Power plant maintenance scheduling using ant colony optimization: an improved formulation
NASA Astrophysics Data System (ADS)
Foong, Wai Kuan; Maier, Holger; Simpson, Angus
2008-04-01
It is common practice in the hydropower industry to either shorten the maintenance duration or to postpone maintenance tasks in a hydropower system when there is expected unserved energy based on current water storage levels and forecast storage inflows. It is therefore essential that a maintenance scheduling optimizer can incorporate the options of shortening the maintenance duration and/or deferring maintenance tasks in the search for practical maintenance schedules. In this article, an improved ant colony optimization-power plant maintenance scheduling optimization (ACO-PPMSO) formulation that considers such options in the optimization process is introduced. As a result, both the optimum commencement time and the optimum outage duration are determined for each of the maintenance tasks that need to be scheduled. In addition, a local search strategy is presented in this article to boost the robustness of the algorithm. When tested on a five-station hydropower system problem, the improved formulation is shown to be capable of allowing shortening of maintenance duration in the event of expected demand shortfalls. In addition, the new local search strategy is also shown to have significantly improved the optimization ability of the ACO-PPMSO algorithm.
NASA Astrophysics Data System (ADS)
Shah, Rahul H.
Production costs account for the largest share of the overall cost of manufacturing facilities. With the U.S. industrial sector becoming more and more competitive, manufacturers are looking for more cost and resource efficient working practices. Operations management and production planning have shown their capability to dramatically reduce manufacturing costs and increase system robustness. When implementing operations related decision making and planning, two fields that have shown to be most effective are maintenance and energy. Unfortunately, the current research that integrates both is limited. Additionally, these studies fail to consider parameter domains and optimization on joint energy and maintenance driven production planning. Accordingly, production planning methodology that considers maintenance and energy is investigated. Two models are presented to achieve well-rounded operating strategy. The first is a joint energy and maintenance production scheduling model. The second is a cost per part model considering maintenance, energy, and production. The proposed methodology will involve a Time-of-Use electricity demand response program, buffer and holding capacity, station reliability, production rate, station rated power, and more. In practice, the scheduling problem can be used to determine a joint energy, maintenance, and production schedule. Meanwhile, the cost per part model can be used to: (1) test the sensitivity of the obtained optimal production schedule and its corresponding savings by varying key production system parameters; and (2) to determine optimal system parameter combinations when using the joint energy, maintenance, and production planning model. Additionally, a factor analysis on the system parameters is conducted and the corresponding performance of the production schedule under variable parameter conditions, is evaluated. Also, parameter optimization guidelines that incorporate maintenance and energy parameter decision making in the production planning framework are discussed. A modified Particle Swarm Optimization solution technique is adopted to solve the proposed scheduling problem. The algorithm is described in detail and compared to Genetic Algorithm. Case studies are presented to illustrate the benefits of using the proposed model and the effectiveness of the Particle Swarm Optimization approach. Numerical Experiments are implemented and analyzed to test the effectiveness of the proposed model. The proposed scheduling strategy can achieve savings of around 19 to 27 % in cost per part when compared to the baseline scheduling scenarios. By optimizing key production system parameters from the cost per part model, the baseline scenarios can obtain around 20 to 35 % in savings for the cost per part. These savings further increase by 42 to 55 % when system parameter optimization is integrated with the proposed scheduling problem. Using this method, the most influential parameters on the cost per part are the rated power from production, the production rate, and the initial machine reliabilities. The modified Particle Swarm Optimization algorithm adopted allows greater diversity and exploration compared to Genetic Algorithm for the proposed joint model which results in it being more computationally efficient in determining the optimal scheduling. While Genetic Algorithm could achieve a solution quality of 2,279.63 at an expense of 2,300 seconds in computational effort. In comparison, the proposed Particle Swarm Optimization algorithm achieved a solution quality of 2,167.26 in less than half the computation effort which is required by Genetic Algorithm.
Monitoring Strategies in Permeable Pavement Systems to Optimize Maintenance Scheduling
As the surface in a permeable pavement system clogs and performance decreases, maintenance is required to preserve the design function. Currently, guidance is limited for scheduling maintenance on an as needed basis. Previous research has shown that surface clogging in a permea...
Monitoring Strategies in Permeable Pavement Systems to Optimize Maintenance Scheduling - abstract
As the surface in a permeable pavement system clogs and performance decreases, maintenance is required to preserve the design function. Currently, guidance is limited for scheduling maintenance on an as needed basis. Previous research has shown that surface clogging in a permea...
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.
Optimal Preventive Maintenance Schedule based on Lifecycle Cost and Time-Dependent Reliability
2011-11-10
Page 1 of 16 UNCLASSIFIED: Distribution Statement A. Approved for public release. 12IDM-0064 Optimal Preventive Maintenance Schedule based... 1 . INTRODUCTION Customers and product manufacturers demand continued functionality of complex equipment and processes. Degradation of material...Documentation Page Form ApprovedOMB No. 0704-0188 Public reporting burden for the collection of information is estimated to average 1 hour per response
Fontecha, John E; Akhavan-Tabatabaei, Raha; Duque, Daniel; Medaglia, Andrés L; Torres, María N; Rodríguez, Juan Pablo
In this work we tackle the problem of planning and scheduling preventive maintenance (PM) of sediment-related sewer blockages in a set of geographically distributed sites that are subject to non-deterministic failures. To solve the problem, we extend a combined maintenance and routing (CMR) optimization approach which is a procedure based on two components: (a) first a maintenance model is used to determine the optimal time to perform PM operations for each site and second (b) a mixed integer program-based split procedure is proposed to route a set of crews (e.g., sewer cleaners, vehicles equipped with winches or rods and dump trucks) in order to perform PM operations at a near-optimal minimum expected cost. We applied the proposed CMR optimization approach to two (out of five) operative zones in the city of Bogotá (Colombia), where more than 100 maintenance operations per zone must be scheduled on a weekly basis. Comparing the CMR against the current maintenance plan, we obtained more than 50% of cost savings in 90% of the sites.
Scheduling Jobs and a Variable Maintenance on a Single Machine with Common Due-Date Assignment
Wan, Long
2014-01-01
We investigate a common due-date assignment scheduling problem with a variable maintenance on a single machine. The goal is to minimize the total earliness, tardiness, and due-date cost. We derive some properties on an optimal solution for our problem. For a special case with identical jobs we propose an optimal polynomial time algorithm followed by a numerical example. PMID:25147861
Multi-objective group scheduling optimization integrated with preventive maintenance
NASA Astrophysics Data System (ADS)
Liao, Wenzhu; Zhang, Xiufang; Jiang, Min
2017-11-01
This article proposes a single-machine-based integration model to meet the requirements of production scheduling and preventive maintenance in group production. To describe the production for identical/similar and different jobs, this integrated model considers the learning and forgetting effects. Based on machine degradation, the deterioration effect is also considered. Moreover, perfect maintenance and minimal repair are adopted in this integrated model. The multi-objective of minimizing total completion time and maintenance cost is taken to meet the dual requirements of delivery date and cost. Finally, a genetic algorithm is developed to solve this optimization model, and the computation results demonstrate that this integrated model is effective and reliable.
Reliability-based optimization of maintenance scheduling of mechanical components under fatigue
Beaurepaire, P.; Valdebenito, M.A.; Schuëller, G.I.; Jensen, H.A.
2012-01-01
This study presents the optimization of the maintenance scheduling of mechanical components under fatigue loading. The cracks of damaged structures may be detected during non-destructive inspection and subsequently repaired. Fatigue crack initiation and growth show inherent variability, and as well the outcome of inspection activities. The problem is addressed under the framework of reliability based optimization. The initiation and propagation of fatigue cracks are efficiently modeled using cohesive zone elements. The applicability of the method is demonstrated by a numerical example, which involves a plate with two holes subject to alternating stress. PMID:23564979
NASA Astrophysics Data System (ADS)
Moghaddam, Kamran S.; Usher, John S.
2011-07-01
In this article, a new multi-objective optimization model is developed to determine the optimal preventive maintenance and replacement schedules in a repairable and maintainable multi-component system. In this model, the planning horizon is divided into discrete and equally-sized periods in which three possible actions must be planned for each component, namely maintenance, replacement, or do nothing. The objective is to determine a plan of actions for each component in the system while minimizing the total cost and maximizing overall system reliability simultaneously over the planning horizon. Because of the complexity, combinatorial and highly nonlinear structure of the mathematical model, two metaheuristic solution methods, generational genetic algorithm, and a simulated annealing are applied to tackle the problem. The Pareto optimal solutions that provide good tradeoffs between the total cost and the overall reliability of the system can be obtained by the solution approach. Such a modeling approach should be useful for maintenance planners and engineers tasked with the problem of developing recommended maintenance plans for complex systems of components.
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...
Jin, Junchen
2016-01-01
The shunting schedule of electric multiple units depot (SSED) is one of the essential plans for high-speed train maintenance activities. This paper presents a 0-1 programming model to address the problem of determining an optimal SSED through automatic computing. The objective of the model is to minimize the number of shunting movements and the constraints include track occupation conflicts, shunting routes conflicts, time durations of maintenance processes, and shunting running time. An enhanced particle swarm optimization (EPSO) algorithm is proposed to solve the optimization problem. Finally, an empirical study from Shanghai South EMU Depot is carried out to illustrate the model and EPSO algorithm. The optimization results indicate that the proposed method is valid for the SSED problem and that the EPSO algorithm outperforms the traditional PSO algorithm on the aspect of optimality. PMID:27436998
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.
Optimizing work zones for highway maintenance with floating car data (FCD) : final report.
DOT National Transportation Integrated Search
2015-12-01
One of the main tools that the Department of Transportation (DOT) of each state in the United States should have to : support their work zone activities is a sound model that produces adequate work zone schedules for roadway maintenance : and constru...
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.
Li, Jun-qing; Pan, Quan-ke; Mao, Kun
2014-01-01
A hybrid algorithm which combines particle swarm optimization (PSO) and iterated local search (ILS) is proposed for solving the hybrid flowshop scheduling (HFS) problem with preventive maintenance (PM) activities. In the proposed algorithm, different crossover operators and mutation operators are investigated. In addition, an efficient multiple insert mutation operator is developed for enhancing the searching ability of the algorithm. Furthermore, an ILS-based local search procedure is embedded in the algorithm to improve the exploitation ability of the proposed algorithm. The detailed experimental parameter for the canonical PSO is tuning. The proposed algorithm is tested on the variation of 77 Carlier and Néron's benchmark problems. Detailed comparisons with the present efficient algorithms, including hGA, ILS, PSO, and IG, verify the efficiency and effectiveness of the proposed algorithm. PMID:24883414
Value centric approaches to the design, operations and maintenance of wind turbines
NASA Astrophysics Data System (ADS)
Khadabadi, Madhur Aravind
Wind turbine maintenance is emerging as an unexpectedly high component of turbine operating cost, and there is an increasing interest in managing this cost. This thesis presents an alternative view of maintenance as a value-driver, and develops an optimization algorithm to evaluate the value delivered by different maintenance techniques. I view maintenance as an operation that moves the turbine to an improved state in which it can generate more power and, thus, earn more revenue. To implement this approach, I model the stochastic deterioration of the turbine in two dimensions: the deterioration rate, and the extent of deterioration, and then use maintenance to improve the state of the turbine. The value of the turbine is the difference between the revenue from to the power generation and the costs incurred in operation and maintenance. With a focus on blade deterioration, I evaluate the value delivered by implementing two different maintenance schemes, predictive maintenance and scheduled maintenance. An example of predictive maintenance technique is the use of Condition Monitoring Systems to precisely detect deterioration. I model Condition Monitoring System (CMS) of different degrees of fidelity, where a higher fidelity CMS would allow the blade state to be determined with a higher precision. The same model is then applied for the scheduled maintenance technique. The improved state information obtained from these techniques is then used to derive an optimal maintenance strategy. The difference between the value of the turbine with and without the inspection type can be interpreted as the value of the inspection. The results indicate that a higher fidelity (and more expensive) inspection method does not necessarily yield the highest value, and, that there is an optimal level of fidelity that results in maximum value. The results also aim to inform the operator of the impact of regional parameters such as wind speed, variance and maintenance costs to the optimal maintenance strategy. The contributions of this work are twofold. First, I present a practical approach to wind turbine valuation that takes operating and market conditions into account. This work should therefore be useful to wind farm operators, investors and decision makers. Second, I show how the value of a maintenance scheme can be explicitly assessed for different conditions.
NASA Astrophysics Data System (ADS)
Zhong, Shuya; Pantelous, Athanasios A.; Beer, Michael; Zhou, Jian
2018-05-01
Offshore wind farm is an emerging source of renewable energy, which has been shown to have tremendous potential in recent years. In this blooming area, a key challenge is that the preventive maintenance of offshore turbines should be scheduled reasonably to satisfy the power supply without failure. In this direction, two significant goals should be considered simultaneously as a trade-off. One is to maximise the system reliability and the other is to minimise the maintenance related cost. Thus, a non-linear multi-objective programming model is proposed including two newly defined objectives with thirteen families of constraints suitable for the preventive maintenance of offshore wind farms. In order to solve our model effectively, the nondominated sorting genetic algorithm II, especially for the multi-objective optimisation is utilised and Pareto-optimal solutions of schedules can be obtained to offer adequate support to decision-makers. Finally, an example is given to illustrate the performances of the devised model and algorithm, and explore the relationships of the two targets with the help of a contrast model.
Optimization Models for Scheduling of Jobs
Indika, S. H. Sathish; Shier, Douglas R.
2006-01-01
This work is motivated by a particular scheduling problem that is faced by logistics centers that perform aircraft maintenance and modification. Here we concentrate on a single facility (hangar) which is equipped with several work stations (bays). Specifically, a number of jobs have already been scheduled for processing at the facility; the starting times, durations, and work station assignments for these jobs are assumed to be known. We are interested in how best to schedule a number of new jobs that the facility will be processing in the near future. We first develop a mixed integer quadratic programming model (MIQP) for this problem. Since the exact solution of this MIQP formulation is time consuming, we develop a heuristic procedure, based on existing bin packing techniques. This heuristic is further enhanced by application of certain local optimality conditions. PMID:27274921
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.
NASA Astrophysics Data System (ADS)
Xie, Chang; Wen, Jing; Liu, Wenying; Wang, Jiaming
With the development of intelligent dispatching, the intelligence level of network control center full-service urgent need to raise. As an important daily work of network control center, the application of maintenance scheduling intelligent arrangement to achieve high-quality and safety operation of power grid is very important. By analyzing the shortages of the traditional maintenance scheduling software, this paper designs a power grid maintenance scheduling intelligence arrangement supporting system based on power flow forecasting, which uses the advanced technologies in maintenance scheduling, such as artificial intelligence, online security checking, intelligent visualization techniques. It implements the online security checking of maintenance scheduling based on power flow forecasting and power flow adjusting based on visualization, in order to make the maintenance scheduling arrangement moreintelligent and visual.
Cryogenics maintenance strategy
NASA Astrophysics Data System (ADS)
Cruzat, Fabiola
2012-09-01
ALMA is an interferometer composed of 66 independent systems, with specific maintenance requirements for each subsystem. To optimize the observation time and reduce downtime maintenance, requirements are very demanding. One subsystem with high maintenance efforts is cryogenics and vacuum. To organize the maintenance, the Cryogenic and Vacuum department is using and implementing different tools. These are monitoring and problem reporting systems and CMMS. This leads to different maintenance approaches: Preventive Maintenance, Corrective Maintenance and Condition Based Maintenance. In order to coordinate activities with other departments the preventive maintenance schedule is kept as flexible as systems allow. To cope with unavoidable failures, the team has to be prepared to work under any condition with the spares on time. Computerized maintenance management system (CMMS) will help to manage inventory control for reliable spare part handling, the correct record of work orders and traceability of maintenance activities. For an optimized approach the department is currently evaluating where preventive or condition based maintenance applies to comply with the individual system demand. Considering the change from maintenance contracts to in-house maintenance will help to minimize costs and increase availability of parts. Due to increased number of system and tasks the cryo team needs to grow. Training of all staff members is mandatory, in depth knowledge must be built up by doing complex maintenance activities in the Cryo group, use of advanced computerized metrology systems.
Federal Register 2010, 2011, 2012, 2013, 2014
2012-01-05
... and engine manufacturers began planning to meet those requirements by optimizing engine designs for low emissions and adding high-efficiency aftertreatment systems. Manufacturers examined the use of... recirculation, and selective catalytic reduction (SCR). SCR systems use a nitrogen-containing reducing agent...
Heimdall System for MSSS Sensor Tasking
NASA Astrophysics Data System (ADS)
Herz, A.; Jones, B.; Herz, E.; George, D.; Axelrad, P.; Gehly, S.
In Norse Mythology, Heimdall uses his foreknowledge and keen eyesight to keep watch for disaster from his home near the Rainbow Bridge. Orbit Logic and the Colorado Center for Astrodynamics Research (CCAR) at the University of Colorado (CU) have developed the Heimdall System to schedule observations of known and uncharacterized objects and search for new objects from the Maui Space Surveillance Site. Heimdall addresses the current need for automated and optimized SSA sensor tasking driven by factors associated with improved space object catalog maintenance. Orbit Logic and CU developed an initial baseline prototype SSA sensor tasking capability for select sensors at the Maui Space Surveillance Site (MSSS) using STK and STK Scheduler, and then added a new Track Prioritization Component for FiSST-inspired computations for predicted Information Gain and Probability of Detection, and a new SSA-specific Figure-of-Merit (FOM) for optimized SSA sensor tasking. While the baseline prototype addresses automation and some of the multi-sensor tasking optimization, the SSA-improved prototype addresses all of the key elements required for improved tasking leading to enhanced object catalog maintenance. The Heimdall proof-of-concept was demonstrated for MSSS SSA sensor tasking for a 24 hour period to attempt observations of all operational satellites in the unclassified NORAD catalog, observe a small set of high priority GEO targets every 30 minutes, make a sky survey of the GEO belt region accessible to MSSS sensors, and observe particular GEO regions that have a high probability of finding new objects with any excess sensor time. This Heimdall prototype software paves the way for further R&D that will integrate this technology into the MSSS systems for operational scheduling, improve the software's scalability, and further tune and enhance schedule optimization. The Heimdall software for SSA sensor tasking provides greatly improved performance over manual tasking, improved coordinated sensor usage, and tasking schedules driven by catalog improvement goals (reduced overall covariance, etc.). The improved performance also enables more responsive sensor tasking to address external events, newly detected objects, newly detected object activity, and sensor anomalies. Instead of having to wait until the next day's scheduling phase, events can be addressed with new tasking schedules immediately (within seconds or minutes). Perhaps the most important benefit is improved SSA based on an overall improvement to the quality of the space catalog. By driving sensor tasking and scheduling based on predicted Information Gain and other relevant factors, better decisions are made in the application of available sensor resources, leading to an improved catalog and better information about the objects of most interest. The Heimdall software solution provides a configurable, automated system to improve sensor tasking efficiency and responsiveness for SSA applications. The FISST algorithms for Track Prioritization, SSA specific task and resource attributes, Scheduler algorithms, and configurable SSA-specific Figure-of-Merit together provide optimized and tunable scheduling for the Maui Space Surveillance Site and possibly other sites and organizations across the U.S. military and for allies around the world.
NASA Astrophysics Data System (ADS)
Szemis, J. M.; Maier, H. R.; Dandy, G. C.
2012-08-01
Rivers, wetlands, and floodplains are in need of management as they have been altered from natural conditions and are at risk of vanishing because of river development. One method to mitigate these impacts involves the scheduling of environmental flow management alternatives (EFMA); however, this is a complex task as there are generally a large number of ecological assets (e.g., wetlands) that need to be considered, each with species with competing flow requirements. Hence, this problem evolves into an optimization problem to maximize an ecological benefit within constraints imposed by human needs and the physical layout of the system. This paper presents a novel optimization framework which uses ant colony optimization to enable optimal scheduling of EFMAs, given constraints on the environmental water that is available. This optimization algorithm is selected because, unlike other currently popular algorithms, it is able to account for all aspects of the problem. The approach is validated by comparing it to a heuristic approach, and its utility is demonstrated using a case study based on the Murray River in South Australia to investigate (1) the trade-off between plant recruitment (i.e., promoting germination) and maintenance (i.e., maintaining habitat) flow requirements, (2) the trade-off between flora and fauna flow requirements, and (3) a hydrograph inversion case. The results demonstrate the usefulness and flexibility of the proposed framework as it is able to determine EFMA schedules that provide optimal or near-optimal trade-offs between the competing needs of species under a range of operating conditions and valuable insight for managers.
Data Base Development of Automobile and Light Truck Maintenance : Volume II. Appendix E.
DOT National Transportation Integrated Search
1978-08-01
The document contains the scheduled maintenance data sheets and total cost summaries--both scheduled and unscheduled maintenance (Life cycle cost for Dealers, life cycle cost for Service Stations, life cycle cost for Independent Repair, and scheduled...
Data Base Development of Automobile and Light Truck Maintenance : Volume III. Appendix F.
DOT National Transportation Integrated Search
1978-08-01
The document contains the scheduled maintenance data sheets and total cost summaries--both scheduled and unscheduled maintenance (Life cycle cost for Dealers, life cycle cost for Service Stations, life cycle cost for Independent Repair, and scheduled...
NASTRAN maintenance and enhancement experiences
NASA Technical Reports Server (NTRS)
Schmitz, R. P.
1975-01-01
The current capability is described which includes isoparametric elements, optimization of grid point sequencing, and eigenvalue routine. Overlay and coding errors were corrected for cyclic symmetry, transient response, and differential stiffness rigid formats. Error corrections and program enhancements are discussed along with developments scheduled for the current year and a brief description of analyses being performed using the program.
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.
NASA Astrophysics Data System (ADS)
Pattabhiraman, Sriram
Airplane fuselage structures are designed with the concept of damage tolerance, wherein small damage are allowed to remain on the airplane, and damage that otherwise affect the safety of the structure are repaired. The damage critical to the safety of the fuselage are repaired by scheduling maintenance at pre-determined intervals. Scheduling maintenance is an interesting trade-off between damage tolerance and cost. Tolerance of larger damage would require less frequent maintenance and hence, a lower cost, to maintain a certain level of reliability. Alternatively, condition-based maintenance techniques have been developed using on-board sensors, which track damage continuously and request maintenance only when the damage size crosses a particular threshold. This effects a tolerance of larger damage than scheduled maintenance, leading to savings in cost. This work quantifies the savings of condition-based maintenance over scheduled maintenance. The work also quantifies converting the cost savings into weight savings. Structural health monitoring will need time to be able to establish itself as a stand-alone system for maintenance, due to concerns on its diagnosis accuracy and reliability. This work also investigates the effect of synchronizing structural health monitoring system with scheduled maintenance. This work uses on-board SHM equipment skip structural airframe maintenance (a subsect of scheduled maintenance), whenever deemed unnecessary while maintain a desired level of safety of structure. The work will also predict the necessary maintenance for a fleet of airplanes, based on the current damage status of the airplanes. The work also analyses the possibility of false alarm, wherein maintenance is being requested with no critical damage on the airplane. The work use SHM as a tool to identify lemons in a fleet of airplanes. Lemons are those airplanes that would warrant more maintenance trips than the average behavior of the fleet.
Optimized PID control of depth of hypnosis in anesthesia.
