware fabrication in the PEC. This prototype system will be developed under the auspices of the Integrated Engineering Environment (IEE) Oversight team and the IEE Committee. At their recommendation the system specifications were based on the fabrication requirements of the AXAF-S Optical Bench.

Pharmacists correcting schedule II prescriptions: DEA flip-flops continue.

PubMed

Abood, Richard R

2010-12-01

The Drug Enforcement Administration (DEA) has in recent years engaged in flip-flopping over important policy decisions. The most recent example involved whether a pharmacist can correct a written schedule II prescription upon verification with the prescriber. For several years the DEA's policy permitted this practice. Then the DEA issued a conflicting policy statement in 2007 in the preamble to the multiple schedule II prescription regulation, causing a series of subsequent contradictory statements ending with the policy that pharmacists should follow state law or policy until the Agency issues a regulation. It is doubtful that the DEA's opinion in the preamble would in itself constitute legal authority, or that the Agency would try to enforce the opinion. Nonetheless, these flip-flop opinions have confused pharmacists, caused some pharmacies to have claims rejected by third party payors, and most likely have inconvenienced patients.

Integration of domain and resource-based reasoning for real-time control in dynamic environments

NASA Technical Reports Server (NTRS)

Morgan, Keith; Whitebread, Kenneth R.; Kendus, Michael; Cromarty, Andrew S.

1993-01-01

A real-time software controller that successfully integrates domain-based and resource-based control reasoning to perform task execution in a dynamically changing environment is described. The design of the controller is based on the concept of partitioning the process to be controlled into a set of tasks, each of which achieves some process goal. It is assumed that, in general, there are multiple ways (tasks) to achieve a goal. The controller dynamically determines current goals and their current criticality, choosing and scheduling tasks to achieve those goals in the time available. It incorporates rule-based goal reasoning, a TMS-based criticality propagation mechanism, and a real-time scheduler. The controller has been used to build a knowledge-based situation assessment system that formed a major component of a real-time, distributed, cooperative problem solving system built under DARPA contract. It is also being employed in other applications now in progress.

Free energy reconstruction from steered dynamics without post-processing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Athenes, Manuel, E-mail: Manuel.Athenes@cea.f; Condensed Matter and Materials Division, Physics and Life Sciences Directorate, LLNL, Livermore, CA 94551; Marinica, Mihai-Cosmin

2010-09-20

Various methods achieving importance sampling in ensembles of nonequilibrium trajectories enable one to estimate free energy differences and, by maximum-likelihood post-processing, to reconstruct free energy landscapes. Here, based on Bayes theorem, we propose a more direct method in which a posterior likelihood function is used both to construct the steered dynamics and to infer the contribution to equilibrium of all the sampled states. The method is implemented with two steering schedules. First, using non-autonomous steering, we calculate the migration barrier of the vacancy in Fe-{alpha}. Second, using an autonomous scheduling related to metadynamics and equivalent to temperature-accelerated molecular dynamics, wemore » accurately reconstruct the two-dimensional free energy landscape of the 38-atom Lennard-Jones cluster as a function of an orientational bond-order parameter and energy, down to the solid-solid structural transition temperature of the cluster and without maximum-likelihood post-processing.« less

Towards a dynamical scheduler for ALMA: a science - software collaboration

NASA Astrophysics Data System (ADS)

Avarias, Jorge; Toledo, Ignacio; Espada, Daniel; Hibbard, John; Nyman, Lars-Ake; Hiriart, Rafael

2016-07-01

State-of-the art astronomical facilities are costly to build and operate, hence it is essential that these facilities must be operated as much efficiently as possible, trying to maximize the scientific output and at the same time minimizing overhead times. Over the latest decades the scheduling problem has drawn attention of research because new facilities have been demonstrated that is unfeasible to try to schedule observations manually, due the complexity to satisfy the astronomical and instrumental constraints and the number of scientific proposals to be reviewed and evaluated in near real-time. In addition, the dynamic nature of some constraints make this problem even more difficult. The Atacama Large Millimeter/submillimeter Array (ALMA) is a major collaboration effort between European (ESO), North American (NRAO) and East Asian countries (NAOJ), under operations on the Chilean Chajnantor plateau, at 5.000 meters of altitude. During normal operations at least two independent arrays are available, aiming to achieve different types of science. Since ALMA does not observe in the visible spectrum, observations are not limited to night time only, thus a 24/7 operation with little downtime as possible is expected when full operations state will have been reached. However, during preliminary operations (early-science) ALMA has been operated on tied schedules using around half of the whole day-time to conduct scientific observations. The purpose of this paper is to explain how the observation scheduling and its optimization is done within ALMA, giving details about the problem complexity, its similarities and differences with traditional scheduling problems found in the literature. The paper delves into the current recommendation system implementation and the difficulties found during the road to its deployment in production.