Padula, Fabrizio; Ionescu, Clara; Latronico, Nicola; Paltenghi, Massimiliano; Visioli, Antonio; Vivacqua, Giulio
2017-06-01
This paper addresses the use of proportional-integral-derivative controllers for regulating the depth of hypnosis in anesthesia by using propofol administration and the bispectral index as a controlled variable. In fact, introducing an automatic control system might provide significant benefits for the patient in reducing the risk for under- and over-dosing. In this study, the controller parameters are obtained through genetic algorithms by solving a min-max optimization problem. A set of 12 patient models representative of a large population variance is used to test controller robustness. The worst-case performance in the considered population is minimized considering two different scenarios: the induction case and the maintenance case. Our results indicate that including a gain scheduling strategy enables optimal performance for induction and maintenance phases, separately. Using a single tuning to address both tasks may results in a loss of performance up to 102% in the induction phase and up to 31% in the maintenance phase. Further on, it is shown that a suitably designed low-pass filter on the controller output can handle the trade-off between the performance and the noise effect in the control variable. Optimally tuned PID controllers provide a fast induction time with an acceptable overshoot and a satisfactory disturbance rejection performance during maintenance. These features make them a very good tool for comparison when other control algorithms are developed. Copyright © 2017 Elsevier B.V. All rights reserved.
Code of Federal Regulations, 2011 CFR
2011-01-01
... authorization, registration and filing of schedules, reciprocal arrangements, and maintenance of identity of... and filing of schedules, reciprocal arrangements, and maintenance of identity of consignments. (a... and will not result in duplication of charges or services. (d) Maintenance of identity of consignments...
Code of Federal Regulations, 2013 CFR
2013-01-01
... authorization, registration and filing of schedules, reciprocal arrangements, and maintenance of identity of... and filing of schedules, reciprocal arrangements, and maintenance of identity of consignments. (a... and will not result in duplication of charges or services. (d) Maintenance of identity of consignments...
Code of Federal Regulations, 2012 CFR
2012-01-01
... authorization, registration and filing of schedules, reciprocal arrangements, and maintenance of identity of... and filing of schedules, reciprocal arrangements, and maintenance of identity of consignments. (a... and will not result in duplication of charges or services. (d) Maintenance of identity of consignments...
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.
76 FR 67633 - Airworthiness Directives; Dassault Aviation Model Mystere-Falcon 50 Airplanes
Federal Register 2010, 2011, 2012, 2013, 2014
2011-11-02
...) of section 5-10 of the Recommended Maintenance Schedules chapter of the Aircraft Maintenance...) of section 5-10 of the Recommended Maintenance Schedules chapter of the Aircraft Maintenance... Dassault Falcon 50/ 50EX Maintenance Procedure 57-607, Non-Destructive Check of Flap Tracks 2 and 5, of...
NASA Astrophysics Data System (ADS)
Siswanto, A.; Kurniati, N.
2018-04-01
An oil and gas company has 2,268 oil and gas wells. Well Barrier Element (WBE) is installed in a well to protect human, prevent asset damage and minimize harm to the environment. The primary WBE component is Surface Controlled Subsurface Safety Valve (SCSSV). The secondary WBE component is Christmas Tree Valves that consist of four valves i.e. Lower Master Valve (LMV), Upper Master Valve (UMV), Swab Valve (SV) and Wing Valve (WV). Current practice on WBE Preventive Maintenance (PM) program is conducted by considering the suggested schedule as stated on manual. Corrective Maintenance (CM) program is conducted when the component fails unexpectedly. Both PM and CM need cost and may cause production loss. This paper attempts to analyze the failure data and reliability based on historical data. Optimal PM interval is determined in order to minimize the total cost of maintenance per unit time. The optimal PM interval for SCSSV is 730 days, LMV is 985 days, UMV is 910 days, SV is 900 days and WV is 780 days. In average of all components, the cost reduction by implementing the suggested interval is 52%, while the reliability is improved by 4% and the availability is increased by 5%.
Performance-based maintenance of gas turbines for reliable control of degraded power systems
NASA Astrophysics Data System (ADS)
Mo, Huadong; Sansavini, Giovanni; Xie, Min
2018-03-01
Maintenance actions are necessary for ensuring proper operations of control systems under component degradation. However, current condition-based maintenance (CBM) models based on component health indices are not suitable for degraded control systems. Indeed, failures of control systems are only determined by the controller outputs, and the feedback mechanism compensates the control performance loss caused by the component deterioration. Thus, control systems may still operate normally even if the component health indices exceed failure thresholds. This work investigates the CBM model of control systems and employs the reduced control performance as a direct degradation measure for deciding maintenance activities. The reduced control performance depends on the underlying component degradation modelled as a Wiener process and the feedback mechanism. To this aim, the controller features are quantified by developing a dynamic and stochastic control block diagram-based simulation model, consisting of the degraded components and the control mechanism. At each inspection, the system receives a maintenance action if the control performance deterioration exceeds its preventive-maintenance or failure thresholds. Inspired by realistic cases, the component degradation model considers random start time and unit-to-unit variability. The cost analysis of maintenance model is conducted via Monte Carlo simulation. Optimal maintenance strategies are investigated to minimize the expected maintenance costs, which is a direct consequence of the control performance. The proposed framework is able to design preventive maintenance actions on a gas power plant, to ensuring required load frequency control performance against a sudden load increase. The optimization results identify the trade-off between system downtime and maintenance costs as a function of preventive maintenance thresholds and inspection frequency. Finally, the control performance-based maintenance model can reduce maintenance costs as compared to CBM and pre-scheduled maintenance.
NASA Astrophysics Data System (ADS)
Witantyo; Rindiyah, Anita
2018-03-01
According to data from maintenance planning and control, it was obtained that highest inventory value is non-routine components. Maintenance components are components which procured based on maintenance activities. The problem happens because there is no synchronization between maintenance activities and the components required. Reliability Centered Maintenance method is used to overcome the problem by reevaluating maintenance activities required components. The case chosen is roller mill system because it has the highest unscheduled downtime record. Components required for each maintenance activities will be determined by its failure distribution, so the number of components needed could be predicted. Moreover, those components will be reclassified from routine component to be non-routine component, so the procurement could be carried out regularly. Based on the conducted analysis, failure happens in almost every maintenance task are classified to become scheduled on condition task, scheduled discard task, schedule restoration task and no schedule maintenance. From 87 used components for maintenance activities are evaluated and there 19 components that experience reclassification from non-routine components to routine components. Then the reliability and need of those components were calculated for one-year operation period. Based on this invention, it is suggested to change all of the components in overhaul activity to increase the reliability of roller mill system. Besides, the inventory system should follow maintenance schedule and the number of required components in maintenance activity so the value of procurement will be decreased and the reliability system will increase.
Laboratory services series: a programmed maintenance system
DOE Office of Scientific and Technical Information (OSTI.GOV)
Tuxbury, D.C.; Srite, B.E.
1980-01-01
The diverse facilities, operations and equipment at a major national research and development laboratory require a systematic, analytical approach to operating equipment maintenance. A computer-scheduled preventive maintenance program is described including program development, equipment identification, maintenance and inspection instructions, scheduling, personnel, and equipment history.
A particle swarm model for estimating reliability and scheduling system maintenance
NASA Astrophysics Data System (ADS)
Puzis, Rami; Shirtz, Dov; Elovici, Yuval
2016-05-01
Modifying data and information system components may introduce new errors and deteriorate the reliability of the system. Reliability can be efficiently regained with reliability centred maintenance, which requires reliability estimation for maintenance scheduling. A variant of the particle swarm model is used to estimate reliability of systems implemented according to the model view controller paradigm. Simulations based on data collected from an online system of a large financial institute are used to compare three component-level maintenance policies. Results show that appropriately scheduled component-level maintenance greatly reduces the cost of upholding an acceptable level of reliability by reducing the need in system-wide maintenance.
NASA Astrophysics Data System (ADS)
Nagata, Takeshi; Tao, Yasuhiro; Utatani, Masahiro; Sasaki, Hiroshi; Fujita, Hideki
This paper proposes a multi-agent approach to maintenance scheduling in restructured power systems. The restructuring of electric power industry has resulted in market-based approaches for unbundling a multitude of service provided by self-interested entities such as power generating companies (GENCOs), transmission providers (TRANSCOs) and distribution companies (DISCOs). The Independent System Operator (ISO) is responsible for the security of the system operation. The schedule submitted to ISO by GENCOs and TRANSCOs should satisfy security and reliability constraints. The proposed method consists of several GENCO Agents (GAGs), TARNSCO Agents (TAGs) and a ISO Agent(IAG). The IAG’s role in maintenance scheduling is limited to ensuring that the submitted schedules do not cause transmission congestion or endanger the system reliability. From the simulation results, it can be seen the proposed multi-agent approach could coordinate between generation and transmission maintenance schedules.
1987-06-01
NAVY OCCUPATIONAL HEALTH INFORMATION MANAGEMENT SYSTEM NOH I MS MEDICAL EXAM SCHEDULING MODULE PROGRAM MAINTENANCE MANUAL S JUNE 1987 DT11C 00... Information Management System (NOHIMS) ~ Medical Examination Scheduling (MES) Program Maintenance Manual 7. Author(s) 8. Performing Organization Rapt. No...the Navy Occupational Health Information Management System (NOHIMS). NOHIMS, whose initial version was developed at the Naval Health Research Center
Centralized mission planning and scheduling system for the Landsat Data Continuity Mission
Kavelaars, Alicia; Barnoy, Assaf M.; Gregory, Shawna; Garcia, Gonzalo; Talon, Cesar; Greer, Gregory; Williams, Jason; Dulski, Vicki
2014-01-01
Satellites in Low Earth Orbit provide missions with closer range for studying aspects such as geography and topography, but often require efficient utilization of space and ground assets. Optimizing schedules for these satellites amounts to a complex planning puzzle since it requires operators to face issues such as discontinuous ground contacts, limited onboard memory storage, constrained downlink margin, and shared ground antenna resources. To solve this issue for the Landsat Data Continuity Mission (LDCM, Landsat 8), all the scheduling exchanges for science data request, ground/space station contact, and spacecraft maintenance and control will be coordinated through a centralized Mission Planning and Scheduling (MPS) engine, based upon GMV’s scheduling system flexplan9 . The synchronization between all operational functions must be strictly maintained to ensure efficient mission utilization of ground and spacecraft activities while working within the bounds of the space and ground resources, such as Solid State Recorder (SSR) and available antennas. This paper outlines the functionalities that the centralized planning and scheduling system has in its operational control and management of the Landsat 8 spacecraft.
Pharmacokinetics of metronomic chemotherapy: a neglected but crucial aspect.
Bocci, Guido; Kerbel, Robert S
2016-11-01
Metronomic chemotherapy describes the close, regular administration of chemotherapy drugs at less-toxic doses over prolonged periods of time. In 2015, the results of randomized phase III clinical trials demonstrated encouraging, albeit limited, efficacy benefits of metronomic chemotherapy regimens administered as adjuvant maintenance therapy for the treatment of breast cancer, or as maintenance therapy in combination with an antiangiogenic agent for metastatic colorectal cancer. Owing to the investigational nature of this approach, metronomic chemotherapy regimens are highly empirical in terms of the optimal dose and schedule for the drugs administered; therefore, greater knowledge of the pharmacokinetics of metronomic chemotherapy is critical to the future success of this treatment strategy. Unfortunately, such preclinical and clinical pharmacokinetic studies are rare. Herein, we present situations in which active drug concentrations have been achieved with metronomic schedules, and discuss their associated pharmacokinetic parameters. We summarize examples from the limited number of clinical studies in order to illustrate the importance of assessing such pharmacokinetic parameters, and discuss the influence this information can have on improving efficacy and reducing toxicity.
Military Free Fall Scheduling And Manifest Optimization Model
2016-12-01
engines running waiting for the next student load. The annual blade hour cost, which consists of fuel, maintenance, and personnel, is $5.6M for FY-16...tarmac with engines running waiting for the next student load (J. Enke, personal communication, 2016). The annual blade hour cost, which consists of...33 Scenario 2 Nonstandard Run #1 C-27 Two Passes per Lift .......................34 Table 9. xii THIS PAGE INTENTIONALLY LEFT BLANK xiii
40 CFR 86.428-80 - Maintenance, scheduled; test vehicles.
Code of Federal Regulations, 2013 CFR
2013-07-01
... 40 Protection of Environment 19 2013-07-01 2013-07-01 false Maintenance, scheduled; test vehicles... PROGRAMS (CONTINUED) CONTROL OF EMISSIONS FROM NEW AND IN-USE HIGHWAY VEHICLES AND ENGINES Emission... vehicles. (a) Periodic maintenance on the engine, emission control system, and fuel system of test vehicles...
Enhanced Software for Scheduling Space-Shuttle Processing
NASA Technical Reports Server (NTRS)
Barretta, Joseph A.; Johnson, Earl P.; Bierman, Rocky R.; Blanco, Juan; Boaz, Kathleen; Stotz, Lisa A.; Clark, Michael; Lebovitz, George; Lotti, Kenneth J.; Moody, James M.;
2004-01-01
The Ground Processing Scheduling System (GPSS) computer program is used to develop streamlined schedules for the inspection, repair, and refurbishment of space shuttles at Kennedy Space Center. A scheduling computer program is needed because space-shuttle processing is complex and it is frequently necessary to modify schedules to accommodate unanticipated events, unavailability of specialized personnel, unexpected delays, and the need to repair newly discovered defects. GPSS implements constraint-based scheduling algorithms and provides an interactive scheduling software environment. In response to inputs, GPSS can respond with schedules that are optimized in the sense that they contain minimal violations of constraints while supporting the most effective and efficient utilization of space-shuttle ground processing resources. The present version of GPSS is a product of re-engineering of a prototype version. While the prototype version proved to be valuable and versatile as a scheduling software tool during the first five years, it was characterized by design and algorithmic deficiencies that affected schedule revisions, query capability, task movement, report capability, and overall interface complexity. In addition, the lack of documentation gave rise to difficulties in maintenance and limited both enhanceability and portability. The goal of the GPSS re-engineering project was to upgrade the prototype into a flexible system that supports multiple- flow, multiple-site scheduling and that retains the strengths of the prototype while incorporating improvements in maintainability, enhanceability, and portability.
Demonstration of decomposition and optimization in the design of experimental space systems
NASA Technical Reports Server (NTRS)
Padula, Sharon; Sandridge, Chris A.; Haftka, Raphael T.; Walsh, Joanne L.
1989-01-01
Effective design strategies for a class of systems which may be termed Experimental Space Systems (ESS) are needed. These systems, which include large space antenna and observatories, space platforms, earth satellites and deep space explorers, have special characteristics which make them particularly difficult to design. It is argued here that these same characteristics encourage the use of advanced computer-aided optimization and planning techniques. The broad goal of this research is to develop optimization strategies for the design of ESS. These strategics would account for the possibly conflicting requirements of mission life, safety, scientific payoffs, initial system cost, launch limitations and maintenance costs. The strategies must also preserve the coupling between disciplines or between subsystems. Here, the specific purpose is to describe a computer-aided planning and scheduling technique. This technique provides the designer with a way to map the flow of data between multidisciplinary analyses. The technique is important because it enables the designer to decompose the system design problem into a number of smaller subproblems. The planning and scheduling technique is demonstrated by its application to a specific preliminary design problem.
Characterization and optimization of spiral eddy current coils for in-situ crack detection
NASA Astrophysics Data System (ADS)
Mandache, Catalin
2018-03-01
In-situ condition-based maintenance is making strides in the aerospace industry and it is seen as an alternative to scheduled, time-based maintenance. With fatigue cracks originating from fastener holes as the main reason for structural failures, embedded eddy current coils are a viable non-invasive solution for their timely detection. The development and potential broad use of these coils are motivated by a few consistent arguments: (i) inspection of structures of complicated geometries and hard to access areas, that often require disassembly, (ii) alternative to regular inspection actions that could introduce inadvertent damage, (iii) for structures that have short inspection intervals, and (iv) for repaired structures where fastener holes contain bushings and prevent further bolt-hole inspections. Since the spiral coils are aiming at detecting radial cracks emanating from the fastener holes, their design parameters should allow for high inductance, low ohmic losses and power requirements, as well as optimal size and high sensitivity to discontinuities. In this study, flexible, surface conformable, spiral eddy current coils are empirically investigated on mock-up specimens, while numerical analysis is performed for their optimization and design improvement.
49 CFR 214.533 - Schedule of repairs subject to availability of parts.
Code of Federal Regulations, 2011 CFR
2011-10-01
... Maintenance Machines and Hi-Rail Vehicles § 214.533 Schedule of repairs subject to availability of parts. (a... 49 Transportation 4 2011-10-01 2011-10-01 false Schedule of repairs subject to availability of... maintenance machine or a hi-rail vehicle by the end of the next business day following the report of the...
Incorporating Equipment Condition Assessment in Risk Monitors for Advanced Small Modular Reactors
DOE Office of Scientific and Technical Information (OSTI.GOV)
Coble, Jamie B.; Coles, Garill A.; Meyer, Ryan M.
2013-10-01
Advanced small modular reactors (aSMRs) can complement the current fleet of large light-water reactors in the USA for baseload and peak demand power production and process heat applications (e.g., water desalination, shale oil extraction, hydrogen production). The day-to-day costs of aSMRs are expected to be dominated by operations and maintenance (O&M); however, the effect of diverse operating missions and unit modularity on O&M is not fully understood. These costs could potentially be reduced by optimized scheduling, with risk-informed scheduling of maintenance, repair, and replacement of equipment. Currently, most nuclear power plants have a “living” probabilistic risk assessment (PRA), which reflectsmore » the as-operated, as-modified plant and combine event probabilities with population-based probability of failure (POF) for key components. “Risk monitors” extend the PRA by incorporating the actual and dynamic plant configuration (equipment availability, operating regime, environmental conditions, etc.) into risk assessment. In fact, PRAs are more integrated into plant management in today’s nuclear power plants than at any other time in the history of nuclear power. However, population-based POF curves are still used to populate fault trees; this approach neglects the time-varying condition of equipment that is relied on during standard and non-standard configurations. Equipment condition monitoring techniques can be used to estimate the component POF. Incorporating this unit-specific estimate of POF in the risk monitor can provide a more accurate estimate of risk in different operating and maintenance configurations. This enhanced risk assessment will be especially important for aSMRs that have advanced component designs, which don’t have an available operating history to draw from, and often use passive design features, which present challenges to PRA. This paper presents the requirements and technical gaps for developing a framework to integrate unit-specific estimates of POF into risk monitors, resulting in enhanced risk monitors that support optimized operation and maintenance of aSMRs.« less
Strategic Gang Scheduling for Railroad Maintenance
DOT National Transportation Integrated Search
2012-08-14
We address the railway track maintenance scheduling problem. The problem stems from the : significant percentage of the annual budget invested by the railway industry for maintaining its railway : tracks. The process requires consideration of human r...
49 CFR 214.533 - Schedule of repairs subject to availability of parts.
Code of Federal Regulations, 2010 CFR
2010-10-01
... Maintenance Machines and Hi-Rail Vehicles § 214.533 Schedule of repairs subject to availability of parts. (a... maintenance machine or a hi-rail vehicle by the end of the next business day following the report of the... maintenance machine or hi-rail vehicle within seven calendar days after receiving the necessary part. The...
A Hybrid Memetic Framework for Coverage Optimization in Wireless Sensor Networks.
Chen, Chia-Pang; Mukhopadhyay, Subhas Chandra; Chuang, Cheng-Long; Lin, Tzu-Shiang; Liao, Min-Sheng; Wang, Yung-Chung; Jiang, Joe-Air
2015-10-01
One of the critical concerns in wireless sensor networks (WSNs) is the continuous maintenance of sensing coverage. Many particular applications, such as battlefield intrusion detection and object tracking, require a full-coverage at any time, which is typically resolved by adding redundant sensor nodes. With abundant energy, previous studies suggested that the network lifetime can be maximized while maintaining full coverage through organizing sensor nodes into a maximum number of disjoint sets and alternately turning them on. Since the power of sensor nodes is unevenly consumed over time, and early failure of sensor nodes leads to coverage loss, WSNs require dynamic coverage maintenance. Thus, the task of permanently sustaining full coverage is particularly formulated as a hybrid of disjoint set covers and dynamic-coverage-maintenance problems, and both have been proven to be nondeterministic polynomial-complete. In this paper, a hybrid memetic framework for coverage optimization (Hy-MFCO) is presented to cope with the hybrid problem using two major components: 1) a memetic algorithm (MA)-based scheduling strategy and 2) a heuristic recursive algorithm (HRA). First, the MA-based scheduling strategy adopts a dynamic chromosome structure to create disjoint sets, and then the HRA is utilized to compensate the loss of coverage by awaking some of the hibernated nodes in local regions when a disjoint set fails to maintain full coverage. The results obtained from real-world experiments using a WSN test-bed and computer simulations indicate that the proposed Hy-MFCO is able to maximize sensing coverage while achieving energy efficiency at the same time. Moreover, the results also show that the Hy-MFCO significantly outperforms the existing methods with respect to coverage preservation and energy efficiency.
NASA Astrophysics Data System (ADS)
Hanish Nithin, Anu; Omenzetter, Piotr
2017-04-01
Optimization of the life-cycle costs and reliability of offshore wind turbines (OWTs) is an area of immense interest due to the widespread increase in wind power generation across the world. Most of the existing studies have used structural reliability and the Bayesian pre-posterior analysis for optimization. This paper proposes an extension to the previous approaches in a framework for probabilistic optimization of the total life-cycle costs and reliability of OWTs by combining the elements of structural reliability/risk analysis (SRA), the Bayesian pre-posterior analysis with optimization through a genetic algorithm (GA). The SRA techniques are adopted to compute the probabilities of damage occurrence and failure associated with the deterioration model. The probabilities are used in the decision tree and are updated using the Bayesian analysis. The output of this framework would determine the optimal structural health monitoring and maintenance schedules to be implemented during the life span of OWTs while maintaining a trade-off between the life-cycle costs and risk of the structural failure. Numerical illustrations with a generic deterioration model for one monitoring exercise in the life cycle of a system are demonstrated. Two case scenarios, namely to build initially an expensive and robust or a cheaper but more quickly deteriorating structures and to adopt expensive monitoring system, are presented to aid in the decision-making process.
Explaining sex differences in lifespan in terms of optimal energy allocation in the baboon.
King, Annette M; Kirkwood, Thomas B L; Shanley, Daryl P
2017-10-01
We provide a quantitative test of the hypothesis that sex role specialization may account for sex differences in lifespan in baboons if such specialization causes the dependency of fitness upon longevity, and consequently the optimal resolution to an energetic trade-off between somatic maintenance and other physiological functions, to differ between males and females. We present a model in which females provide all offspring care and males compete for access to reproductive females and in which the partitioning of available energy between the competing fitness-enhancing functions of growth, maintenance, and reproduction is modeled as a dynamic behavioral game, with the optimal decision for each individual depending upon his/her state and the behavior of other members of the population. Our model replicates the sexual dimorphism in body size and sex differences in longevity and reproductive scheduling seen in natural populations of baboons. We show that this outcome is generally robust to perturbations in model parameters, an important finding given that the same behavior is seen across multiple populations and species in the wild. This supports the idea that sex differences in longevity result from differences in the value of somatic maintenance relative to other fitness-enhancing functions in keeping with the disposable soma theory. © 2017 The Author(s). Evolution © 2017 The Society for the Study of Evolution.
The ATA-67 Formula for Direct Operating Cost
NASA Technical Reports Server (NTRS)
Faulkner, H. B.
1972-01-01
The ATA formulas for direct operating cost were developed for the purpose of comparing different aircraft, existing or not, on the same route or the same aircraft on different routes. Such characteristics of the airline as crew pay, maintenance procedures, and depreciation schedules are kept constant. In air transportation systems analysis the 1967 ATA formula is usually used with appropriate exceptions or modifications, such as: different maintenance labor rate, total maintenance multiplied by a factor, maintenance burden deleted, different depreciation schedule, or different spares percentages.
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.
NASA Astrophysics Data System (ADS)
Sembiring, N.; Nasution, A. H.
2018-02-01
Corrective maintenance i.e replacing or repairing the machine component after machine break down always done in a manufacturing company. It causes the production process must be stopped. Production time will decrease due to the maintenance team must replace or repair the damage machine component. This paper proposes a preventive maintenance’s schedule for a critical component of a critical machine of an crude palm oil and kernel company due to increase maintenance efficiency. The Reliability Engineering & Maintenance Value Stream Mapping is used as a method and a tool to analize the reliability of the component and reduce the wastage in any process by segregating value added and non value added activities.
NASA Astrophysics Data System (ADS)
Paprocka, I.; Kempa, W. M.; Grabowik, C.; Kalinowski, K.; Krenczyk, D.
2016-08-01
In the paper a survey of predictive and reactive scheduling methods is done in order to evaluate how the ability of prediction of reliability characteristics influences over robustness criteria. The most important reliability characteristics are: Mean Time to Failure, Mean Time of Repair. Survey analysis is done for a job shop scheduling problem. The paper answers the question: what method generates robust schedules in the case of a bottleneck failure occurrence before, at the beginning of planned maintenance actions or after planned maintenance actions? Efficiency of predictive schedules is evaluated using criteria: makespan, total tardiness, flow time, idle time. Efficiency of reactive schedules is evaluated using: solution robustness criterion and quality robustness criterion. This paper is the continuation of the research conducted in the paper [1], where the survey of predictive and reactive scheduling methods is done only for small size scheduling problems.
Improvements in Space Surveillance Processing for Wide Field of View Optical Sensors
NASA Astrophysics Data System (ADS)
Sydney, P.; Wetterer, C.
2014-09-01
For more than a decade, an autonomous satellite tracking system at the Air Force Maui Optical and Supercomputing (AMOS) observatory has been generating routine astrometric measurements of Earth-orbiting Resident Space Objects (RSOs) using small commercial telescopes and sensors. Recent work has focused on developing an improved processing system, enhancing measurement performance and response while supporting other sensor systems and missions. This paper will outline improved techniques in scheduling, detection, astrometric and photometric measurements, and catalog maintenance. The processing system now integrates with Special Perturbation (SP) based astrodynamics algorithms, allowing covariance-based scheduling and more precise orbital estimates and object identification. A merit-based scheduling algorithm provides a global optimization framework to support diverse collection tasks and missions. The detection algorithms support a range of target tracking and camera acquisition rates. New comprehensive star catalogs allow for more precise astrometric and photometric calibrations including differential photometry for monitoring environmental changes. This paper will also examine measurement performance with varying tracking rates and acquisition parameters.
NASA Astrophysics Data System (ADS)
Singh, Navneet K.; Singh, Asheesh K.; Tripathy, Manoj
2012-05-01
For power industries electricity load forecast plays an important role for real-time control, security, optimal unit commitment, economic scheduling, maintenance, energy management, and plant structure planning
A Phase 1 study of Vorinostat Maintenance after Autologous Transplant in High Risk Lymphoma
Hofmeister, Craig C.; Williams, Nita; Geyer, Susan; Hade, Erinn M.; Bowers, Mindy A.; Earl, Christian T.; Vaughn, John; Bingman, Anissa; Humphries, Kristina; Lozanski, Gerard; Baiocchi, Robert A.; Jaglowski, Samantha M.; Blum, Kristie; Porcu, Pierluigi; Flynn, Joseph; Penza, Sam; Benson, Don M.; Andritsos, Leslie A.; Devine, Steven M.
2014-01-01
Only a minority of patients with high risk lymphoma will be cured with autologous transplant, so maintenance with Vorinostat, an oral agent with activity in relapsed lymphoma, was studied starting day +60 for 21 consecutive days followed by a week off for up to 11 cycles. Twenty-three lymphoma patients were treated. Ten patients completed the full 11 cycle treatment plan per protocol, 4 patients were removed due to progressive disease, 7 withdrew or were removed from the study due to toxicities. Despite Prevnar vaccine administration every 2 months for 3 injections, the mean antibody concentration never reached protective levels (>0.35 mcg/mL). Fatigue and functional well-being measured by BFI and FACT-G improved significantly from cycle 1 to cycle 7, but the depression scores from the CES-D did not change. Given the toxicities observed, this broad spectrum deacetylase inhibitor at this schedule is not optimal for prolonged maintenance therapy. PMID:25213183
78 FR 48608 - Drawbridge Operation Regulation; Atlantic Intracoastal Waterway (AIWW), Chesapeake, VA
Federal Register 2010, 2011, 2012, 2013, 2014
2013-08-09
... maintenance of the moveable spans on the structure. The current operating schedule for the bridge is set out... deviation from the operating schedule that governs the operation of the I64 Bridge across the Atlantic... necessary to facilitate maintenance work on the moveable spans. This temporary deviation allows the...
2007-10-19
HGPI); Combustion Inspections (CI); and inspection and scheduled critical maintenance on all auxillary systems of the four GE Frame 9E units located...Work requirements for a functional end product. 6 services and scheduled critical maintenance on all auxillary systems of the four GE Frame
NASA Astrophysics Data System (ADS)
Zhadanovsky, Boris; Sinenko, Sergey
2018-03-01
Economic indicators of construction work, particularly in high-rise construction, are directly related to the choice of optimal number of machines. The shortage of machinery makes it impossible to complete the construction & installation work on scheduled time. Rates of performance of construction & installation works and labor productivity during high-rise construction largely depend on the degree of provision of construction project with machines (level of work mechanization). During calculation of the need for machines in construction projects, it is necessary to ensure that work is completed on scheduled time, increased level of complex mechanization, increased productivity and reduction of manual work, and improved usage and maintenance of machine fleet. The selection of machines and determination of their numbers should be carried out by using formulas presented in this work.
77 FR 12175 - Airworthiness Directives; DASSAULT AVIATION Airplanes
Federal Register 2010, 2011, 2012, 2013, 2014
2012-02-29
... specified products. The MCAI states: The Maintenance Procedure (MP) 57-607, related to non destructive check... Recommended Maintenance Schedules chapter of the Aircraft Maintenance Documentation. After the implementation... maintenance program to include ``Non-Destructive Check of Flap Tracks 2 and 5,'' Maintenance Procedure 57-607...
MacDuff, G S; Krantz, P J; McClannahan, L E
1993-01-01
We used a graduated guidance procedure to teach 4 boys with autism to follow photographic activity schedules to increase on-task and on-schedule behavior. The multiple baseline across participants design included baseline, teaching, maintenance, resequencing of photographs, and generalization to novel photographs phases. The results indicated that photographic activity schedules (albums depicting after-school activities) produced sustained engagement, and skills generalized to a new sequence of photographs and to new photographs. The acquisition of schedule-following skills enabled these children with severe developmental disabilities to display lengthy response chains, independently change activities, and change activities in different group home settings in the absence of immediate supervision and prompts from others. PMID:8473261
Risk-based maintenance of ethylene oxide production facilities.
Khan, Faisal I; Haddara, Mahmoud R
2004-05-20
This paper discusses a methodology for the design of an optimum inspection and maintenance program. The methodology, called risk-based maintenance (RBM) is based on integrating a reliability approach and a risk assessment strategy to obtain an optimum maintenance schedule. First, the likely equipment failure scenarios are formulated. Out of many likely failure scenarios, the ones, which are most probable, are subjected to a detailed study. Detailed consequence analysis is done for the selected scenarios. Subsequently, these failure scenarios are subjected to a fault tree analysis to determine their probabilities. Finally, risk is computed by combining the results of the consequence and the probability analyses. The calculated risk is compared against known acceptable criteria. The frequencies of the maintenance tasks are obtained by minimizing the estimated risk. A case study involving an ethylene oxide production facility is presented. Out of the five most hazardous units considered, the pipeline used for the transportation of the ethylene is found to have the highest risk. Using available failure data and a lognormal reliability distribution function human health risk factors are calculated. Both societal risk factors and individual risk factors exceeded the acceptable risk criteria. To determine an optimal maintenance interval, a reverse fault tree analysis was used. The maintenance interval was determined such that the original high risk is brought down to an acceptable level. A sensitivity analysis is also undertaken to study the impact of changing the distribution of the reliability model as well as the error in the distribution parameters on the maintenance interval.
NASA Astrophysics Data System (ADS)
Khalqihi, K. I.; Rahayu, M.; Rendra, M.
2017-12-01
PT Perkebunan Nusantara VIII Ciater is a company produced black tea orthodox more or less 4 tons every day. At the production section, PT Perkebunan Nusantara VIII will use local exhaust ventilation specially at sortation area on sieve machine. To maintain the quality of the black tea orthodox, all machine must be scheduled for maintenance every once a month and takes time 2 hours in workhours, with additional local exhaust ventilation, it will increase time for maintenance process, if maintenance takes time more than 2 hours it will caused production process delayed. To support maintenance process in PT Perkebunan Nusantara VIII Ciater, designing local exhaust ventilation using design for assembly approach with Boothroyd and Dewhurst method, design for assembly approach is choosen to simplify maintenance process which required assembly process. There are 2 LEV designs for this research. Design 1 with 94 components, assembly time 647.88 seconds and assembly efficiency level 23.62%. Design 2 with 82 components, assembly time 567.84 seconds and assembly efficiency level 24.83%. Design 2 is choosen for this research based on DFA goals, minimum total part that use, optimization assembly time, and assembly efficiency level.
Managing Highway Maintenance: Standards for Maintenance Work, Part 1, Unit 8, Level 2.
ERIC Educational Resources Information Center
Federal Highway Administration (DOT), Washington, DC. Offices of Research and Development.
Part of the series "Managing Highway Maintenance," the unit is about maintenance standards and is designed for superintendents and senior foremen who are responsible for scheduling and controlling routine maintenance. It describes different kinds of standards, why and how standards are developed, and how standards are to be used and…
77 FR 27115 - Drawbridge Operation Regulations; Raritan River, Perth Amboy, NJ
Federal Register 2010, 2011, 2012, 2013, 2014
2012-05-09
... the draw may remain in the closed position for four days to facilitate mechanical maintenance. Vessels... scheduled mechanical maintenance at the bridge. In order to perform the bridge maintenance the bridge must...
Production scheduling with ant colony optimization
NASA Astrophysics Data System (ADS)
Chernigovskiy, A. S.; Kapulin, D. V.; Noskova, E. E.; Yamskikh, T. N.; Tsarev, R. Yu
2017-10-01
The optimum solution of the production scheduling problem for manufacturing processes at an enterprise is crucial as it allows one to obtain the required amount of production within a specified time frame. Optimum production schedule can be found using a variety of optimization algorithms or scheduling algorithms. Ant colony optimization is one of well-known techniques to solve the global multi-objective optimization problem. In the article, the authors present a solution of the production scheduling problem by means of an ant colony optimization algorithm. A case study of the algorithm efficiency estimated against some others production scheduling algorithms is presented. Advantages of the ant colony optimization algorithm and its beneficial effect on the manufacturing process are provided.
Inactivated poliovirus vaccine and the final stages of poliovirus eradication.
Hovi, T
2001-03-21
The use of the inactivated poliovirus vaccine (IPV) will increase before and probably also after the global eradication of the wild type poliovirus. Before eradication, the switch from the use of oral poliovirus vaccine (OPV) to IPV has been due to the better safety record of IPV. Introduction of IPV in the regular immunisation schedules is made easier by the development of several combination vaccines, including IPV. Maternal antibodies and young age, often considered problematic for early initiation of IPV schedules, did not compromise optimal maintenance of seropositivity during infancy or long-term persisting antibody levels in our studies. OPV-derived, potentially pathogenic and transmissible poliovirus strains, excreted by some individuals for years, may present a problem for a blunt stopping of all polio immunisations after eradication. Our recent results suggest that locally excreted IgA might have a role in the elimination of poliovirus infection in the intestinal tissues.
ERIC Educational Resources Information Center
Daniel, Clarence H.
This handbook explains planned preventive maintenance program, which is an operational system of maintenance designed to increase the effectiveness of the maintenance staff and the use of maintenance funds through efficient scheduling of inspections and follow-through of work to be performed. Sections are included for the chief administrative…
NASA Technical Reports Server (NTRS)
Phillips, Dave; Haas, William; Barth, Tim; Benjamin, Perakath; Graul, Michael; Bagatourova, Olga
2005-01-01
Range Process Simulation Tool (RPST) is a computer program that assists managers in rapidly predicting and quantitatively assessing the operational effects of proposed technological additions to, and/or upgrades of, complex facilities and engineering systems such as the Eastern Test Range. Originally designed for application to space transportation systems, RPST is also suitable for assessing effects of proposed changes in industrial facilities and large organizations. RPST follows a model-based approach that includes finite-capacity schedule analysis and discrete-event process simulation. A component-based, scalable, open architecture makes RPST easily and rapidly tailorable for diverse applications. Specific RPST functions include: (1) definition of analysis objectives and performance metrics; (2) selection of process templates from a processtemplate library; (3) configuration of process models for detailed simulation and schedule analysis; (4) design of operations- analysis experiments; (5) schedule and simulation-based process analysis; and (6) optimization of performance by use of genetic algorithms and simulated annealing. The main benefits afforded by RPST are provision of information that can be used to reduce costs of operation and maintenance, and the capability for affordable, accurate, and reliable prediction and exploration of the consequences of many alternative proposed decisions.
Application of model predictive control for optimal operation of wind turbines
NASA Astrophysics Data System (ADS)
Yuan, Yuan; Cao, Pei; Tang, J.
2017-04-01
For large-scale wind turbines, reducing maintenance cost is a major challenge. Model predictive control (MPC) is a promising approach to deal with multiple conflicting objectives using the weighed sum approach. In this research, model predictive control method is applied to wind turbine to find an optimal balance between multiple objectives, such as the energy capture, loads on turbine components, and the pitch actuator usage. The actuator constraints are integrated into the objective function at the control design stage. The analysis is carried out in both the partial load region and full load region, and the performances are compared with those of a baseline gain scheduling PID controller. The application of this strategy achieves enhanced balance of component loads, the average power and actuator usages in partial load region.
Browns Ferry turbine team-it`s all in the planning
DOE Office of Scientific and Technical Information (OSTI.GOV)
NONE
1995-05-01
This article illustrates a good example of how a project was creatively completed ahead of schedule and under budget. When the Brown`s Ferry turbine maintenance team took on the task of servicing unit 2`s turbine, the work was like building a ship in a bottle. {open_quotes}We had no room in which to work and only standard tools for the maintenance{close_quotes}, said Jim Roche, turbine manager. The big problem on the turbine floor is that there is only one single overhead crane for lifting the turbine components. All the major turbine components and support equipment are on the same floor. Eachmore » one requires a crane, and there is only one crane. There is limited laydown space. To do the maintenance properly, the team had to have a maintenance schedule it felt comfortable with, industry experience, tools yet to be invented, and money. The design method for this schedule is presented.« less
Management Tools for Bus Maintenance: Current Practices and New Methods. Final Report.
ERIC Educational Resources Information Center
Foerster, James; And Others
Management of bus fleet maintenance requires systematic recordkeeping, management reporting, and work scheduling procedures. Tools for controlling and monitoring routine maintenance activities are in common use. These include defect and fluid consumption reports, work order systems, historical maintenance records, and performance and cost…
75 FR 7411 - Schedule of Water Charges
Federal Register 2010, 2011, 2012, 2013, 2014
2010-02-19
... sale revenues, while the costs of reservoir maintenance and operations, contractual services and..., ``including debt service, operation, maintenance, replacement, reserves, and associated administrative costs... holds funds dedicated to pay the costs of project construction, operation, maintenance, and replacement...
NASA Astrophysics Data System (ADS)
Sembiring, N.; Panjaitan, N.; Saragih, A. F.
2018-02-01
PT. XYZ is a manufacturing company that produces fresh fruit bunches (FFB) to Crude Palm Oil (CPO) and Palm Kernel Oil (PKO). PT. XYZ consists of six work stations: receipt station, sterilizing station, thressing station, pressing station, clarification station, and kernelery station. So far, the company is still implementing corrective maintenance maintenance system for production machines where the machine repair is done after damage occurs. Problems at PT. XYZ is the absence of scheduling engine maintenance in a planned manner resulting in the engine often damaged which can disrupt the smooth production. Another factor that is the problem in this research is the kernel station environment that becomes less convenient for operators such as there are machines and equipment not used in the production area, slippery, muddy, scattered fibers, incomplete use of PPE, and lack of employee discipline. The most commonly damaged machine is in the seed processing station (kernel station) which is cake breaker conveyor machine. The solution of this problem is to propose a schedule plan for maintenance of the machine by using the method of reliability centered maintenance and also the application of 5S. The result of the application of Reliability Centered maintenance method is obtained four components that must be treated scheduled (time directed), namely: for bearing component is 37 days, gearbox component is 97 days, CBC pen component is 35 days and conveyor pedal component is 32 days While after identification the application of 5S obtained the proposed corporate environmental improvement measures in accordance with the principles of 5S where unused goods will be moved from the production area, grouping goods based on their use, determining the procedure of cleaning the production area, conducting inspection in the use of PPE, and making 5S slogans.
Human-Machine Collaborative Optimization via Apprenticeship Scheduling
2016-09-09
prenticeship Scheduling (COVAS), which performs ma- chine learning using human expert demonstration, in conjunction with optimization, to automatically and ef...ficiently produce optimal solutions to challenging real- world scheduling problems. COVAS first learns a policy from human scheduling demonstration via...apprentice- ship learning , then uses this initial solution to provide a tight bound on the value of the optimal solution, thereby substantially
Chen, Tony Y H; Ponsot, Yves; Brouillette, Martin; Tétrault, Jean-Píerre; Tu, Le Mai
2007-06-01
The study evaluates the effect of chronic usage, beyond the recommended maintenance schedule, on the efficacy of electromagnetic lithotripter. To our knowledge, there is no publication investigating the effect of chronic usage on the electromagnetic lithotripter, despite the maintenance schedule established by the manufacturers. Our goal is to verify if the acoustic parameters of the shock wave changed with usage, and if this change could be associated with change in clinical efficacy. This study lasted 18 months. Every 6 months the lithotripter's efficacy was evaluated in two ways: objectively and clinically. Objective efficacy was measured using a piezoelectric hydrophone and artificial stones to capture the acoustic parameters and the crater of fragmentation, respectively. Clinical efficacy data was collected by studying the rate of successful extracorporeal shock wave lithotripsy treatment in patients with urolithiasis. The changes in clinical efficacy, acoustic parameters, and craters of fragmentation were compared and analyzed with appropriate statistical methods. Five hundred twenty five patients participated in the study. The clinical efficacy remained stable throughout the three observation periods (55.7%, 66.2% and 55.5%; p = 0.11). The focal head of the lithotripter was used three times the recommended schedule. There was no obvious change in the acoustic parameters of the shock waves, and the focal zone remained stable. The clinical efficacy of the electromagnetic lithotripter appears to be stable despite usage beyond the recommended maintenance schedule. More studies are needed to validate the safety of this practice.
Code of Federal Regulations, 2010 CFR
2010-07-01
... preventative maintenance schedule and, as applicable, detailed descriptions of the corrective action procedures... compliance with the operation and maintenance requirements that apply to me? 63.7826 Section 63.7826... Compliance Requirements § 63.7826 How do I demonstrate initial compliance with the operation and maintenance...
Informed maintenance for next generation space transportation systems
NASA Astrophysics Data System (ADS)
Fox, Jack J.
2001-02-01
Perhaps the most substantial single obstacle to progress of space exploration and utilization of space for human benefit is the safety & reliability and the inherent cost of launching to, and returning from, space. The primary influence in the high costs of current launch systems (the same is true for commercial and military aircraft and most other reusable systems) is the operations, maintenance and infrastructure portion of the program's total life cycle costs. Reusable Launch Vehicle (RLV) maintenance and design have traditionally been two separate engineering disciplines with often conflicting objectives-maximizing ease of maintenance versus optimizing performance, size and cost. Testability analysis, an element of Informed Maintenance (IM), has been an ad hoc, manual effort, in which maintenance engineers attempt to identify an efficient method of troubleshooting for the given product, with little or no control over product design. Therefore, testability deficiencies in the design cannot be rectified. It is now widely recognized that IM must be engineered into the product at the design stage itself, so that an optimal compromise is achieved between system maintainability and performance. The elements of IM include testability analysis, diagnostics/prognostics, automated maintenance scheduling, automated logistics coordination, paperless documentation and data mining. IM derives its heritage from complimentary NASA science, space and aeronautic enterprises such as the on-board autonomous Remote Agent Architecture recently flown on NASA's Deep Space 1 Probe as well as commercial industries that employ quick turnaround operations. Commercial technologies and processes supporting NASA's IM initiatives include condition based maintenance technologies from Boeing's Commercial 777 Aircraft and Lockheed-Martin's F-22 Fighter, automotive computer diagnostics and autonomous controllers that enable 100,000 mile maintenance free operations, and locomotive monitoring system software. This paper will summarize NASA's long-term strategy, development, and implementation plans for Informed Maintenance for next generation RLVs. This will be done through a convergence into a single IM vision the work being performed throughout NASA, industry and academia. Additionally, a current status of IM development throughout NASA programs such as the Space Shuttle, X-33, X-34 and X-37 will be provided and will conclude with an overview of near-term work that is being initiated in FY00 to support NASA's 2nd Generation Reusable Launch Vehicle Program. .
Informed maintenance for next generation reusable launch systems
NASA Astrophysics Data System (ADS)
Fox, Jack J.; Gormley, Thomas J.
2001-03-01
Perhaps the most substantial single obstacle to progress of space exploration and utilization of space for human benefit is the safety & reliability and the inherent cost of launching to, and returning from, space. The primary influence in the high costs of current launch systems (the same is true for commercial and military aircraft and most other reusable systems) is the operations, maintenance and infrastructure portion of the program's total life cycle costs. Reusable Launch Vehicle (RLV) maintenance and design have traditionally been two separate engineering disciplines with often conflicting objectives - maximizing ease of maintenance versus optimizing performance, size and cost. Testability analysis, an element of Informed Maintenance (IM), has been an ad hoc, manual effort, in which maintenance engineers attempt to identify an efficient method of troubleshooting for the given product, with little or no control over product design. Therefore, testability deficiencies in the design cannot be rectified. It is now widely recognized that IM must be engineered into the product at the design stage itself, so that an optimal compromise is achieved between system maintainability and performance. The elements of IM include testability analysis, diagnostics/prognostics, automated maintenance scheduling, automated logistics coordination, paperless documentation and data mining. IM derives its heritage from complimentary NASA science, space and aeronautic enterprises such as the on-board autonomous Remote Agent Architecture recently flown on NASA's Deep Space 1 Probe as well as commercial industries that employ quick turnaround operations. Commercial technologies and processes supporting NASA's IM initiatives include condition based maintenance technologies from Boeing's Commercial 777 Aircraft and Lockheed-Martin's F-22 Fighter, automotive computer diagnostics and autonomous controllers that enable 100,000 mile maintenance free operations, and locomotive monitoring system software. This paper will summarize NASA's long-term strategy, development, and implementation plans for Informed Maintenance for next generation RLVs. This will be done through a convergence into a single IM vision the work being performed throughout NASA, industry and academia. Additionally, a current status of IM development throughout NASA programs such as the Space Shuttle, X-33, X-34 and X-37 will be provided and will conclude with an overview of near-term work that is being initiated in FY00 to support NASA's 2 nd Generation Reusable Launch Vehicle Program.
Algorithm comparison for schedule optimization in MR fingerprinting.
Cohen, Ouri; Rosen, Matthew S
2017-09-01
In MR Fingerprinting, the flip angles and repetition times are chosen according to a pseudorandom schedule. In previous work, we have shown that maximizing the discrimination between different tissue types by optimizing the acquisition schedule allows reductions in the number of measurements required. The ideal optimization algorithm for this application remains unknown, however. In this work we examine several different optimization algorithms to determine the one best suited for optimizing MR Fingerprinting acquisition schedules. Copyright © 2017 Elsevier Inc. All rights reserved.
14 CFR 145.3 - Definition of terms.
Code of Federal Regulations, 2011 CFR
2011-01-01
... maintenance resulting from unforeseen events; or (2) Scheduled checks that contain servicing and/or... regulations and serving as the primary contact with the FAA. (b) Article means an aircraft, airframe, aircraft... for the work of a certificated repair station that performs maintenance, preventive maintenance...
14 CFR 145.3 - Definition of terms.
Code of Federal Regulations, 2013 CFR
2013-01-01
... maintenance resulting from unforeseen events; or (2) Scheduled checks that contain servicing and/or... regulations and serving as the primary contact with the FAA. (b) Article means an aircraft, airframe, aircraft... for the work of a certificated repair station that performs maintenance, preventive maintenance...
14 CFR 145.3 - Definition of terms.
Code of Federal Regulations, 2012 CFR
2012-01-01
... maintenance resulting from unforeseen events; or (2) Scheduled checks that contain servicing and/or... regulations and serving as the primary contact with the FAA. (b) Article means an aircraft, airframe, aircraft... for the work of a certificated repair station that performs maintenance, preventive maintenance...
14 CFR 145.3 - Definition of terms.
Code of Federal Regulations, 2014 CFR
2014-01-01
... maintenance resulting from unforeseen events; or (2) Scheduled checks that contain servicing and/or... regulations and serving as the primary contact with the FAA. (b) Article means an aircraft, airframe, aircraft... for the work of a certificated repair station that performs maintenance, preventive maintenance...
14 CFR 145.3 - Definition of terms.
Code of Federal Regulations, 2010 CFR
2010-01-01
... maintenance resulting from unforeseen events; or (2) Scheduled checks that contain servicing and/or... regulations and serving as the primary contact with the FAA. (b) Article means an aircraft, airframe, aircraft... for the work of a certificated repair station that performs maintenance, preventive maintenance...
Pollution Prevention in the Land Maintenance System
2000-04-01
pollutants, and greenhouse gases. Canada’s Land Maintenance System consists of first line field units, second line field units, base units and a repair...workshops. For example, extending maintenance schedules, using extended life products and using dehumidification for preservation of equipment will lower
Using Optimization to Improve Test Planning
2017-09-01
friendly and to display the output differently, the test and evaluation test schedule optimization model would be a good tool for the test and... evaluation schedulers. 14. SUBJECT TERMS schedule optimization, test planning 15. NUMBER OF PAGES 223 16. PRICE CODE 17. SECURITY CLASSIFICATION OF...make the input more user-friendly and to display the output differently, the test and evaluation test schedule optimization model would be a good tool
Operation and Maintenance Resources for Small Drinking Water Systems
These documents and tools provide information on identifying treatment technologies that remove multiple contaminants, schedules for maintenance tasks and checklists, and logs for easily recording findings.
ERIC Educational Resources Information Center
Federal Highway Administration (DOT), Washington, DC. Offices of Research and Development.
Part of the series "Managing Highway Maintenance," the unit is designed for use with unit eight, level one, and unit 13, level two, and the certification tests for those units in the series. It contains typical management data and selected highway maintenance standards for the areas of: surface and shoulder; roadside and drainage; traffic…
Optimal radiotherapy dose schedules under parametric uncertainty
NASA Astrophysics Data System (ADS)
Badri, Hamidreza; Watanabe, Yoichi; Leder, Kevin
2016-01-01
We consider the effects of parameter uncertainty on the optimal radiation schedule in the context of the linear-quadratic model. Our interest arises from the observation that if inter-patient variability in normal and tumor tissue radiosensitivity or sparing factor of the organs-at-risk (OAR) are not accounted for during radiation scheduling, the performance of the therapy may be strongly degraded or the OAR may receive a substantially larger dose than the allowable threshold. This paper proposes a stochastic radiation scheduling concept to incorporate inter-patient variability into the scheduling optimization problem. Our method is based on a probabilistic approach, where the model parameters are given by a set of random variables. Our probabilistic formulation ensures that our constraints are satisfied with a given probability, and that our objective function achieves a desired level with a stated probability. We used a variable transformation to reduce the resulting optimization problem to two dimensions. We showed that the optimal solution lies on the boundary of the feasible region and we implemented a branch and bound algorithm to find the global optimal solution. We demonstrated how the configuration of optimal schedules in the presence of uncertainty compares to optimal schedules in the absence of uncertainty (conventional schedule). We observed that in order to protect against the possibility of the model parameters falling into a region where the conventional schedule is no longer feasible, it is required to avoid extremal solutions, i.e. a single large dose or very large total dose delivered over a long period. Finally, we performed numerical experiments in the setting of head and neck tumors including several normal tissues to reveal the effect of parameter uncertainty on optimal schedules and to evaluate the sensitivity of the solutions to the choice of key model parameters.
41 CFR 102-34.275 - What kind of maintenance programs must we have?
Code of Federal Regulations, 2010 CFR
2010-07-01
... 41 Public Contracts and Property Management 3 2010-07-01 2010-07-01 false What kind of maintenance programs must we have? 102-34.275 Section 102-34.275 Public Contracts and Property Management Federal... VEHICLE MANAGEMENT Scheduled Maintenance of Motor Vehicles § 102-34.275 What kind of maintenance programs...
Control systems for heating, ventilating, and air conditioning
DOE Office of Scientific and Technical Information (OSTI.GOV)
Haines, R.W.
1977-01-01
Hundreds of ideas for designing and controlling sophisticated heating, ventilating and air conditioning (HVAC) systems are presented. Information is included on enthalpy control, energy conservation in HVAC systems, on solar heating, cooling and refrigeration systems, and on a self-draining water collector and heater. Computerized control systems and the economics of supervisory systems are discussed. Information is presented on computer system components, software, relevant terminology, and computerized security and fire reporting systems. Benefits of computer systems are explained, along with optimization techniques, data management, maintenance schedules, and energy consumption. A bibliography, glossaries of HVAC terminology, abbreviations, symbols, and a subject indexmore » are provided. (LCL)« less
Data transmission system and method
NASA Technical Reports Server (NTRS)
Bruck, Jehoshua (Inventor); Langberg, Michael (Inventor); Sprintson, Alexander (Inventor)
2010-01-01
A method of transmitting data packets, where randomness is added to the schedule. Universal broadcast schedules using encoding and randomization techniques are also discussed, together with optimal randomized schedules and an approximation algorithm for finding near-optimal schedules.
Optimizing sleep to maximize performance: implications and recommendations for elite athletes.
Simpson, N S; Gibbs, E L; Matheson, G O
2017-03-01
Despite a growing body of literature demonstrating a positive relationship between sleep and optimal performance, athletes often have low sleep quality and quantity. Insufficient sleep among athletes may be due to scheduling constraints and the low priority of sleep relative to other training demands, as well as a lack of awareness of the role of sleep in optimizing athletic performance. Domains of athletic performance (e.g., speed and endurance), neurocognitive function (e.g., attention and memory), and physical health (e.g., illness and injury risk, and weight maintenance) have all been shown to be negatively affected by insufficient sleep or experimentally modeled sleep restriction. However, healthy adults are notoriously poor at self-assessing the magnitude of the impact of sleep loss, underscoring the need for increased awareness of the importance of sleep among both elite athletes and practitioners managing their care. Strategies to optimize sleep quality and quantity in athletes include approaches for expanding total sleep duration, improving sleep environment, and identifying potential sleep disorders. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.
Zsigraiova, Zdena; Semiao, Viriato; Beijoco, Filipa
2013-04-01
This work proposes an innovative methodology for the reduction of the operation costs and pollutant emissions involved in the waste collection and transportation. Its innovative feature lies in combining vehicle route optimization with that of waste collection scheduling. The latter uses historical data of the filling rate of each container individually to establish the daily circuits of collection points to be visited, which is more realistic than the usual assumption of a single average fill-up rate common to all the system containers. Moreover, this allows for the ahead planning of the collection scheduling, which permits a better system management. The optimization process of the routes to be travelled makes recourse to Geographical Information Systems (GISs) and uses interchangeably two optimization criteria: total spent time and travelled distance. Furthermore, rather than using average values, the relevant parameters influencing fuel consumption and pollutant emissions, such as vehicle speed in different roads and loading weight, are taken into consideration. The established methodology is applied to the glass-waste collection and transportation system of Amarsul S.A., in Barreiro. Moreover, to isolate the influence of the dynamic load on fuel consumption and pollutant emissions a sensitivity analysis of the vehicle loading process is performed. For that, two hypothetical scenarios are tested: one with the collected volume increasing exponentially along the collection path; the other assuming that the collected volume decreases exponentially along the same path. The results evidence unquestionable beneficial impacts of the optimization on both the operation costs (labor and vehicles maintenance and fuel consumption) and pollutant emissions, regardless the optimization criterion used. Nonetheless, such impact is particularly relevant when optimizing for time yielding substantial improvements to the existing system: potential reductions of 62% for the total spent time, 43% for the fuel consumption and 40% for the emitted pollutants. This results in total cost savings of 57%, labor being the greatest contributor, representing over €11,000 per year for the two vehicles collecting glass-waste. Moreover, it is shown herein that the dynamic loading process of the collection vehicle impacts on both the fuel consumption and on pollutant emissions. Copyright © 2012 Elsevier Ltd. All rights reserved.
NASA Technical Reports Server (NTRS)
1980-01-01
Information concerning the installation, operation, and maintenance of the pyramidal Solar System for space heating and domestic hot water is presented. Principles of operation, sequence of installation, and procedures for the operation and maintenance of each subsystem making up the solar system are presented. Troubleshooting charts and maintenance schedules are presented.
NASA Astrophysics Data System (ADS)
1980-09-01
Information concerning the installation, operation, and maintenance of the pyramidal Solar System for space heating and domestic hot water is presented. Principles of operation, sequence of installation, and procedures for the operation and maintenance of each subsystem making up the solar system are presented. Troubleshooting charts and maintenance schedules are presented.
18 CFR 368.3 - Schedule of records and periods of retention.
Code of Federal Regulations, 2013 CFR
2013-04-01
... companies. (c) Paid checks and receipts for payments of specific vouchers 5 years. (d) Authorization for the... and reports of condition of property Destroy when superseded. Maintenance 13. Maintenance project and work orders: (a) Authorizations for expenditures for maintenance work to be covered by project or work...
18 CFR 368.3 - Schedule of records and periods of retention.
Code of Federal Regulations, 2014 CFR
2014-04-01
... companies. (c) Paid checks and receipts for payments of specific vouchers 5 years. (d) Authorization for the... and reports of condition of property Destroy when superseded. Maintenance 13. Maintenance project and work orders: (a) Authorizations for expenditures for maintenance work to be covered by project or work...
76 FR 73477 - Airworthiness Directives; BAE SYSTEMS (Operations) Limited Airplanes
Federal Register 2010, 2011, 2012, 2013, 2014
2011-11-29
... of the AMM [aircraft maintenance manual] to introduce a new hydraulic filter assembly life limit and...: The BAe 146/AVRO 146-RJ Aircraft Maintenance Manual (AMM) includes chapters 05-10 ``Time Limits'', 05...'' and 05-20 ``Scheduled Maintenance Checks'', some sub-chapters of which have been identified as...
18 CFR 368.3 - Schedule of records and periods of retention.
Code of Federal Regulations, 2012 CFR
2012-04-01
... companies. (c) Paid checks and receipts for payments of specific vouchers 5 years. (d) Authorization for the... and reports of condition of property Destroy when superseded. Maintenance 13. Maintenance project and work orders: (a) Authorizations for expenditures for maintenance work to be covered by project or work...
46 CFR 109.301 - Operational readiness, maintenance, and inspection of lifesaving equipment.
Code of Federal Regulations, 2012 CFR
2012-10-01
... and cleaning each fuel tank, and refilling it with fresh fuel. (2) Each davit, winch, fall and other...(e); (ii) Maintenance and repair instructions; (iii) A schedule of periodic maintenance; (iv) A... repair equipment. Spare parts and repair equipment must be provided for each lifesaving appliance and...
46 CFR 109.301 - Operational readiness, maintenance, and inspection of lifesaving equipment.
Code of Federal Regulations, 2011 CFR
2011-10-01
... and cleaning each fuel tank, and refilling it with fresh fuel. (2) Each davit, winch, fall and other...(e); (ii) Maintenance and repair instructions; (iii) A schedule of periodic maintenance; (iv) A... repair equipment. Spare parts and repair equipment must be provided for each lifesaving appliance and...
46 CFR 109.301 - Operational readiness, maintenance, and inspection of lifesaving equipment.
Code of Federal Regulations, 2014 CFR
2014-10-01
... and cleaning each fuel tank, and refilling it with fresh fuel. (2) Each davit, winch, fall and other...(e); (ii) Maintenance and repair instructions; (iii) A schedule of periodic maintenance; (iv) A... repair equipment. Spare parts and repair equipment must be provided for each lifesaving appliance and...
46 CFR 109.301 - Operational readiness, maintenance, and inspection of lifesaving equipment.
Code of Federal Regulations, 2013 CFR
2013-10-01
... and cleaning each fuel tank, and refilling it with fresh fuel. (2) Each davit, winch, fall and other...(e); (ii) Maintenance and repair instructions; (iii) A schedule of periodic maintenance; (iv) A... repair equipment. Spare parts and repair equipment must be provided for each lifesaving appliance and...
40 CFR 1065.410 - Maintenance limits for stabilized test engines.
Code of Federal Regulations, 2011 CFR
2011-07-01
...) AIR POLLUTION CONTROLS ENGINE-TESTING PROCEDURES Engine Selection, Preparation, and Maintenance § 1065... scheduled maintenance on emission data engines must be representative of what is planned to be available to... no longer use it as an emission-data engine. Also, if your test engine has a major mechanical failure...
40 CFR 1065.410 - Maintenance limits for stabilized test engines.
Code of Federal Regulations, 2010 CFR
2010-07-01
...) AIR POLLUTION CONTROLS ENGINE-TESTING PROCEDURES Engine Selection, Preparation, and Maintenance § 1065... scheduled maintenance on emission data engines must be representative of what is planned to be available to... no longer use it as an emission-data engine. Also, if your test engine has a major mechanical failure...
49 CFR Appendix A to Part 224 - Schedule of Civil Penalties1
Code of Federal Regulations, 2012 CFR
2012-10-01
... 49 Transportation 4 2012-10-01 2012-10-01 false Schedule of Civil Penalties1 A Appendix A to Part 224 Transportation Other Regulations Relating to Transportation (Continued) FEDERAL RAILROAD... Appendix A to Part 224—Schedule of Civil Penalties1 Subpart B—Application, Inspection, and Maintenance of...
75 FR 56517 - Privacy Act of 1974; System of Records
Federal Register 2010, 2011, 2012, 2013, 2014
2010-09-16
... entry and replace with ``5 U.S.C. 6120, Flexible and Compressed Work Schedules, Purposes; DoD Directive... and tour of duty at the alternative worksite; regular work schedule (8 hours a day, flexitour or compressed); telework schedule. Authority for maintenance of the system: 5 U.S.C. 6120, Flexible and...
Software for Planning Scientific Activities on Mars
NASA Technical Reports Server (NTRS)
Ai-Chang, Mitchell; Bresina, John; Jonsson, Ari; Hsu, Jennifer; Kanefsky, Bob; Morris, Paul; Rajan, Kanna; Yglesias, Jeffrey; Charest, Len; Maldague, Pierre
2003-01-01
Mixed-Initiative Activity Plan Generator (MAPGEN) is a ground-based computer program for planning and scheduling the scientific activities of instrumented exploratory robotic vehicles, within the limitations of available resources onboard the vehicle. MAPGEN is a combination of two prior software systems: (1) an activity-planning program, APGEN, developed at NASA s Jet Propulsion Laboratory and (2) the Europa planner/scheduler from NASA Ames Research Center. MAPGEN performs all of the following functions: Automatic generation of plans and schedules for scientific and engineering activities; Testing of hypotheses (or what-if analyses of various scenarios); Editing of plans; Computation and analysis of resources; and Enforcement and maintenance of constraints, including resolution of temporal and resource conflicts among planned activities. MAPGEN can be used in either of two modes: one in which the planner/scheduler is turned off and only the basic APGEN functionality is utilized, or one in which both component programs are used to obtain the full planning, scheduling, and constraint-maintenance functionality.
NASA Technical Reports Server (NTRS)
Rash, James L.
2010-01-01
NASA's space data-communications infrastructure, the Space Network and the Ground Network, provide scheduled (as well as some limited types of unscheduled) data-communications services to user spacecraft via orbiting relay satellites and ground stations. An implementation of the methods and algorithms disclosed herein will be a system that produces globally optimized schedules with not only optimized service delivery by the space data-communications infrastructure but also optimized satisfaction of all user requirements and prescribed constraints, including radio frequency interference (RFI) constraints. Evolutionary search, a class of probabilistic strategies for searching large solution spaces, constitutes the essential technology in this disclosure. Also disclosed are methods and algorithms for optimizing the execution efficiency of the schedule-generation algorithm itself. The scheduling methods and algorithms as presented are adaptable to accommodate the complexity of scheduling the civilian and/or military data-communications infrastructure. Finally, the problem itself, and the methods and algorithms, are generalized and specified formally, with applicability to a very broad class of combinatorial optimization problems.
Survey of Condition Indicators for Condition Monitoring Systems (Open Access)
2014-09-29
Hinesburg, Vermont, 05461, USA jz@renewablenrgsystems.com ABSTRACT Currently, the wind energy industry is swiftly changing its maintenance strategy...from schedule based maintenance to predictive based maintenance . Condition monitoring systems (CMS) play an important role in the predictive... maintenance cycle. As condition monitoring systems are being adopted by more and more OEM and O&M service providers from the wind energy industry, it is
Maintenance Downtime April 23, 2014
Atmospheric Science Data Center
2014-04-23
Date(s): Wednesday, April 23, 2014 Time: 7:00 am - 5:00 pm EDT Event ... Due to scheduled maintenance Wednesday, April 23, 2014: The Data Pool, MISR order and browse tools, TES and MOPITT Search ...
Maintenance Downtime September 18, 2013
Atmospheric Science Data Center
2013-09-16
Date(s): Wednesday, September 18, 2013 Time: 9:00 - 11:00 am EST Event Impact: Due to scheduled maintenance Wednesday, September 18, 2013: The MISR order and browse tools, Reverb, and AMAPS will be ...
A Novel Particle Swarm Optimization Approach for Grid Job Scheduling
NASA Astrophysics Data System (ADS)
Izakian, Hesam; Tork Ladani, Behrouz; Zamanifar, Kamran; Abraham, Ajith
This paper represents a Particle Swarm Optimization (PSO) algorithm, for grid job scheduling. PSO is a population-based search algorithm based on the simulation of the social behavior of bird flocking and fish schooling. Particles fly in problem search space to find optimal or near-optimal solutions. In this paper we used a PSO approach for grid job scheduling. The scheduler aims at minimizing makespan and flowtime simultaneously. Experimental studies show that the proposed novel approach is more efficient than the PSO approach reported in the literature.
46 CFR 199.190 - Operational readiness, maintenance, and inspection of lifesaving equipment.
Code of Federal Regulations, 2012 CFR
2012-10-01
... each fuel tank must be emptied, cleaned, and refilled with fresh fuel. (2) Each davit, winch, fall, and... required under paragraph (e) of this section. (ii) Maintenance and repair instructions. (iii) A schedule of... planned maintenance program that includes the items listed in that paragraph. (c) Spare parts and repair...
46 CFR 199.190 - Operational readiness, maintenance, and inspection of lifesaving equipment.
Code of Federal Regulations, 2013 CFR
2013-10-01
... each fuel tank must be emptied, cleaned, and refilled with fresh fuel. (2) Each davit, winch, fall, and... required under paragraph (e) of this section. (ii) Maintenance and repair instructions. (iii) A schedule of... planned maintenance program that includes the items listed in that paragraph. (c) Spare parts and repair...
46 CFR 199.190 - Operational readiness, maintenance, and inspection of lifesaving equipment.
Code of Federal Regulations, 2014 CFR
2014-10-01
... each fuel tank must be emptied, cleaned, and refilled with fresh fuel. (2) Each davit, winch, fall, and... required under paragraph (e) of this section. (ii) Maintenance and repair instructions. (iii) A schedule of... planned maintenance program that includes the items listed in that paragraph. (c) Spare parts and repair...
46 CFR 199.190 - Operational readiness, maintenance, and inspection of lifesaving equipment.
Code of Federal Regulations, 2011 CFR
2011-10-01
... each fuel tank must be emptied, cleaned, and refilled with fresh fuel. (2) Each davit, winch, fall, and... required under paragraph (e) of this section. (ii) Maintenance and repair instructions. (iii) A schedule of... planned maintenance program that includes the items listed in that paragraph. (c) Spare parts and repair...
40 CFR 1054.145 - Are there interim provisions that apply only for a limited time?
Code of Federal Regulations, 2010 CFR
2010-07-01
... scheduled emission-related maintenance falls within 10 hours of a test point, delay the maintenance until the engine reaches the test point. Measure emissions before and after peforming the maintenance. Use... example, for the fuel line permeation standards starting in 2012, equipment manufacturers may order a...
Maglev guideway cost and construction schedule assessment
DOE Office of Scientific and Technical Information (OSTI.GOV)
Plotkin, D.; Kim, S.
1997-05-01
A summary of construction cost and scheduling information is presented for four maglev guideway designs on an example route from Baltimore, MD to Newark, NJ. This work results from the National Maglev Initiative (NMI), a government-industry effort from 1989 to 1994. The system design concepts used as a basis for developing cost and construction scheduling information, were submitted by four industry consortia solely for this analysis, and represent their own unpublished designs. The detailed cost and construction schedule analyses cover the main guideway only. A summary estimate was made for stations, power distribution systems, maintenance facilities, and other types ofmore » infrastructure. The results of the analyses indicate a number of design aspects which must receive further consideration by future designers. These aspects will affect the practical and economic construction and long-term maintenance of a high-speed maglev guideway.« less
Maintaining consistency between planning hierarchies: Techniques and applications
NASA Technical Reports Server (NTRS)
Zoch, David R.
1987-01-01
In many planning and scheduling environments, it is desirable to be able to view and manipulate plans at different levels of abstraction, allowing the users the option of viewing and manipulating either a very detailed representation of the plan or a high-level more abstract version of the plan. Generating a detailed plan from a more abstract plan requires domain-specific planning/scheduling knowledge; the reverse process of generating a high-level plan from a detailed plan Reverse Plan Maintenance, or RPM) requires having the system remember the actions it took based on its domain-specific knowledge and its reasons for taking those actions. This reverse plan maintenance process is described as implemented in a specific planning and scheduling tool, The Mission Operations Planning Assistant (MOPA), as well as the applications of RPM to other planning and scheduling problems; emphasizing the knowledge that is needed to maintain the correspondence between the different hierarchical planning levels.
NASA Technical Reports Server (NTRS)
Rash, James
2014-01-01
NASA's space data-communications infrastructure-the Space Network and the Ground Network-provide scheduled (as well as some limited types of unscheduled) data-communications services to user spacecraft. The Space Network operates several orbiting geostationary platforms (the Tracking and Data Relay Satellite System (TDRSS)), each with its own servicedelivery antennas onboard. The Ground Network operates service-delivery antennas at ground stations located around the world. Together, these networks enable data transfer between user spacecraft and their mission control centers on Earth. Scheduling data-communications events for spacecraft that use the NASA communications infrastructure-the relay satellites and the ground stations-can be accomplished today with software having an operational heritage dating from the 1980s or earlier. An implementation of the scheduling methods and algorithms disclosed and formally specified herein will produce globally optimized schedules with not only optimized service delivery by the space data-communications infrastructure but also optimized satisfaction of all user requirements and prescribed constraints, including radio frequency interference (RFI) constraints. Evolutionary algorithms, a class of probabilistic strategies for searching large solution spaces, is the essential technology invoked and exploited in this disclosure. Also disclosed are secondary methods and algorithms for optimizing the execution efficiency of the schedule-generation algorithms themselves. The scheduling methods and algorithms as presented are adaptable to accommodate the complexity of scheduling the civilian and/or military data-communications infrastructure within the expected range of future users and space- or ground-based service-delivery assets. Finally, the problem itself, and the methods and algorithms, are generalized and specified formally. The generalized methods and algorithms are applicable to a very broad class of combinatorial-optimization problems that encompasses, among many others, the problem of generating optimal space-data communications schedules.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Tahvili, Sahar; Österberg, Jonas; Silvestrov, Sergei
One of the most important factors in the operations of many cooperations today is to maximize profit and one important tool to that effect is the optimization of maintenance activities. Maintenance activities is at the largest level divided into two major areas, corrective maintenance (CM) and preventive maintenance (PM). When optimizing maintenance activities, by a maintenance plan or policy, we seek to find the best activities to perform at each point in time, be it PM or CM. We explore the use of stochastic simulation, genetic algorithms and other tools for solving complex maintenance planning optimization problems in terms ofmore » a suggested framework model based on discrete event simulation.« less
Carbon emission and sequestration of urban turfgrass systems in Hong Kong.
Kong, Ling; Shi, Zhengjun; Chu, L M
2014-03-01
Climate change is more than just a global issue. Locally released carbon dioxide may lead to a rise in global ambient temperature and influence the surrounding climate. Urban greenery may mitigate this as they can remove carbon dioxide by storing carbon in substrates and vegetation. On the other hand, urban greenery systems which are under intense management and maintenance may contribute to the emission of carbon dioxide or other greenhouse gases. The impact of urban greenery on carbon balance in major metropolitan areas thus remains controversial. We investigated the carbon footprints of urban turf operation and maintenance by conducting a research questionnaire on different Hong Kong turfs in 2012, and showed that turf maintenance contributed 0.17 to 0.63 kg Ce m(-2)y(-1) to carbon emissions. We also determined the carbon storage of turfs at 0.05 to 0.21 kg C m(-2) for aboveground grass biomass and 1.26 to 4.89 kg C m(-2) for soils (to 15 cm depth). We estimated that the carbon sink capacity of turfs could be offset by carbon emissions in 5-24 years under current management patterns, shifting from carbon sink to carbon source. Our study suggested that maintenance management played a key role in the carbon budget and footprint of urban greeneries. The environmental impact of turfgrass systems can be optimized by shifting away from empirically designed maintenance schedules towards rational ones based on carbon sink and emission principles. Copyright © 2014 Elsevier B.V. All rights reserved.
Optimizing preventive maintenance policy: A data-driven application for a light rail braking system.
Corman, Francesco; Kraijema, Sander; Godjevac, Milinko; Lodewijks, Gabriel
2017-10-01
This article presents a case study determining the optimal preventive maintenance policy for a light rail rolling stock system in terms of reliability, availability, and maintenance costs. The maintenance policy defines one of the three predefined preventive maintenance actions at fixed time-based intervals for each of the subsystems of the braking system. Based on work, maintenance, and failure data, we model the reliability degradation of the system and its subsystems under the current maintenance policy by a Weibull distribution. We then analytically determine the relation between reliability, availability, and maintenance costs. We validate the model against recorded reliability and availability and get further insights by a dedicated sensitivity analysis. The model is then used in a sequential optimization framework determining preventive maintenance intervals to improve on the key performance indicators. We show the potential of data-driven modelling to determine optimal maintenance policy: same system availability and reliability can be achieved with 30% maintenance cost reduction, by prolonging the intervals and re-grouping maintenance actions.
Optimizing preventive maintenance policy: A data-driven application for a light rail braking system
Corman, Francesco; Kraijema, Sander; Godjevac, Milinko; Lodewijks, Gabriel
2017-01-01
This article presents a case study determining the optimal preventive maintenance policy for a light rail rolling stock system in terms of reliability, availability, and maintenance costs. The maintenance policy defines one of the three predefined preventive maintenance actions at fixed time-based intervals for each of the subsystems of the braking system. Based on work, maintenance, and failure data, we model the reliability degradation of the system and its subsystems under the current maintenance policy by a Weibull distribution. We then analytically determine the relation between reliability, availability, and maintenance costs. We validate the model against recorded reliability and availability and get further insights by a dedicated sensitivity analysis. The model is then used in a sequential optimization framework determining preventive maintenance intervals to improve on the key performance indicators. We show the potential of data-driven modelling to determine optimal maintenance policy: same system availability and reliability can be achieved with 30% maintenance cost reduction, by prolonging the intervals and re-grouping maintenance actions. PMID:29278245
Duan, Litian; Wang, Zizhong John; Duan, Fu
2016-11-16
In the multiple-reader environment (MRE) of radio frequency identification (RFID) system, multiple readers are often scheduled to interrogate the randomized tags via operating at different time slots or frequency channels to decrease the signal interferences. Based on this, a Geometric Distribution-based Multiple-reader Scheduling Optimization Algorithm using Artificial Immune System (GD-MRSOA-AIS) is proposed to fairly and optimally schedule the readers operating from the viewpoint of resource allocations. GD-MRSOA-AIS is composed of two parts, where a geometric distribution function combined with the fairness consideration is first introduced to generate the feasible scheduling schemes for reader operation. After that, artificial immune system (including immune clone, immune mutation and immune suppression) quickly optimize these feasible ones as the optimal scheduling scheme to ensure that readers are fairly operating with larger effective interrogation range and lower interferences. Compared with the state-of-the-art algorithm, the simulation results indicate that GD-MRSOA-AIS could efficiently schedules the multiple readers operating with a fairer resource allocation scheme, performing in larger effective interrogation range.
Duan, Litian; Wang, Zizhong John; Duan, Fu
2016-01-01
In the multiple-reader environment (MRE) of radio frequency identification (RFID) system, multiple readers are often scheduled to interrogate the randomized tags via operating at different time slots or frequency channels to decrease the signal interferences. Based on this, a Geometric Distribution-based Multiple-reader Scheduling Optimization Algorithm using Artificial Immune System (GD-MRSOA-AIS) is proposed to fairly and optimally schedule the readers operating from the viewpoint of resource allocations. GD-MRSOA-AIS is composed of two parts, where a geometric distribution function combined with the fairness consideration is first introduced to generate the feasible scheduling schemes for reader operation. After that, artificial immune system (including immune clone, immune mutation and immune suppression) quickly optimize these feasible ones as the optimal scheduling scheme to ensure that readers are fairly operating with larger effective interrogation range and lower interferences. Compared with the state-of-the-art algorithm, the simulation results indicate that GD-MRSOA-AIS could efficiently schedules the multiple readers operating with a fairer resource allocation scheme, performing in larger effective interrogation range. PMID:27854342
Range and mission scheduling automation using combined AI and operations research techniques
NASA Technical Reports Server (NTRS)
Arbabi, Mansur; Pfeifer, Michael
1987-01-01
Ground-based systems for Satellite Command, Control, and Communications (C3) operations require a method for planning, scheduling and assigning the range resources such as: antenna systems scattered around the world, communications systems, and personnel. The method must accommodate user priorities, last minute changes, maintenance requirements, and exceptions from nominal requirements. Described are computer programs which solve 24 hour scheduling problems, using heuristic algorithms and a real time interactive scheduling process.
Li, Xuejun; Xu, Jia; Yang, Yun
2015-01-01
Cloud workflow system is a kind of platform service based on cloud computing. It facilitates the automation of workflow applications. Between cloud workflow system and its counterparts, market-oriented business model is one of the most prominent factors. The optimization of task-level scheduling in cloud workflow system is a hot topic. As the scheduling is a NP problem, Ant Colony Optimization (ACO) and Particle Swarm Optimization (PSO) have been proposed to optimize the cost. However, they have the characteristic of premature convergence in optimization process and therefore cannot effectively reduce the cost. To solve these problems, Chaotic Particle Swarm Optimization (CPSO) algorithm with chaotic sequence and adaptive inertia weight factor is applied to present the task-level scheduling. Chaotic sequence with high randomness improves the diversity of solutions, and its regularity assures a good global convergence. Adaptive inertia weight factor depends on the estimate value of cost. It makes the scheduling avoid premature convergence by properly balancing between global and local exploration. The experimental simulation shows that the cost obtained by our scheduling is always lower than the other two representative counterparts.
Li, Xuejun; Xu, Jia; Yang, Yun
2015-01-01
Cloud workflow system is a kind of platform service based on cloud computing. It facilitates the automation of workflow applications. Between cloud workflow system and its counterparts, market-oriented business model is one of the most prominent factors. The optimization of task-level scheduling in cloud workflow system is a hot topic. As the scheduling is a NP problem, Ant Colony Optimization (ACO) and Particle Swarm Optimization (PSO) have been proposed to optimize the cost. However, they have the characteristic of premature convergence in optimization process and therefore cannot effectively reduce the cost. To solve these problems, Chaotic Particle Swarm Optimization (CPSO) algorithm with chaotic sequence and adaptive inertia weight factor is applied to present the task-level scheduling. Chaotic sequence with high randomness improves the diversity of solutions, and its regularity assures a good global convergence. Adaptive inertia weight factor depends on the estimate value of cost. It makes the scheduling avoid premature convergence by properly balancing between global and local exploration. The experimental simulation shows that the cost obtained by our scheduling is always lower than the other two representative counterparts. PMID:26357510
Applying the TOC Project Management to Operation and Maintenance Scheduling of a Research Vessel
NASA Astrophysics Data System (ADS)
Manti, M. Firdausi; Fujimoto, Hideo; Chen, Lian-Yi
Marine research vessels and their systems are major assets in the marine resources development. Since the running costs for the ship are very high, it is necessary to reduce the total cost by an efficient scheduling for operation and maintenance. To reduce project period and make it efficient, we applied TOC project management method that is a project management approach developed by Dr. Eli Goldratt. It challenges traditional approaches to project management. It will become the most important improvement in the project management since the development of PERT and critical path methodologies. As a case study, we presented the marine geology research project for the purpose of operations in addition to repair on the repairing dock projects for maintenance of vessels.
Waning of vaccine-induced immunity to measles in kidney transplanted children.
Rocca, Salvatore; Santilli, Veronica; Cotugno, Nicola; Concato, Carlo; Manno, Emma Concetta; Nocentini, Giulia; Macchiarulo, Giulia; Cancrini, Caterina; Finocchi, Andrea; Guzzo, Isabella; Dello Strologo, Luca; Palma, Paolo
2016-09-01
Vaccine-preventable diseases are a significant cause of morbidity and mortality in solid organ transplant recipients who undergo immunosuppression after transplantation. Data on immune responses and long-term maintenance after vaccinations in such population are still limited.We cross-sectionally evaluated the maintenance of immune response to measles vaccine in kidney transplanted children on immunosuppressive therapy. Measles-specific enzyme-linked immunosorbent assay and B-cell enzyme-linked immunosorbent spot were performed in 74 kidney transplant patients (Tps) and in 23 healthy controls (HCs) previously vaccinated and tested for humoral protection against measles. The quality of measles antibody response was measured by avidity test. B-cell phenotype, investigated via flow cytometry, was further correlated to the ability of Tps to maintain protective humoral responses to measles over time.We observed the loss of vaccine-induced immunity against measles in 19% of Tps. Nonseroprotected children showed signs of impaired B-cell distribution as well as immune senescence and lower antibody avidity. We further reported as time elapsed between vaccination and transplantation, as well as the vaccine administration during dialysis are clinical factors affecting the maintenance of the immune memory response against measles.Tps present both quantitative and qualitative alterations in the maintenance of protective immunity to measles vaccine. Prospective studies are needed to optimize the vaccination schedules in kidney transplant recipients in order to increase the immunization coverage over time in this population.
Code of Federal Regulations, 2010 CFR
2010-01-01
... authorization for the type aircraft checked. (3) A schedule that provides for the performance of bench checks..., Equipment, and Maintenance A Appendix A to Part 91 Aeronautics and Space FEDERAL AVIATION ADMINISTRATION... Maintenance 1. Category II Manual (a) Application for approval. An applicant for approval of a Category II...
Code of Federal Regulations, 2013 CFR
2013-01-01
... authorization for the type aircraft checked. (3) A schedule that provides for the performance of bench checks..., Equipment, and Maintenance A Appendix A to Part 91 Aeronautics and Space FEDERAL AVIATION ADMINISTRATION... Maintenance 1. Category II Manual (a) Application for approval. An applicant for approval of a Category II...
Code of Federal Regulations, 2012 CFR
2012-01-01
... authorization for the type aircraft checked. (3) A schedule that provides for the performance of bench checks..., Equipment, and Maintenance A Appendix A to Part 91 Aeronautics and Space FEDERAL AVIATION ADMINISTRATION... Maintenance 1. Category II Manual (a) Application for approval. An applicant for approval of a Category II...
Code of Federal Regulations, 2014 CFR
2014-01-01
... authorization for the type aircraft checked. (3) A schedule that provides for the performance of bench checks..., Equipment, and Maintenance A Appendix A to Part 91 Aeronautics and Space FEDERAL AVIATION ADMINISTRATION... Maintenance 1. Category II Manual (a) Application for approval. An applicant for approval of a Category II...
Code of Federal Regulations, 2011 CFR
2011-01-01
... authorization for the type aircraft checked. (3) A schedule that provides for the performance of bench checks..., Equipment, and Maintenance A Appendix A to Part 91 Aeronautics and Space FEDERAL AVIATION ADMINISTRATION... Maintenance 1. Category II Manual (a) Application for approval. An applicant for approval of a Category II...
40 CFR 1054.145 - Are there interim provisions that apply only for a limited time?
Code of Federal Regulations, 2011 CFR
2011-07-01
... scheduled emission-related maintenance falls within 10 hours of a test point, delay the maintenance until the engine reaches the test point. Measure emissions before and after peforming the maintenance. Use... data under 40 CFR 1060.235(e) for your emission family. (j) Continued use of 40 CFR part 90 test...
40 CFR 1054.145 - Are there interim provisions that apply only for a limited time?
Code of Federal Regulations, 2012 CFR
2012-07-01
... scheduled emission-related maintenance falls within 10 hours of a test point, delay the maintenance until the engine reaches the test point. Measure emissions before and after peforming the maintenance. Use... data under 40 CFR 1060.235(e) for your emission family. (j) Continued use of 40 CFR part 90 test...
NASA Astrophysics Data System (ADS)
Zhang, Xingong; Yin, Yunqiang; Wu, Chin-Chia
2017-01-01
There is a situation found in many manufacturing systems, such as steel rolling mills, fire fighting or single-server cycle-queues, where a job that is processed later consumes more time than that same job when processed earlier. The research finds that machine maintenance can improve the worsening of processing conditions. After maintenance activity, the machine will be restored. The maintenance duration is a positive and non-decreasing differentiable convex function of the total processing times of the jobs between maintenance activities. Motivated by this observation, the makespan and the total completion time minimization problems in the scheduling of jobs with non-decreasing rates of job processing time on a single machine are considered in this article. It is shown that both the makespan and the total completion time minimization problems are NP-hard in the strong sense when the number of maintenance activities is arbitrary, while the makespan minimization problem is NP-hard in the ordinary sense when the number of maintenance activities is fixed. If the deterioration rates of the jobs are identical and the maintenance duration is a linear function of the total processing times of the jobs between maintenance activities, then this article shows that the group balance principle is satisfied for the makespan minimization problem. Furthermore, two polynomial-time algorithms are presented for solving the makespan problem and the total completion time problem under identical deterioration rates, respectively.
1989-12-01
to construct because the mechanism is a dispatching procedure. Since all nonpreemptive schedules are contained in the set of all preemptive schedules...the optimal value of T’.. in the preemptive case is at least a lower bound on the optimal T., for the nonpreemptive schedules. This principle is the...adapt to changes in the enviro.nment. In hard real-time systems, tasks are also distinguished as preemptable and nonpreemptable . A task is preemptable
Particle swarm optimization based space debris surveillance network scheduling
NASA Astrophysics Data System (ADS)
Jiang, Hai; Liu, Jing; Cheng, Hao-Wen; Zhang, Yao
2017-02-01
The increasing number of space debris has created an orbital debris environment that poses increasing impact risks to existing space systems and human space flights. For the safety of in-orbit spacecrafts, we should optimally schedule surveillance tasks for the existing facilities to allocate resources in a manner that most significantly improves the ability to predict and detect events involving affected spacecrafts. This paper analyzes two criteria that mainly affect the performance of a scheduling scheme and introduces an artificial intelligence algorithm into the scheduling of tasks of the space debris surveillance network. A new scheduling algorithm based on the particle swarm optimization algorithm is proposed, which can be implemented in two different ways: individual optimization and joint optimization. Numerical experiments with multiple facilities and objects are conducted based on the proposed algorithm, and simulation results have demonstrated the effectiveness of the proposed algorithm.
2008-03-01
order fulfillment visibility, Kanban deployment, inventory count can be made visually, machines and tool labeling, costs, preventive maintenance...order fulfillment, computer scheduling versus Kanban , pull versus push systems, flow time efficiencies, back room costs of scheduling, MRP costs
DOE Office of Scientific and Technical Information (OSTI.GOV)
Bagdon, M.J.; Martin, P.J.
1997-06-01
In 1994, Novus Engineering and EME Group began a project for the New York State Office of Mental Health (OMH) to maximize the use and benefit of energy management systems (EMS) installed at various large psychiatric hospitals throughout New York State. The project, which was funded and managed by the Dormitory Authority of the State of New York (DASNY), had three major objectives: (1) Maximize Energy Savings - Novus staff quickly learned that EMS systems as set up by contractors are far from optimal for generating energy savings. This part of the program revealed numerous opportunities for increased energy savings,more » such as: fine tuning proportional/integral/derivative (PID) loops to eliminate valve and damper hunting; adjusting temperature reset schedules to reduce energy consumption and provide more uniform temperature conditions throughout the facilities; and modifying equipment schedules. (2) Develop Monitoring Protocols - Large EMS systems are so complex that they require a systematic approach to daily, monthly and seasonal monitoring of building system conditions in order to locate system problems before they turn into trouble calls or equipment failures. In order to assist local facility staff in their monitoring efforts, Novus prepared user-friendly handbooks on each EMS. These included monitoring protocols tailored to each facility. (3) Provide Staff Training - When a new EMS is installed at a facility, it is frequently the maintenance staffs first exposure to a complex computerized system. Without proper training in what to look for, staff use of the EMS is generally very limited. With proper training, staff can be taught to take a pro-active approach to identify and solve problems before they get out of hand. The staff then realize that the EMS is a powerful preventative maintenance tool that can be used to make their work more effective and efficient. Case histories are presented.« less
Optimal recombination in genetic algorithms for flowshop scheduling problems
NASA Astrophysics Data System (ADS)
Kovalenko, Julia
2016-10-01
The optimal recombination problem consists in finding the best possible offspring as a result of a recombination operator in a genetic algorithm, given two parent solutions. We prove NP-hardness of the optimal recombination for various variants of the flowshop scheduling problem with makespan criterion and criterion of maximum lateness. An algorithm for solving the optimal recombination problem for permutation flowshop problems is built, using enumeration of prefect matchings in a special bipartite graph. The algorithm is adopted for the classical flowshop scheduling problem and for the no-wait flowshop problem. It is shown that the optimal recombination problem for the permutation flowshop scheduling problem is solvable in polynomial time for almost all pairs of parent solutions as the number of jobs tends to infinity.
The 1988 Inland Waterway Review
1988-11-01
Maintenance Costs ............. 91 Table 4.3 Major Rehabilitation Projects: ............................... 92 Table 4.4 Scheduled Constructed Projects in the...Maintenance Costs .......................... 100 Figure 4.7 Operations and Maintenance Costs Per Ton Mile in 1986 For Inland Waterways Suspect to Fuel Tax...application of study and construction cost -sharing. It also increased waterway fuel taxes and created the Inland Waterways Users Board. In effect, the Act
2015-09-17
turbines , SHM tools, maintenance scheduling, and performance of the SHM system determine the added value of the system of systems (A. Van Horenbeek...J. R., & Pintelon, L. (2013). Quantifying the added value of an imperfectly performing condition monitoring system— Application to a wind turbine ...INTEGRATED SYSTEMS HEALTH MANAGEMENT AS AN ENABLER FOR CONDITION BASED MAINTENANCE AND AUTONOMIC
41 CFR 102-34.285 - Where can we obtain help in setting up a maintenance program?
Code of Federal Regulations, 2010 CFR
2010-07-01
... PROPERTY 34-MOTOR VEHICLE MANAGEMENT Scheduled Maintenance of Motor Vehicles § 102-34.285 Where can we... 41 Public Contracts and Property Management 3 2010-07-01 2010-07-01 false Where can we obtain help in setting up a maintenance program? 102-34.285 Section 102-34.285 Public Contracts and Property...
An Optimization Model for Scheduling Problems with Two-Dimensional Spatial Resource Constraint
NASA Technical Reports Server (NTRS)
Garcia, Christopher; Rabadi, Ghaith
2010-01-01
Traditional scheduling problems involve determining temporal assignments for a set of jobs in order to optimize some objective. Some scheduling problems also require the use of limited resources, which adds another dimension of complexity. In this paper we introduce a spatial resource-constrained scheduling problem that can arise in assembly, warehousing, cross-docking, inventory management, and other areas of logistics and supply chain management. This scheduling problem involves a twodimensional rectangular area as a limited resource. Each job, in addition to having temporal requirements, has a width and a height and utilizes a certain amount of space inside the area. We propose an optimization model for scheduling the jobs while respecting all temporal and spatial constraints.
SUMO: operation and maintenance management web tool for astronomical observatories
NASA Astrophysics Data System (ADS)
Mujica-Alvarez, Emma; Pérez-Calpena, Ana; García-Vargas, María. Luisa
2014-08-01
SUMO is an Operation and Maintenance Management web tool, which allows managing the operation and maintenance activities and resources required for the exploitation of a complex facility. SUMO main capabilities are: information repository, assets and stock control, tasks scheduler, executed tasks archive, configuration and anomalies control and notification and users management. The information needed to operate and maintain the system must be initially stored at the tool database. SUMO shall automatically schedule the periodical tasks and facilitates the searching and programming of the non-periodical tasks. Tasks planning can be visualized in different formats and dynamically edited to be adjusted to the available resources, anomalies, dates and other constrains that can arise during daily operation. SUMO shall provide warnings to the users notifying potential conflicts related to the required personal availability or the spare stock for the scheduled tasks. To conclude, SUMO has been designed as a tool to help during the operation management of a scientific facility, and in particular an astronomical observatory. This is done by controlling all operating parameters: personal, assets, spare and supply stocks, tasks and time constrains.
Performance comparison of some evolutionary algorithms on job shop scheduling problems
NASA Astrophysics Data System (ADS)
Mishra, S. K.; Rao, C. S. P.
2016-09-01
Job Shop Scheduling as a state space search problem belonging to NP-hard category due to its complexity and combinational explosion of states. Several naturally inspire evolutionary methods have been developed to solve Job Shop Scheduling Problems. In this paper the evolutionary methods namely Particles Swarm Optimization, Artificial Intelligence, Invasive Weed Optimization, Bacterial Foraging Optimization, Music Based Harmony Search Algorithms are applied and find tuned to model and solve Job Shop Scheduling Problems. To compare about 250 Bench Mark instances have been used to evaluate the performance of these algorithms. The capabilities of each these algorithms in solving Job Shop Scheduling Problems are outlined.
Design of an Aircrew Scheduling Decision Aid for the 6916th Electronic Security Squadron.
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
PanDA Pilot Submission using Condor-G: Experience and Improvements
DOE Office of Scientific and Technical Information (OSTI.GOV)
Zhao X.; Hover John; Wlodek Tomasz
2011-01-01
PanDA (Production and Distributed Analysis) is the workload management system of the ATLAS experiment, used to run managed production and user analysis jobs on the grid. As a late-binding, pilot-based system, the maintenance of a smooth and steady stream of pilot jobs to all grid sites is critical for PanDA operation. The ATLAS Computing Facility (ACF) at BNL, as the ATLAS Tier1 center in the US, operates the pilot submission systems for the US. This is done using the PanDA 'AutoPilot' scheduler component which submits pilot jobs via Condor-G, a grid job scheduling system developed at the University of Wisconsin-Madison.more » In this paper, we discuss the operation and performance of the Condor-G pilot submission at BNL, with emphasis on the challenges and issues encountered in the real grid production environment. With the close collaboration of Condor and PanDA teams, the scalability and stability of the overall system has been greatly improved over the last year. We review improvements made to Condor-G resulting from this collaboration, including isolation of site-based issues by running a separate Gridmanager for each remote site, introduction of the 'Nonessential' job attribute to allow Condor to optimize its behavior for the specific character of pilot jobs, better understanding and handling of the Gridmonitor process, as well as better scheduling in the PanDA pilot scheduler component. We will also cover the monitoring of the health of the system.« less
2009-01-01
activities within the patrol area. Maintenance of the Minuteman III weapon system requires maintenance and security teams travel to one or more of 150...launch facilities, all of which are geograph- ically isolated from major population centers. Travel time from F. E. Warren AFB, the main support base...the F. E. Warren AFB work center to make travel preparations, and ends after all maintenance actions are completed, or once the team arrives at one
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.
Maintenance of the Hanford cone penetrometer platform during fiscal year 1999
DOE Office of Scientific and Technical Information (OSTI.GOV)
IWATATE, D.F.
This SOW describes services requested of Applied Research and Associates, Inc. (ARA), as a commercial provider of cone penetrometer equipment and services, to provide routine inspection and minimum preventive maintenance on the Hanford CP Platform (CPP) during Fiscal Year 1999. This SOW specifically pertains to the maintenance of the CPP and associated support equipment and is limited in scope to routine preventive maintenance and identification of any deficiencies. ARA is the original manufacturer of the CPP and will conduct this work following the vendor-prepared maintenance schedule.
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.
Sensibility study in a flexible job shop scheduling problem
NASA Astrophysics Data System (ADS)
Curralo, Ana; Pereira, Ana I.; Barbosa, José; Leitão, Paulo
2013-10-01
This paper proposes the impact assessment of the jobs order in the optimal time of operations in a Flexible Job Shop Scheduling Problem. In this work a real assembly cell was studied: the AIP-PRIMECA cell at the Université de Valenciennes et du Hainaut-Cambrésis, in France, which is considered as a Flexible Job Shop problem. The problem consists in finding the machines operations schedule, taking into account the precedence constraints. The main objective is to minimize the batch makespan, i.e. the finish time of the last operation completed in the schedule. Shortly, the present study consists in evaluating if the jobs order affects the optimal time of the operations schedule. The genetic algorithm was used to solve the optimization problem. As a conclusion, it's assessed that the jobs order influence the optimal time.
NASA Astrophysics Data System (ADS)
Silber, Armin; Gonzalez, Christian; Pino, Francisco; Escarate, Patricio; Gairing, Stefan
2014-08-01
With expanding sizes and increasing complexity of large astronomical observatories on remote observing sites, the call for an efficient and recourses saving maintenance concept becomes louder. The increasing number of subsystems on telescopes and instruments forces large observatories, like in industries, to rethink conventional maintenance strategies for reaching this demanding goal. The implementation of full-, or semi-automatic processes for standard service activities can help to keep the number of operating staff on an efficient level and to reduce significantly the consumption of valuable consumables or equipment. In this contribution we will demonstrate on the example of the 80 Cryogenic subsystems of the ALMA Front End instrument, how an implemented automatic service process increases the availability of spare parts and Line Replaceable Units. Furthermore how valuable staff recourses can be freed from continuous repetitive maintenance activities, to allow focusing more on system diagnostic tasks, troubleshooting and the interchanging of line replaceable units. The required service activities are decoupled from the day-to-day work, eliminating dependencies on workload peaks or logistic constrains. The automatic refurbishing processes running in parallel to the operational tasks with constant quality and without compromising the performance of the serviced system components. Consequentially that results in an efficiency increase, less down time and keeps the observing schedule on track. Automatic service processes in combination with proactive maintenance concepts are providing the necessary flexibility for the complex operational work structures of large observatories. The gained planning flexibility is allowing an optimization of operational procedures and sequences by considering the required cost efficiency.
HURON (HUman and Robotic Optimization Network) Multi-Agent Temporal Activity Planner/Scheduler
NASA Technical Reports Server (NTRS)
Hua, Hook; Mrozinski, Joseph J.; Elfes, Alberto; Adumitroaie, Virgil; Shelton, Kacie E.; Smith, Jeffrey H.; Lincoln, William P.; Weisbin, Charles R.
2012-01-01
HURON solves the problem of how to optimize a plan and schedule for assigning multiple agents to a temporal sequence of actions (e.g., science tasks). Developed as a generic planning and scheduling tool, HURON has been used to optimize space mission surface operations. The tool has also been used to analyze lunar architectures for a variety of surface operational scenarios in order to maximize return on investment and productivity. These scenarios include numerous science activities performed by a diverse set of agents: humans, teleoperated rovers, and autonomous rovers. Once given a set of agents, activities, resources, resource constraints, temporal constraints, and de pendencies, HURON computes an optimal schedule that meets a specified goal (e.g., maximum productivity or minimum time), subject to the constraints. HURON performs planning and scheduling optimization as a graph search in state-space with forward progression. Each node in the graph contains a state instance. Starting with the initial node, a graph is automatically constructed with new successive nodes of each new state to explore. The optimization uses a set of pre-conditions and post-conditions to create the children states. The Python language was adopted to not only enable more agile development, but to also allow the domain experts to easily define their optimization models. A graphical user interface was also developed to facilitate real-time search information feedback and interaction by the operator in the search optimization process. The HURON package has many potential uses in the fields of Operations Research and Management Science where this technology applies to many commercial domains requiring optimization to reduce costs. For example, optimizing a fleet of transportation truck routes, aircraft flight scheduling, and other route-planning scenarios involving multiple agent task optimization would all benefit by using HURON.
Framework for computationally efficient optimal irrigation scheduling using ant colony optimization
USDA-ARS?s Scientific Manuscript database
A general optimization framework is introduced with the overall goal of reducing search space size and increasing the computational efficiency of evolutionary algorithm application for optimal irrigation scheduling. The framework achieves this goal by representing the problem in the form of a decisi...
May 23, 2012, Notice of Proposed Rulemaking with revisions related to emissions controls on diesel-powered emergency vehicles and revisions related to scheduled maintenance intervals for diesel engines and vehicles using Selective Catalytic Reduction (SCR)
41 CFR 101-39.303 - Maintenance.
Code of Federal Regulations, 2011 CFR
2011-07-01
... MANAGEMENT SYSTEMS 39.3-Use and Care of GSA Interagency Fleet Management System Vehicles § 101-39.303...) vehicles, safety and preventive maintenance inspections will be performed at regularly scheduled intervals as directed by GSA. Users of GSA IFMS vehicles shall comply with the safety and preventive...
Federal Register 2010, 2011, 2012, 2013, 2014
2011-01-05
... to these aircraft if Bombardier Service Bulletin (SB) 601-0590 [Scheduled Maintenance Instructions... information: Challenger 601 Time Limits/Maintenance Checks, PSP 601-5, Revision 38, dated June 19, 2009. Challenger 601 Time Limits/Maintenance Checks, PSP 601A-5, Revision 34, dated June 19, 2009. Challenger 604...
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.
DTS: Building custom, intelligent schedulers
NASA Technical Reports Server (NTRS)
Hansson, Othar; Mayer, Andrew
1994-01-01
DTS is a decision-theoretic scheduler, built on top of a flexible toolkit -- this paper focuses on how the toolkit might be reused in future NASA mission schedulers. The toolkit includes a user-customizable scheduling interface, and a 'Just-For-You' optimization engine. The customizable interface is built on two metaphors: objects and dynamic graphs. Objects help to structure problem specifications and related data, while dynamic graphs simplify the specification of graphical schedule editors (such as Gantt charts). The interface can be used with any 'back-end' scheduler, through dynamically-loaded code, interprocess communication, or a shared database. The 'Just-For-You' optimization engine includes user-specific utility functions, automatically compiled heuristic evaluations, and a postprocessing facility for enforcing scheduling policies. The optimization engine is based on BPS, the Bayesian Problem-Solver (1,2), which introduced a similar approach to solving single-agent and adversarial graph search problems.
Car painting process scheduling with harmony search algorithm
NASA Astrophysics Data System (ADS)
Syahputra, M. F.; Maiyasya, A.; Purnamawati, S.; Abdullah, D.; Albra, W.; Heikal, M.; Abdurrahman, A.; Khaddafi, M.
2018-02-01
Automotive painting program in the process of painting the car body by using robot power, making efficiency in the production system. Production system will be more efficient if pay attention to scheduling of car order which will be done by considering painting body shape of car. Flow shop scheduling is a scheduling model in which the job-job to be processed entirely flows in the same product direction / path. Scheduling problems often arise if there are n jobs to be processed on the machine, which must be specified which must be done first and how to allocate jobs on the machine to obtain a scheduled production process. Harmony Search Algorithm is a metaheuristic optimization algorithm based on music. The algorithm is inspired by observations that lead to music in search of perfect harmony. This musical harmony is in line to find optimal in the optimization process. Based on the tests that have been done, obtained the optimal car sequence with minimum makespan value.
Pitch Guidance Optimization for the Orion Abort Flight Tests
NASA Technical Reports Server (NTRS)
Stillwater, Ryan Allanque
2010-01-01
The National Aeronautics and Space Administration created the Constellation program to develop the next generation of manned space vehicles and launch vehicles. The Orion abort system is initiated in the event of an unsafe condition during launch. The system has a controller gains schedule that can be tuned to reduce the attitude errors between the simulated Orion abort trajectories and the guidance trajectory. A program was created that uses the method of steepest descent to tune the pitch gains schedule by an automated procedure. The gains schedule optimization was applied to three potential abort scenarios; each scenario tested using the optimized gains schedule resulted in reduced attitude errors when compared to the Orion production gains schedule.
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).
Fractional Programming for Communication Systems—Part II: Uplink Scheduling via Matching
NASA Astrophysics Data System (ADS)
Shen, Kaiming; Yu, Wei
2018-05-01
This two-part paper develops novel methodologies for using fractional programming (FP) techniques to design and optimize communication systems. Part I of this paper proposes a new quadratic transform for FP and treats its application for continuous optimization problems. In this Part II of the paper, we study discrete problems, such as those involving user scheduling, which are considerably more difficult to solve. Unlike the continuous problems, discrete or mixed discrete-continuous problems normally cannot be recast as convex problems. In contrast to the common heuristic of relaxing the discrete variables, this work reformulates the original problem in an FP form amenable to distributed combinatorial optimization. The paper illustrates this methodology by tackling the important and challenging problem of uplink coordinated multi-cell user scheduling in wireless cellular systems. Uplink scheduling is more challenging than downlink scheduling, because uplink user scheduling decisions significantly affect the interference pattern in nearby cells. Further, the discrete scheduling variable needs to be optimized jointly with continuous variables such as transmit power levels and beamformers. The main idea of the proposed FP approach is to decouple the interaction among the interfering links, thereby permitting a distributed and joint optimization of the discrete and continuous variables with provable convergence. The paper shows that the well-known weighted minimum mean-square-error (WMMSE) algorithm can also be derived from a particular use of FP; but our proposed FP-based method significantly outperforms WMMSE when discrete user scheduling variables are involved, both in term of run-time efficiency and optimizing results.
NASA Astrophysics Data System (ADS)
Hoell, Simon; Omenzetter, Piotr
2017-04-01
The increasing demand for carbon neutral energy in a challenging economic environment is a driving factor for erecting ever larger wind turbines in harsh environments using novel wind turbine blade (WTBs) designs characterized by high flexibilities and lower buckling capacities. To counteract resulting increasing of operation and maintenance costs, efficient structural health monitoring systems can be employed to prevent dramatic failures and to schedule maintenance actions according to the true structural state. This paper presents a novel methodology for classifying structural damages using vibrational responses from a single sensor. The method is based on statistical classification using Bayes' theorem and an advanced statistic, which allows controlling the performance by varying the number of samples which represent the current state. This is done for multivariate damage sensitive features defined as partial autocorrelation coefficients (PACCs) estimated from vibrational responses and principal component analysis scores from PACCs. Additionally, optimal DSFs are composed not only for damage classification but also for damage detection based on binary statistical hypothesis testing, where features selections are found with a fast forward procedure. The method is applied to laboratory experiments with a small scale WTB with wind-like excitation and non-destructive damage scenarios. The obtained results demonstrate the advantages of the proposed procedure and are promising for future applications of vibration-based structural health monitoring in WTBs.
Optimal Scheduling of Time-Shiftable Electric Loads in Expeditionary Power Grids
2015-09-01
NAVAL POSTGRADUATE SCHOOL MONTEREY, CALIFORNIA THESIS OPTIMAL SCHEDULING OF TIME-SHIFTABLE ELECTRIC LOADS IN EXPEDITIONARY POWER GRIDS by John G...to 09-25-2015 4. TITLE AND SUBTITLE OPTIMAL SCHEDULING OF TIME-SHIFTABLE ELECTRIC LOADS IN EXPEDI- TIONARY POWER GRIDS 5. FUNDING NUMBERS 6. AUTHOR(S...eliminate unmanaged peak demand, reduce generator peak-to-average power ratios, and facilitate a persistent shift to higher fuel efficiency. Using
Hwang, Juwon; Shah, Dhavan V
2018-06-05
Parental concerns over the safety or necessity of childhood vaccination have increased over the past decades. At the same time, there has been a proliferation of vaccine-related information available through a range of health information sources. This study investigates the associations between evaluations of health information sources, parental perceptions of childhood vaccination benefits, and the maintenance of vaccination schedules for their children. Specifically, this study aims to (a) incorporate social media into the battery of health information sources and (b) differentiate households with a childhood autism diagnosis and those without, given unsubstantiated but persistent concerns about vaccine safety and autism. Analyzing a sample of U.S. households, a total of 4,174 parents who have at least one child under the age of 18 were analyzed, including 138 of parents of households with a childhood autism diagnosis. Results show that the more the parents value interpersonal communication and magazines as sources of health information, the more they perceive vaccination benefits, and the more the value they put on television, the better they keep vaccination schedules up-to-date for their children. On the other hand, social media are negatively associated with their perceptions of vaccination benefits. Although parents of children diagnosed with autism are less likely to perceive vaccination benefits, no interaction effects with evaluations of health information sources are found on parental perceptions of vaccination benefits or maintenance of schedules.
Evaluations of Some Scheduling Algorithms for Hard Real-Time Systems
1990-06-01
construct because the mechanism is a dispatching procedure. Since all nonpreemptive schedules are contained in the set of all preemptive schedules, the...optimal value of Tmax in the preemptive case is at least a lower bound on the optimal Tmax for the nonpreemptive schedules. This principle is the basis...23 b. Nonpreemptable Version .............................................. 24 4. The Minimize Maximum Tardiness with Earliest Start
DOT National Transportation Integrated Search
2015-12-01
This project investigated INDOT equipment records and equipment industry standards to produce standard equipment specifications : and a predictive maintenance schedule for the more than 1100 single and tandem axle trucks in use at INDOT. The research...
78 FR 46615 - Records Schedules; Availability and Request for Comments
Federal Register 2010, 2011, 2012, 2013, 2014
2013-08-01
... process is available on request. Schedules Pending 1. Department of Defense, Defense Contract Management... officials. 2. Department of Defense, Defense Contract Management Agency (N1- 558-10-6, 6 items, 6 temporary... related to the production and maintenance of such records. 3. Department of Defense, Defense Logistics...
Concurrent Schedules of Reinforcement as "Challenges" to Maintenance
ERIC Educational Resources Information Center
Peterson, Stephanie M.; Frieder, Jessica E.; Quigley, Shawn P.; Kestner, Kathryn M.; Goyal, Manish; Smith, Shilo L.; Dayton, Elizabeth; Brower-Breitwieser, Carrie
2017-01-01
One measure of success for interventions treating problem behavior is the effects achieved in the face of a challenge (e.g., changes in reinforcement schedules, lapses in treatment integrity); one hopes to demonstrate persistence of appropriate alternatives and the absence of resurgence of target behaviors. The present study successfully treated…
78 FR 66266 - Drawbridge Operation Regulation; Atlantic Intracoastal Waterway (AIWW), Chesapeake, VA
Federal Register 2010, 2011, 2012, 2013, 2014
2013-11-05
... deviation from the operating schedule that governs the I64 Bridge across the Atlantic Intracoastal Waterway... deviation, call or email Mrs. Kashanda Booker, Bridge Administration Branch Fifth District, Coast Guard... maintenance of the moveable spans on the structure. The current operating schedule for the drawbridge is set...
Development of Watch Schedule Using Rules Approach
NASA Astrophysics Data System (ADS)
Jurkevicius, Darius; Vasilecas, Olegas
The software for schedule creation and optimization solves a difficult, important and practical problem. The proposed solution is an online employee portal where administrator users can create and manage watch schedules and employee requests. Each employee can login with his/her own account and see his/her assignments, manage requests, etc. Employees set as administrators can perform the employee scheduling online, manage requests, etc. This scheduling software allows users not only to see the initial and optimized watch schedule in a simple and understandable form, but also to create special rules and criteria and input their business. The system using rules automatically will generate watch schedule.
On scheduling task systems with variable service times
NASA Astrophysics Data System (ADS)
Maset, Richard G.; Banawan, Sayed A.
1993-08-01
Several strategies have been proposed for developing optimal and near-optimal schedules for task systems (jobs consisting of multiple tasks that can be executed in parallel). Most such strategies, however, implicitly assume deterministic task service times. We show that these strategies are much less effective when service times are highly variable. We then evaluate two strategies—one adaptive, one static—that have been proposed for retaining high performance despite such variability. Both strategies are extensions of critical path scheduling, which has been found to be efficient at producing near-optimal schedules. We found the adaptive approach to be quite effective.
Xing, KeYi; Han, LiBin; Zhou, MengChu; Wang, Feng
2012-06-01
Deadlock-free control and scheduling are vital for optimizing the performance of automated manufacturing systems (AMSs) with shared resources and route flexibility. Based on the Petri net models of AMSs, this paper embeds the optimal deadlock avoidance policy into the genetic algorithm and develops a novel deadlock-free genetic scheduling algorithm for AMSs. A possible solution of the scheduling problem is coded as a chromosome representation that is a permutation with repetition of parts. By using the one-step look-ahead method in the optimal deadlock control policy, the feasibility of a chromosome is checked, and infeasible chromosomes are amended into feasible ones, which can be easily decoded into a feasible deadlock-free schedule. The chromosome representation and polynomial complexity of checking and amending procedures together support the cooperative aspect of genetic search for scheduling problems strongly.
Hybrid glowworm swarm optimization for task scheduling in the cloud environment
NASA Astrophysics Data System (ADS)
Zhou, Jing; Dong, Shoubin
2018-06-01
In recent years many heuristic algorithms have been proposed to solve task scheduling problems in the cloud environment owing to their optimization capability. This article proposes a hybrid glowworm swarm optimization (HGSO) based on glowworm swarm optimization (GSO), which uses a technique of evolutionary computation, a strategy of quantum behaviour based on the principle of neighbourhood, offspring production and random walk, to achieve more efficient scheduling with reasonable scheduling costs. The proposed HGSO reduces the redundant computation and the dependence on the initialization of GSO, accelerates the convergence and more easily escapes from local optima. The conducted experiments and statistical analysis showed that in most cases the proposed HGSO algorithm outperformed previous heuristic algorithms to deal with independent tasks.
NASA Technical Reports Server (NTRS)
Butcher, L.; Jonas, T.; Wood, W.
1982-01-01
The heavy schedule of tracking activities at the Echo Deep Space Station (DSS 12) prevents some time-consuming maintenance tasks from being performed. Careful coordination prior to and during a mandatory task (antenna panel replacement) made it possible to do a large number of unrelated tasks that ordinarily would have to be deferred. The maintenance and operations tasks accomplished during the downtime are described.
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.
NASA Astrophysics Data System (ADS)
Zhao, Wei-hu; Zhao, Jing; Zhao, Shang-hong; Li, Yong-jun; Wang, Xiang; Dong, Yi; Dong, Chen
2013-08-01
Optical satellite communication with the advantages of broadband, large capacity and low power consuming broke the bottleneck of the traditional microwave satellite communication. The formation of the Space-based Information System with the technology of high performance optical inter-satellite communication and the realization of global seamless coverage and mobile terminal accessing are the necessary trend of the development of optical satellite communication. Considering the resources, missions and restraints of Data Relay Satellite Optical Communication System, a model of optical communication resources scheduling is established and a scheduling algorithm based on artificial intelligent optimization is put forwarded. According to the multi-relay-satellite, multi-user-satellite, multi-optical-antenna and multi-mission with several priority weights, the resources are scheduled reasonable by the operation: "Ascertain Current Mission Scheduling Time" and "Refresh Latter Mission Time-Window". The priority weight is considered as the parameter of the fitness function and the scheduling project is optimized by the Genetic Algorithm. The simulation scenarios including 3 relay satellites with 6 optical antennas, 12 user satellites and 30 missions, the simulation result reveals that the algorithm obtain satisfactory results in both efficiency and performance and resources scheduling model and the optimization algorithm are suitable in multi-relay-satellite, multi-user-satellite, and multi-optical-antenna recourses scheduling problem.
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.
CQPSO scheduling algorithm for heterogeneous multi-core DAG task model
NASA Astrophysics Data System (ADS)
Zhai, Wenzheng; Hu, Yue-Li; Ran, Feng
2017-07-01
Efficient task scheduling is critical to achieve high performance in a heterogeneous multi-core computing environment. The paper focuses on the heterogeneous multi-core directed acyclic graph (DAG) task model and proposes a novel task scheduling method based on an improved chaotic quantum-behaved particle swarm optimization (CQPSO) algorithm. A task priority scheduling list was built. A processor with minimum cumulative earliest finish time (EFT) was acted as the object of the first task assignment. The task precedence relationships were satisfied and the total execution time of all tasks was minimized. The experimental results show that the proposed algorithm has the advantage of optimization abilities, simple and feasible, fast convergence, and can be applied to the task scheduling optimization for other heterogeneous and distributed environment.
Zhu, Xiaoning
2014-01-01
Rail mounted gantry crane (RMGC) scheduling is important in reducing makespan of handling operation and improving container handling efficiency. In this paper, we present an RMGC scheduling optimization model, whose objective is to determine an optimization handling sequence in order to minimize RMGC idle load time in handling tasks. An ant colony optimization is proposed to obtain near optimal solutions. Computational experiments on a specific railway container terminal are conducted to illustrate the proposed model and solution algorithm. The results show that the proposed method is effective in reducing the idle load time of RMGC. PMID:25538768
DOT National Transportation Integrated Search
2015-12-01
This project investigated INDOT equipment records and equipment industry standards to produce standard equipment specifications : and a predictive maintenance schedule for the more than 1100 single and tandem axle trucks in use at INDOT. The research...
14 CFR Sec. 19-2 - Maintenance of data.
Code of Federal Regulations, 2013 CFR
2013-01-01
... Classifications Sec. 19-2 Maintenance of data. (a) Each air carrier required to file Form 41 Schedule T-100 data... classifications prescribed. Codes are prescribed for each operating element and service class. All traffic... that the enplanement/deplanement information be broken out into separate units called “on-flight market...
14 CFR Sec. 19-2 - Maintenance of data.
Code of Federal Regulations, 2014 CFR
2014-01-01
... Classifications Sec. 19-2 Maintenance of data. (a) Each air carrier required to file Form 41 Schedule T-100 data... classifications prescribed. Codes are prescribed for each operating element and service class. All traffic... that the enplanement/deplanement information be broken out into separate units called “on-flight market...
40 CFR 205.162-3 - Instructions for maintenance, use, and repair.
Code of Federal Regulations, 2013 CFR
2013-07-01
...) NOISE ABATEMENT PROGRAMS TRANSPORTATION EQUIPMENT NOISE EMISSION CONTROLS Motorcycles § 205.162-3... this purpose in mind. The instructions shall be clear and, to the extent practicable, written in non... contain a schedule for the performance of all required noise emission control maintenance. Space must be...
40 CFR 205.162-3 - Instructions for maintenance, use, and repair.
Code of Federal Regulations, 2014 CFR
2014-07-01
...) NOISE ABATEMENT PROGRAMS TRANSPORTATION EQUIPMENT NOISE EMISSION CONTROLS Motorcycles § 205.162-3... this purpose in mind. The instructions shall be clear and, to the extent practicable, written in non... contain a schedule for the performance of all required noise emission control maintenance. Space must be...
40 CFR 205.162-3 - Instructions for maintenance, use, and repair.
Code of Federal Regulations, 2012 CFR
2012-07-01
...) NOISE ABATEMENT PROGRAMS TRANSPORTATION EQUIPMENT NOISE EMISSION CONTROLS Motorcycles § 205.162-3... this purpose in mind. The instructions shall be clear and, to the extent practicable, written in non... contain a schedule for the performance of all required noise emission control maintenance. Space must be...
40 CFR 205.162-3 - Instructions for maintenance, use, and repair.
Code of Federal Regulations, 2011 CFR
2011-07-01
...) NOISE ABATEMENT PROGRAMS TRANSPORTATION EQUIPMENT NOISE EMISSION CONTROLS Motorcycles § 205.162-3... this purpose in mind. The instructions shall be clear and, to the extent practicable, written in non... contain a schedule for the performance of all required noise emission control maintenance. Space must be...
NASA Astrophysics Data System (ADS)
Tang, Dunbing; Dai, Min
2015-09-01
The traditional production planning and scheduling problems consider performance indicators like time, cost and quality as optimization objectives in manufacturing processes. However, environmentally-friendly factors like energy consumption of production have not been completely taken into consideration. Against this background, this paper addresses an approach to modify a given schedule generated by a production planning and scheduling system in a job shop floor, where machine tools can work at different cutting speeds. It can adjust the cutting speeds of the operations while keeping the original assignment and processing sequence of operations of each job fixed in order to obtain energy savings. First, the proposed approach, based on a mixed integer programming mathematical model, changes the total idle time of the given schedule to minimize energy consumption in the job shop floor while accepting the optimal solution of the scheduling objective, makespan. Then, a genetic-simulated annealing algorithm is used to explore the optimal solution due to the fact that the problem is strongly NP-hard. Finally, the effectiveness of the approach is performed smalland large-size instances, respectively. The experimental results show that the approach can save 5%-10% of the average energy consumption while accepting the optimal solution of the makespan in small-size instances. In addition, the average maximum energy saving ratio can reach to 13%. And it can save approximately 1%-4% of the average energy consumption and approximately 2.4% of the average maximum energy while accepting the near-optimal solution of the makespan in large-size instances. The proposed research provides an interesting point to explore an energy-aware schedule optimization for a traditional production planning and scheduling problem.
Xiang, Wei; Li, Chong
2015-01-01
Operating Room (OR) is the core sector in hospital expenditure, the operation management of which involves a complete three-stage surgery flow, multiple resources, prioritization of the various surgeries, and several real-life OR constraints. As such reasonable surgery scheduling is crucial to OR management. To optimize OR management and reduce operation cost, a short-term surgery scheduling problem is proposed and defined based on the survey of the OR operation in a typical hospital in China. The comprehensive operation cost is clearly defined considering both under-utilization and overutilization. A nested Ant Colony Optimization (nested-ACO) incorporated with several real-life OR constraints is proposed to solve such a combinatorial optimization problem. The 10-day manual surgery schedules from a hospital in China are compared with the optimized schedules solved by the nested-ACO. Comparison results show the advantage using the nested-ACO in several measurements: OR-related time, nurse-related time, variation in resources' working time, and the end time. The nested-ACO considering real-life operation constraints such as the difference between first and following case, surgeries priority, and fixed nurses in pre/post-operative stage is proposed to solve the surgery scheduling optimization problem. The results clearly show the benefit of using the nested-ACO in enhancing the OR management efficiency and minimizing the comprehensive overall operation cost.
Instructional versus schedule control of humans' choices in situations of diminishing returns
Hackenberg, Timothy D.; Joker, Veronica R.
1994-01-01
Four adult humans chose repeatedly between a fixed-time schedule (of points later exchangeable for money) and a progressive-time schedule that began at 0 s and increased by a fixed number of seconds with each point delivered by that schedule. Each point delivered by the fixed-time schedule reset the requirements of the progressive-time schedule to its minimum value. Subjects were provided with instructions that specified a particular sequence of choices. Under the initial conditions, the instructions accurately specified the optimal choice sequence. Thus, control by instructions and optimal control by the programmed contingencies both supported the same performance. To distinguish the effects of instructions from schedule sensitivity, the correspondence between the instructed and optimal choice patterns was gradually altered across conditions by varying the step size of the progressive-time schedule while maintaining the same instructions. Step size was manipulated, typically in 1-s units, first in an ascending and then in a descending sequence of conditions. Instructions quickly established control in all 4 subjects but, by narrowing the range of choice patterns, they reduced subsequent sensitivity to schedule changes. Instructional control was maintained across the ascending sequence of progressive-time values for each subject, but eventually diminished, giving way to more schedule-appropriate patterns. The transition from instruction-appropriate to schedule-appropriate behavior was characterized by an increase in the variability of choice patterns and local increases in point density. On the descending sequence of progressive-time values, behavior appeared to be schedule sensitive, sometimes even optimally sensitive, but it did not always change systematically with the contingencies, suggesting the involvement of other factors. PMID:16812747
DOE Office of Scientific and Technical Information (OSTI.GOV)
Liang, Faming; Cheng, Yichen; Lin, Guang
2014-06-13
Simulated annealing has been widely used in the solution of optimization problems. As known by many researchers, the global optima cannot be guaranteed to be located by simulated annealing unless a logarithmic cooling schedule is used. However, the logarithmic cooling schedule is so slow that no one can afford to have such a long CPU time. This paper proposes a new stochastic optimization algorithm, the so-called simulated stochastic approximation annealing algorithm, which is a combination of simulated annealing and the stochastic approximation Monte Carlo algorithm. Under the framework of stochastic approximation Markov chain Monte Carlo, it is shown that themore » new algorithm can work with a cooling schedule in which the temperature can decrease much faster than in the logarithmic cooling schedule, e.g., a square-root cooling schedule, while guaranteeing the global optima to be reached when the temperature tends to zero. The new algorithm has been tested on a few benchmark optimization problems, including feed-forward neural network training and protein-folding. The numerical results indicate that the new algorithm can significantly outperform simulated annealing and other competitors.« less
Multi-Objective Approach for Energy-Aware Workflow Scheduling in Cloud Computing Environments
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
AI techniques for a space application scheduling problem
NASA Technical Reports Server (NTRS)
Thalman, N.; Sparn, T.; Jaffres, L.; Gablehouse, D.; Judd, D.; Russell, C.
1991-01-01
Scheduling is a very complex optimization problem which can be categorized as an NP-complete problem. NP-complete problems are quite diverse, as are the algorithms used in searching for an optimal solution. In most cases, the best solutions that can be derived for these combinatorial explosive problems are near-optimal solutions. Due to the complexity of the scheduling problem, artificial intelligence (AI) can aid in solving these types of problems. Some of the factors are examined which make space application scheduling problems difficult and presents a fairly new AI-based technique called tabu search as applied to a real scheduling application. the specific problem is concerned with scheduling application. The specific problem is concerned with scheduling solar and stellar observations for the SOLar-STellar Irradiance Comparison Experiment (SOLSTICE) instrument in a constrained environment which produces minimum impact on the other instruments and maximizes target observation times. The SOLSTICE instrument will gly on-board the Upper Atmosphere Research Satellite (UARS) in 1991, and a similar instrument will fly on the earth observing system (Eos).
Multi-objective approach for energy-aware workflow scheduling in cloud computing environments.
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.
Discrete Bat Algorithm for Optimal Problem of Permutation Flow Shop Scheduling
Luo, Qifang; Zhou, Yongquan; Xie, Jian; Ma, Mingzhi; Li, Liangliang
2014-01-01
A discrete bat algorithm (DBA) is proposed for optimal permutation flow shop scheduling problem (PFSP). Firstly, the discrete bat algorithm is constructed based on the idea of basic bat algorithm, which divide whole scheduling problem into many subscheduling problems and then NEH heuristic be introduced to solve subscheduling problem. Secondly, some subsequences are operated with certain probability in the pulse emission and loudness phases. An intensive virtual population neighborhood search is integrated into the discrete bat algorithm to further improve the performance. Finally, the experimental results show the suitability and efficiency of the present discrete bat algorithm for optimal permutation flow shop scheduling problem. PMID:25243220
Discrete bat algorithm for optimal problem of permutation flow shop scheduling.
Luo, Qifang; Zhou, Yongquan; Xie, Jian; Ma, Mingzhi; Li, Liangliang
2014-01-01
A discrete bat algorithm (DBA) is proposed for optimal permutation flow shop scheduling problem (PFSP). Firstly, the discrete bat algorithm is constructed based on the idea of basic bat algorithm, which divide whole scheduling problem into many subscheduling problems and then NEH heuristic be introduced to solve subscheduling problem. Secondly, some subsequences are operated with certain probability in the pulse emission and loudness phases. An intensive virtual population neighborhood search is integrated into the discrete bat algorithm to further improve the performance. Finally, the experimental results show the suitability and efficiency of the present discrete bat algorithm for optimal permutation flow shop scheduling problem.
7 CFR 1580.502 - Maintenance of records, audits and compliance.
Code of Federal Regulations, 2010 CFR
2010-01-01
... Internal Revenue Service Form 990-C, Farmers' Cooperative Association Income Tax Return; Form 1040, U.S. Individual Income Tax Return; Schedule C (Form 1040), Profit or Loss From Business; Schedule F (Form 1040... Income Tax Return; or Form 4835, Farm Rental Income and Expenses. (b) At all times during regular...
49 CFR 214.531 - Schedule of repairs; general.
Code of Federal Regulations, 2010 CFR
2010-10-01
... Hi-Rail Vehicles § 214.531 Schedule of repairs; general. Except as provided in §§ 214.527(c)(5), 214.529, and 214.533, an on-track roadway maintenance machine or hi-rail vehicle that does not meet all... or hi-rail vehicle shall be placed out of on-track service. ...
Improved NSGA model for multi objective operation scheduling and its evaluation
NASA Astrophysics Data System (ADS)
Li, Weining; Wang, Fuyu
2017-09-01
Reasonable operation can increase the income of the hospital and improve the patient’s satisfactory level. In this paper, by using multi object operation scheduling method with improved NSGA algorithm, it shortens the operation time, reduces the operation costand lowers the operation risk, the multi-objective optimization model is established for flexible operation scheduling, through the MATLAB simulation method, the Pareto solution is obtained, the standardization of data processing. The optimal scheduling scheme is selected by using entropy weight -Topsis combination method. The results show that the algorithm is feasible to solve the multi-objective operation scheduling problem, and provide a reference for hospital operation scheduling.
Logistics Management: Cases Studies,
LOGISTICS , * MANAGEMENT PLANNING AND CONTROL), DECISION MAKING, INVENTORY CONTROL, SPARE PARTS, AIR FORCE EQUIPMENT, NAVAL AIRCRAFT, MAINTENANCE, DEPLOYMENT, SCHEDULING, SYSTEMS ENGINEERING, TEXTBOOKS
Understanding London's Water Supply Tradeoffs When Scheduling Interventions Under Deep Uncertainty
NASA Astrophysics Data System (ADS)
Huskova, I.; Matrosov, E. S.; Harou, J. J.; Kasprzyk, J. R.; Reed, P. M.
2015-12-01
Water supply planning in many major world cities faces several challenges associated with but not limited to climate change, population growth and insufficient land availability for infrastructure development. Long-term plans to maintain supply-demand balance and ecosystem services require careful consideration of uncertainties associated with future conditions. The current approach for London's water supply planning utilizes least cost optimization of future intervention schedules with limited uncertainty consideration. Recently, the focus of the long-term plans has shifted from solely least cost performance to robustness and resilience of the system. Identifying robust scheduling of interventions requires optimizing over a statistically representative sample of stochastic inputs which may be computationally difficult to achieve. In this study we optimize schedules using an ensemble of plausible scenarios and assess how manipulating that ensemble influences the different Pareto-approximate intervention schedules. We investigate how a major stress event's location in time as well as the optimization problem formulation influence the Pareto-approximate schedules. A bootstrapping method that respects the non-stationary trend of climate change scenarios and ensures the even distribution of the major stress event in the scenario ensemble is proposed. Different bootstrapped hydrological scenario ensembles are assessed using many-objective scenario optimization of London's future water supply and demand intervention scheduling. However, such a "fixed" scheduling of interventions approach does not aim to embed flexibility or adapt effectively as the future unfolds. Alternatively, making decisions based on the observations of occurred conditions could help planners who prefer adaptive planning. We will show how rules to guide the implementation of interventions based on observations may result in more flexible strategies.
The Basic Organizing/Optimizing Training Scheduler (BOOTS): User's Guide. Technical Report 151.
ERIC Educational Resources Information Center
Church, Richard L.; Keeler, F. Laurence
This report provides the step-by-step instructions required for using the Navy's Basic Organizing/Optimizing Training Scheduler (BOOTS) system. BOOTS is a computerized tool designed to aid in the creation of master training schedules for each Navy recruit training command. The system is defined in terms of three major functions: (1) data file…
Task Scheduling in Desktop Grids: Open Problems
NASA Astrophysics Data System (ADS)
Chernov, Ilya; Nikitina, Natalia; Ivashko, Evgeny
2017-12-01
We survey the areas of Desktop Grid task scheduling that seem to be insufficiently studied so far and are promising for efficiency, reliability, and quality of Desktop Grid computing. These topics include optimal task grouping, "needle in a haystack" paradigm, game-theoretical scheduling, domain-imposed approaches, special optimization of the final stage of the batch computation, and Enterprise Desktop Grids.
Developing optimal nurses work schedule using integer programming
NASA Astrophysics Data System (ADS)
Shahidin, Ainon Mardhiyah; Said, Mohd Syazwan Md; Said, Noor Hizwan Mohamad; Sazali, Noor Izatie Amaliena
2017-08-01
Time management is the art of arranging, organizing and scheduling one's time for the purpose of generating more effective work and productivity. Scheduling is the process of deciding how to commit resources between varieties of possible tasks. Thus, it is crucial for every organization to have a good work schedule for their staffs. The job of Ward nurses at hospitals runs for 24 hours every day. Therefore, nurses will be working using shift scheduling. This study is aimed to solve the nurse scheduling problem at an emergency ward of a private hospital. A 7-day work schedule for 7 consecutive weeks satisfying all the constraints set by the hospital will be developed using Integer Programming. The work schedule for the nurses obtained gives an optimal solution where all the constraints are being satisfied successfully.
117. ARAI Shop and maintenance (ARA627) building roof and floor ...
117. ARA-I Shop and maintenance (ARA-627) building roof and floor plan. Includes room finish and equipment schedule. Norman Engineering Company 961-area/SF-627-A-1. Date: January 1959. Ineel index code no. 068-0627-00-613-102759. - Idaho National Engineering Laboratory, Army Reactors Experimental Area, Scoville, Butte County, ID
ERIC Educational Resources Information Center
California State Dept. of Education, Sacramento.
This handbook provides information that administrators of maintenance and operations in California schools can use in systematically planning and scheduling school facility support services. The first unit, chapter 1, is designed to help members of school district governing boards establish board policies, regulations, and procedures. Topics…
Federal Register 2010, 2011, 2012, 2013, 2014
2010-12-22
... maintenance activities. SGRLPS proposes to transport visitors to the Station during the Sunday work window... two times per year within the proposed work window. Scheduled light maintenance activities would... light. For each emergency repair event, the SGRLPS proposes to conduct a maximum of four flights (two...
40 CFR 53.4 - Applications for reference or equivalent method determinations.
Code of Federal Regulations, 2013 CFR
2013-07-01
...) Required or recommended routine, periodic, and preventative maintenance and maintenance schedules. (J) Any... methods for PM 2.5 and PM 10-2,5 must be described in sufficient detail, based on the elements described... Table A-1 to this subpart) will be met throughout the warranty period and that the applicant accepts...
40 CFR 53.4 - Applications for reference or equivalent method determinations.
Code of Federal Regulations, 2014 CFR
2014-07-01
...) Required or recommended routine, periodic, and preventative maintenance and maintenance schedules. (J) Any... methods for PM 2.5 and PM 10-2.5 must be described in sufficient detail, based on the elements described... Table A-1 to this subpart) will be met throughout the warranty period and that the applicant accepts...
The Ames-Lockheed orbiter processing scheduling system
NASA Technical Reports Server (NTRS)
Zweben, Monte; Gargan, Robert
1991-01-01
A general purpose scheduling system and its application to Space Shuttle Orbiter Processing at the Kennedy Space Center (KSC) are described. Orbiter processing entails all the inspection, testing, repair, and maintenance necessary to prepare the Shuttle for launch and takes place within the Orbiter Processing Facility (OPF) at KSC, the Vehicle Assembly Building (VAB), and on the launch pad. The problems are extremely combinatoric in that there are thousands of tasks, resources, and other temporal considerations that must be coordinated. Researchers are building a scheduling tool that they hope will be an integral part of automating the planning and scheduling process at KSC. The scheduling engine is domain independent and is also being applied to Space Shuttle cargo processing problems as well as wind tunnel scheduling problems.
Optimizing integrated airport surface and terminal airspace operations under uncertainty
NASA Astrophysics Data System (ADS)
Bosson, Christabelle S.
In airports and surrounding terminal airspaces, the integration of surface, arrival and departure scheduling and routing have the potential to improve the operations efficiency. Moreover, because both the airport surface and the terminal airspace are often altered by random perturbations, the consideration of uncertainty in flight schedules is crucial to improve the design of robust flight schedules. Previous research mainly focused on independently solving arrival scheduling problems, departure scheduling problems and surface management scheduling problems and most of the developed models are deterministic. This dissertation presents an alternate method to model the integrated operations by using a machine job-shop scheduling formulation. A multistage stochastic programming approach is chosen to formulate the problem in the presence of uncertainty and candidate solutions are obtained by solving sample average approximation problems with finite sample size. The developed mixed-integer-linear-programming algorithm-based scheduler is capable of computing optimal aircraft schedules and routings that reflect the integration of air and ground operations. The assembled methodology is applied to a Los Angeles case study. To show the benefits of integrated operations over First-Come-First-Served, a preliminary proof-of-concept is conducted for a set of fourteen aircraft evolving under deterministic conditions in a model of the Los Angeles International Airport surface and surrounding terminal areas. Using historical data, a representative 30-minute traffic schedule and aircraft mix scenario is constructed. The results of the Los Angeles application show that the integration of air and ground operations and the use of a time-based separation strategy enable both significant surface and air time savings. The solution computed by the optimization provides a more efficient routing and scheduling than the First-Come-First-Served solution. Additionally, a data driven analysis is performed for the Los Angeles environment and probabilistic distributions of pertinent uncertainty sources are obtained. A sensitivity analysis is then carried out to assess the methodology performance and find optimal sampling parameters. Finally, simulations of increasing traffic density in the presence of uncertainty are conducted first for integrated arrivals and departures, then for integrated surface and air operations. To compare the optimization results and show the benefits of integrated operations, two aircraft separation methods are implemented that offer different routing options. The simulations of integrated air operations and the simulations of integrated air and surface operations demonstrate that significant traveling time savings, both total and individual surface and air times, can be obtained when more direct routes are allowed to be traveled even in the presence of uncertainty. The resulting routings induce however extra take off delay for departing flights. As a consequence, some flights cannot meet their initial assigned runway slot which engenders runway position shifting when comparing resulting runway sequences computed under both deterministic and stochastic conditions. The optimization is able to compute an optimal runway schedule that represents an optimal balance between total schedule delays and total travel times.
NASA Astrophysics Data System (ADS)
Santosa, B.; Siswanto, N.; Fiqihesa
2018-04-01
This paper proposes a discrete Particle Swam Optimization (PSO) to solve limited-wait hybrid flowshop scheduing problem with multi objectives. Flow shop schedulimg represents the condition when several machines are arranged in series and each job must be processed at each machine with same sequence. The objective functions are minimizing completion time (makespan), total tardiness time, and total machine idle time. Flow shop scheduling model always grows to cope with the real production system accurately. Since flow shop scheduling is a NP-Hard problem then the most suitable method to solve is metaheuristics. One of metaheuristics algorithm is Particle Swarm Optimization (PSO), an algorithm which is based on the behavior of a swarm. Originally, PSO was intended to solve continuous optimization problems. Since flow shop scheduling is a discrete optimization problem, then, we need to modify PSO to fit the problem. The modification is done by using probability transition matrix mechanism. While to handle multi objectives problem, we use Pareto Optimal (MPSO). The results of MPSO is better than the PSO because the MPSO solution set produced higher probability to find the optimal solution. Besides the MPSO solution set is closer to the optimal solution
Use of androgen deprivation therapy in prostate cancer: indications and prevalence
Connolly, Roisin M; Carducci, Michael A; Antonarakis, Emmanuel S
2012-01-01
Androgens play a prominent role in the development, maintenance and progression of prostate cancer. The introduction of androgen deprivation therapies into the treatment paradigm for prostate cancer patients has resulted in a wide variety of benefits ranging from a survival advantage for those with clinically localized or locally advanced disease, to improvements in symptom control for patients with advanced disease. Controversies remain, however, surrounding the optimal timing, duration and schedule of these hormonal approaches. Newer hormonal manipulations such as abiraterone acetate have also been investigated and will broaden treatment options for men with prostate cancer. This review highlights the various androgen-directed treatment options available to men with prostate cancer, their specific indications and the evidence supporting each approach, as well as patterns of use of hormonal therapies. PMID:22231299
Optimization of robotic welding procedures for maintenance repair of hydraulic turbines
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lamarche, L.; Galopin, M.; Simoneau, R.
1996-12-31
A six axes super-compact robot is used for field repair of cavitation damages found on the discharge ring of hydraulic turbines. Optimization of overlay welding procedures to minimize surface distortion and reduce tearing forces on anchors in concrete, were studied through experimentation and FEM modelling. Planned experimentation has been used to develop optimum pulsed GMAW schedules of stainless steel overlays in 2G position. Best welding sequence was resolved through over lay welding of free plates. Each overlay consisted in one or two layers which were welded in the longitudinal and/or transverse direction of the rectangular plate. A bidirectional welding mode,more » a longitudinal layer followed by a transverse layer position and no cooling between the two layers, were found to be most effective in reducing distortion. The optimized 2G welding procedure was applied to a simulated field repair. Plate was anchored on a massive iron bracket with a set of instrumented bolts, to understand how normal tearing forces in anchors evolve. Preliminary results on FEM modelling of lateral force on anchors indicate good correlation with experiments, for an elementary design.« less
Kamat, Ashish M; Flaig, Thomas W; Grossman, H Barton; Konety, Badrinath; Lamm, Donald; O'Donnell, Michael A; Uchio, Edward; Efstathiou, Jason A; Taylor, John A
2015-04-01
Multiple clinical trials have demonstrated that intravesical Bacillus Calmette-Guérin (BCG) treatment reduces recurrences and progression in patients with non-muscle-invasive bladder cancer (NMIBC). However, although BCG has been in use for almost 40 years, this agent is often underutilized and practice patterns of administration vary. This neglect is most likely caused by uncertainties about the optimal use of BCG, including unawareness of optimal treatment schedules and about patient populations that most benefit from BCG treatment. To address this deficit, a focus group of specialized urologic oncologists (urologists, medical oncologists and radiation oncologists) reviewed the current guidelines and clinical evidence, discussed their experiences and formed a consensus regarding the optimal use of BCG in the management of patients with NIMBC. The experts concluded that continuing therapy with 3-week BCG maintenance is superior to induction treatment only and is the single most important factor in improving outcomes in patients with NMIBC. They also concluded that a reliable alternative to radical cystectomy in truly BCG-refractory disease remains the subject of clinical trials. In addition, definitions for common terms of BCG failure, such as BCG-refractory and BCG-intolerant, have been formulated.
Methods of increasing efficiency and maintainability of pipeline systems
NASA Astrophysics Data System (ADS)
Ivanov, V. A.; Sokolov, S. M.; Ogudova, E. V.
2018-05-01
This study is dedicated to the issue of pipeline transportation system maintenance. The article identifies two classes of technical-and-economic indices, which are used to select an optimal pipeline transportation system structure. Further, the article determines various system maintenance strategies and strategy selection criteria. Meanwhile, the maintenance strategies turn out to be not sufficiently effective due to non-optimal values of maintenance intervals. This problem could be solved by running the adaptive maintenance system, which includes a pipeline transportation system reliability improvement algorithm, especially an equipment degradation computer model. In conclusion, three model building approaches for determining optimal technical systems verification inspections duration were considered.
Dutton, Gareth R; Gowey, Marissa A; Tan, Fei; Zhou, Dali; Ard, Jamy; Perri, Michael G; Lewis, Cora E
2017-08-15
Behavioral interventions for obesity produce clinically meaningful weight loss, but weight regain following treatment is common. Extended care programs attenuate weight regain and improve weight loss maintenance. However, less is known about the most effective ways to deliver extended care, including contact schedules. We compared the 12-month weight regain of an extended care program utilizing a non-conventional, clustered campaign treatment schedule and a self-directed program among individuals who previously achieved ≥5% weight reductions. Participants (N = 108; mean age = 51.6 years; mean weight = 92.6 kg; 52% African American; 95% female) who achieved ≥5% weight loss during an initial 16-week behavioral obesity treatment were randomized into a 2-arm, 12-month extended care trial. A clustered campaign condition included 12 group-based visits delivered in three, 4-week clusters. A self-directed condition included provision of the same printed intervention materials but no additional treatment visits. The study was conducted in a U.S. academic medical center from 2011 to 2015. Prior to randomization, participants lost an average of -7.55 ± 3.04 kg. Participants randomized to the 12-month clustered campaign program regained significantly less weight (0.35 ± 4.62 kg) than self-directed participants (2.40 ± 3.99 kg), which represented a significant between-group difference of 2.28 kg (p = 0.0154) after covariate adjustments. This corresponded to maintaining 87% and 64% of lost weight in the clustered campaign and self-directed conditions, respectively, which was a significant between-group difference of 29% maintenance of lost weight after covariate adjustments, p = 0.0396. In this initial test of a clustered campaign treatment schedule, this novel approach effectively promoted 12-month maintenance of lost weight. Future trials should directly compare the clustered campaigns with conventional (e.g., monthly) extended care schedules. Clinicaltrials.gov NCT02487121 . Registered 06/26/2015 (retrospectively registered).
Krauss, Gregory; Biton, Victor; Harvey, Jay H; Elger, Christian; Trinka, Eugen; Soares da Silva, Patrício; Gama, Helena; Cheng, Hailong; Grinnell, Todd; Blum, David
2018-01-01
To examine the influence of titration schedule and maintenance dose on the incidence and type of treatment-emergent adverse events (TEAEs) associated with adjunctive eslicarbazepine acetate (ESL). Data from three randomized, double-blind, placebo-controlled trials were analyzed. Patients with refractory partial-onset seizures were randomized to maintenance doses of ESL 400, 800, or 1200mg QD (dosing was initiated at 400 or 800mg QD) or placebo. The incidence of TEAEs was analyzed during the double-blind period (2-week titration phase; 12-week maintenance phase), according to the randomized maintenance dose and the titration schedule. 1447 patients were included in the analysis. During the first week of treatment, 62% of patients taking ESL 800mg QD had ≥1 TEAE, vs 35% of those taking 400mg QD and 32% of the placebo group; dizziness, somnolence, nausea, and headache were numerically more frequent in patients taking ESL 800mg than those taking ESL 400mg QD. During the double-blind period, the incidences of common TEAEs were lower in patients who initiated ESL at 400mg vs 800mg QD. For the 800 and 1200mg QD maintenance doses, rates of TEAEs leading to discontinuation were lower in patients who began treatment with 400mg than in those who began taking ESL 800mg QD. Initiation of ESL at 800mg QD is feasible. However, initiating treatment with ESL 400mg QD for 1 or 2 weeks is recommended, being associated with a lower incidence of TEAEs, and related discontinuations. For some patients, treatment may be initiated at 800mg QD, if the need for more immediate seizure reduction outweighs concerns about increased risk of adverse reactions during initiation. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.
The impact of roster changes on absenteeism and incident frequency in an Australian coal mine
Baker, A; Heiler, K; Ferguson, S
2003-01-01
Background: The occupational health and safety implications associated with compressed and extended work periods have not been fully explored in the mining sector. Aims: To examine the impact on employee health and safety of changes to the roster system in an Australian coal mine. Methods: Absenteeism and incident frequency rate data were collected over a 33 month period that covered three different roster schedules. Period 1 covered the original 8-hour/7-day roster. Period 2 covered a 12-month period under a 12-hour/7-day schedule, and period 3 covered a 12-month period during which a roster that scheduled shifts only on weekdays, with uncapped overtime on weekends and days off (12-hour/5-day) was in place. Data were collected and analysed from the maintenance, mining, and coal preparation plant (CPP) sectors. Results: The only significant change in absenteeism rates was an increase in the maintenance sector in the third data collection period. Absenteeism rates in the mining and CPP sectors were not different between data collection periods. The increase in the maintenance sector may be owing to: (1) a greater requirement for maintenance employees to perform overtime as a result of the roster change compared to other employee groups; or (2) greater monotony associated with extended work periods for maintenance employees compared to others. After the first roster change, accident incident frequency decreased in the CPP sector but not in the other sectors. There was no effect on incident frequency after the second roster change in any sector. Conclusions: The current study did not find significant negative effects of a 12-hour pattern, when compared to an 8-hour system. However, when unregulated and excessive overtime was introduced as part of the 12-hour/5-day roster, absenteeism rates were increased in the maintenance sector. The combination of excessive work hours and lack of consultation with employees regarding the second change may have contributed to the overall negative effects. PMID:12499456
Optimization of scheduling system for plant watering using electric cars in agro techno park
NASA Astrophysics Data System (ADS)
Oktavia Adiwijaya, Nelly; Herlambang, Yudha; Slamin
2018-04-01
Agro Techno Park in University of Jember is a special area used for the development of agriculture, livestock and fishery. In this plantation, the process of watering the plants is according to the frequency of each plant needs. This research develops the optimization of plant watering scheduling system using edge coloring of graph. This research was conducted in 3 stages, namely, data collection phase, analysis phase, and system development stage. The collected data was analyzed and then converted into a graph by using bipartite adjacency matrix representation. The development phase is conducted to build a web-based watering schedule optimization system. The result of this research showed that the schedule system is optimal because it can maximize the use of all electric cars to water the plants and minimize the number of idle cars.
NASA Astrophysics Data System (ADS)
Lu, Yuan-Yuan; Wang, Ji-Bo; Ji, Ping; He, Hongyu
2017-09-01
In this article, single-machine group scheduling with learning effects and convex resource allocation is studied. The goal is to find the optimal job schedule, the optimal group schedule, and resource allocations of jobs and groups. For the problem of minimizing the makespan subject to limited resource availability, it is proved that the problem can be solved in polynomial time under the condition that the setup times of groups are independent. For the general setup times of groups, a heuristic algorithm and a branch-and-bound algorithm are proposed, respectively. Computational experiments show that the performance of the heuristic algorithm is fairly accurate in obtaining near-optimal solutions.
Computer-aided resource planning and scheduling for radiological services
NASA Astrophysics Data System (ADS)
Garcia, Hong-Mei C.; Yun, David Y.; Ge, Yiqun; Khan, Javed I.
1996-05-01
There exists tremendous opportunity in hospital-wide resource optimization based on system integration. This paper defines the resource planning and scheduling requirements integral to PACS, RIS and HIS integration. An multi-site case study is conducted to define the requirements. A well-tested planning and scheduling methodology, called Constrained Resource Planning model, has been applied to the chosen problem of radiological service optimization. This investigation focuses on resource optimization issues for minimizing the turnaround time to increase clinical efficiency and customer satisfaction, particularly in cases where the scheduling of multiple exams are required for a patient. How best to combine the information system efficiency and human intelligence in improving radiological services is described. Finally, an architecture for interfacing a computer-aided resource planning and scheduling tool with the existing PACS, HIS and RIS implementation is presented.
The Composition of the Master Schedule
NASA Technical Reports Server (NTRS)
Thomas, Cynthia C.; Behrend, Dirk; MacMillan, Daniel S.
2010-01-01
Over a period of about four months, the IVS Coordinating Center (IVSCC) each year composes the Master Schedule for the IVS observing program of the next calendar year. The process begins in early July when the IVSCC contacts the IVS Network Stations to request information about available station time as well as holiday and maintenance schedules for the upcoming year. Going through various planning stages and a review process with the IVS Observing Program Committee (OPC), the final version of the Master Schedule is posted by early November. We describe the general steps of the composition and illustrate them with the example of the planning for the Master Schedule of the 2010 observing year.
NASA Technical Reports Server (NTRS)
Brown, Aaron J.
2011-01-01
Orbit maintenance is the series of burns performed during a mission to ensure the orbit satisfies mission constraints. Low-altitude missions often require non-trivial orbit maintenance (Delta)V due to sizable orbital perturbations and minimum altitude thresholds. A strategy is presented for minimizing this (Delta)V using impulsive burn parameter optimization. An initial estimate for the burn parameters is generated by considering a feasible solution to the orbit maintenance problem. An example demonstrates the dV savings from the feasible solution to the optimal solution.
AN OPTIMAL MAINTENANCE MANAGEMENT MODEL FOR AIRPORT CONCRETE PAVEMENT
NASA Astrophysics Data System (ADS)
Shimomura, Taizo; Fujimori, Yuji; Kaito, Kiyoyuki; Obama, Kengo; Kobayashi, Kiyoshi
In this paper, an optimal management model is formulated for the performance-based rehabilitation/maintenance contract for airport concrete pavement, whereby two types of life cycle cost risks, i.e., ground consolidation risk and concrete depreciation risk, are explicitly considered. The non-homogenous Markov chain model is formulated to represent the deterioration processes of concrete pavement which are conditional upon the ground consolidation processes. The optimal non-homogenous Markov decision model with multiple types of risk is presented to design the optimal rehabilitation/maintenance plans. And the methodology to revise the optimal rehabilitation/maintenance plans based upon the monitoring data by the Bayesian up-to-dating rules. The validity of the methodology presented in this paper is examined based upon the case studies carried out for the H airport.
Lokhandwala, Parvez M; Shike, Hiroko; Wang, Ming; Domen, Ronald E; George, Melissa R
2018-01-01
Typical approach for increasing apheresis platelet collections is to recruit new donors. Here, we investigated the effectiveness of an alternative strategy: optimizing donor scheduling, prior to recruitment, at a hospital-based blood donor center. Analysis of collections, during the 89 consecutive months since opening of donor center, was performed. Linear regression and segmented time-series analyses were performed to calculate growth rates of collections and to test for statistical differences, respectively. Pre-intervention donor scheduling capacity was 39/month. In the absence of active donor recruitment, during the first 29 months, the number of collections rose gradually to 24/month (growth-rate of 0.70/month). However, between month-30 and -55, collections exhibited a plateau at 25.6 ± 3.0 (growth-rate of -0.09/month) (p<0.0001). This plateau-phase coincided with donor schedule approaching saturation (65.6 ± 7.6% schedule booked). Scheduling capacity was increased by following two interventions: adding an apheresis instrument (month-56) and adding two more collection days/week (month-72). Consequently, the scheduling capacity increased to 130/month. Post-interventions, apheresis platelet collections between month-56 and -81 exhibited a spontaneous renewed growth at a rate of 0.62/month (p<0.0001), in absence of active donor recruitment. Active donor recruitment in month-82 and -86, when the donor schedule had been optimized to accommodate further growth, resulted in a dramatic but transient surge in collections. Apheresis platelet collections plateau at nearly 2/3rd of the scheduling capacity. Optimizing the scheduling capacity prior to active donor recruitment is an effective strategy to increase platelet collections at a hospital-based donor center.
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
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
Axelrod, David E; Vedula, Sudeepti; Obaniyi, James
2017-05-01
The effectiveness of cancer chemotherapy is limited by intra-tumor heterogeneity, the emergence of spontaneous and induced drug-resistant mutant subclones, and the maximum dose to which normal tissues can be exposed without adverse side effects. The goal of this project was to determine if intermittent schedules of the maximum dose that allows colon crypt maintenance could overcome these limitations, specifically by eliminating mixtures of drug-resistant mutants from heterogeneous early colon adenomas while maintaining colon crypt function. A computer model of cell dynamics in human colon crypts was calibrated with measurements of human biopsy specimens. The model allowed simulation of continuous and intermittent dose schedules of a cytotoxic chemotherapeutic drug, as well as the drug's effect on the elimination of mutant cells and the maintenance of crypt function. Colon crypts can tolerate a tenfold greater intermittent dose than constant dose. This allows elimination of a mixture of relatively drug-sensitive and drug-resistant mutant subclones from heterogeneous colon crypts. Mutants can be eliminated whether they arise spontaneously or are induced by the cytotoxic drug. An intermittent dose, at the maximum that allows colon crypt maintenance, can be effective in eliminating a heterogeneous mixture of mutant subclones before they fill the crypt and form an adenoma.
14 CFR 121.343 - Flight data recorders.
Code of Federal Regulations, 2011 CFR
2011-01-01
... recorder must be installed at the next heavy maintenance check after May 26, 1994, but no later than May 26, 1995. A heavy maintenance check is considered to be any time an aircraft is scheduled to be out of..., 1995, compliance date for all aircraft on that list. (3) After May 26, 1994, any aircraft that is...
14 CFR 121.343 - Flight data recorders.
Code of Federal Regulations, 2012 CFR
2012-01-01
... recorder must be installed at the next heavy maintenance check after May 26, 1994, but no later than May 26, 1995. A heavy maintenance check is considered to be any time an aircraft is scheduled to be out of..., 1995, compliance date for all aircraft on that list. (3) After May 26, 1994, any aircraft that is...
14 CFR 121.343 - Flight data recorders.
Code of Federal Regulations, 2013 CFR
2013-01-01
... recorder must be installed at the next heavy maintenance check after May 26, 1994, but no later than May 26, 1995. A heavy maintenance check is considered to be any time an aircraft is scheduled to be out of..., 1995, compliance date for all aircraft on that list. (3) After May 26, 1994, any aircraft that is...
14 CFR 121.343 - Flight data recorders.
Code of Federal Regulations, 2010 CFR
2010-01-01
... recorder must be installed at the next heavy maintenance check after May 26, 1994, but no later than May 26, 1995. A heavy maintenance check is considered to be any time an aircraft is scheduled to be out of..., 1995, compliance date for all aircraft on that list. (3) After May 26, 1994, any aircraft that is...
14 CFR 121.343 - Flight data recorders.
Code of Federal Regulations, 2014 CFR
2014-01-01
... recorder must be installed at the next heavy maintenance check after May 26, 1994, but no later than May 26, 1995. A heavy maintenance check is considered to be any time an aircraft is scheduled to be out of..., 1995, compliance date for all aircraft on that list. (3) After May 26, 1994, any aircraft that is...
40 CFR 53.4 - Applications for reference or equivalent method determinations.
Code of Federal Regulations, 2012 CFR
2012-07-01
...) Required or recommended routine, periodic, and preventative maintenance and maintenance schedules. (J) Any... methods for PM2.5 and PM10−2.5 must be described in sufficient detail, based on the elements described in... Table A-1 to this subpart) will be met throughout the warranty period and that the applicant accepts...
40 CFR 53.4 - Applications for reference or equivalent method determinations.
Code of Federal Regulations, 2011 CFR
2011-07-01
...) Required or recommended routine, periodic, and preventative maintenance and maintenance schedules. (J) Any... methods for PM2.5 and PM10−2.5 must be described in sufficient detail, based on the elements described in... Table A-1 to this subpart) will be met throughout the warranty period and that the applicant accepts...
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.
Optimal load scheduling in commercial and residential microgrids
NASA Astrophysics Data System (ADS)
Ganji Tanha, Mohammad Mahdi
Residential and commercial electricity customers use more than two third of the total energy consumed in the United States, representing a significant resource of demand response. Price-based demand response, which is in response to changes in electricity prices, represents the adjustments in load through optimal load scheduling (OLS). In this study, an efficient model for OLS is developed for residential and commercial microgrids which include aggregated loads in single-units and communal loads. Single unit loads which include fixed, adjustable and shiftable loads are controllable by the unit occupants. Communal loads which include pool pumps, elevators and central heating/cooling systems are shared among the units. In order to optimally schedule residential and commercial loads, a community-based optimal load scheduling (CBOLS) is proposed in this thesis. The CBOLS schedule considers hourly market prices, occupants' comfort level, and microgrid operation constraints. The CBOLS' objective in residential and commercial microgrids is the constrained minimization of the total cost of supplying the aggregator load, defined as the microgrid load minus the microgrid generation. This problem is represented by a large-scale mixed-integer optimization for supplying single-unit and communal loads. The Lagrangian relaxation methodology is used to relax the linking communal load constraint and decompose the independent single-unit functions into subproblems which can be solved in parallel. The optimal solution is acceptable if the aggregator load limit and the duality gap are within the bounds. If any of the proposed criteria is not satisfied, the Lagrangian multiplier will be updated and a new optimal load schedule will be regenerated until both constraints are satisfied. The proposed method is applied to several case studies and the results are presented for the Galvin Center load on the 16th floor of the IIT Tower in Chicago.
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.
Uplink Packet-Data Scheduling in DS-CDMA Systems
NASA Astrophysics Data System (ADS)
Choi, Young Woo; Kim, Seong-Lyun
In this letter, we consider the uplink packet scheduling for non-real-time data users in a DS-CDMA system. As an effort to jointly optimize throughput and fairness, we formulate a time-span minimization problem incorporating the time-multiplexing of different simultaneous transmission schemes. Based on simple rules, we propose efficient scheduling algorithms and compare them with the optimal solution obtained by linear programming.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wright, J.L.
1992-06-18
Properly selected and maintained chain drives can be expected to give thousands of hours of reliable service. Selection is usually done just once. This paper reports on good maintenance which must be done regularly to keep the drive operating. An effective maintenance program for roller chain should include correct type and adequate amounts of lubrication, replacement of worn chains and sprockets, and elimination of drive interferences. It is important to set u a lubrication and inspection/correction schedule to ensure that all required maintenance is carried out.
Diagnostics of heavy mining equipment during the scheduled preventive maintenance
NASA Astrophysics Data System (ADS)
Drygin, M. Yu; Kuryshkin, N. P.
2018-01-01
Intensification of production, economic globalization and dramatic downgrade of the workers’ professional skills lead to unacceptable technical state of heavy mining equipment. Equipment maintenance outage reaches 84 % of the total downtime, of which emergency maintenance takes up to 36 % of time, that excesses 429 hours per year fr one excavator. It is shown that yearly diagnostics using methods of non-destructive check allows to reduce emergency downtime by 47 %, and 55 % of revealed defects can be eliminated without breaking the technological cycle of the equipment.
Simulators for Maintenance Training: Some Issues, Problems and Areas for Future Research
1978-07-01
trainer into a full-scale, three-dimensional simulation of one cabinet of the NIKE HIPAR system. Test points for troubleshooting were located on simulated...described was used to teach maintenance of the NIKE HIPAR system. It too was considered to be a general purpose trainer in that its basic features could be...types of maintenance simulators based on a detailed task analysis of the NIKE HIPAR system as it existed one year before it was scheduled to become
Jiang, Yuyi; Shao, Zhiqing; Guo, Yi
2014-01-01
A complex computing problem can be solved efficiently on a system with multiple computing nodes by dividing its implementation code into several parallel processing modules or tasks that can be formulated as directed acyclic graph (DAG) problems. The DAG jobs may be mapped to and scheduled on the computing nodes to minimize the total execution time. Searching an optimal DAG scheduling solution is considered to be NP-complete. This paper proposed a tuple molecular structure-based chemical reaction optimization (TMSCRO) method for DAG scheduling on heterogeneous computing systems, based on a very recently proposed metaheuristic method, chemical reaction optimization (CRO). Comparing with other CRO-based algorithms for DAG scheduling, the design of tuple reaction molecular structure and four elementary reaction operators of TMSCRO is more reasonable. TMSCRO also applies the concept of constrained critical paths (CCPs), constrained-critical-path directed acyclic graph (CCPDAG) and super molecule for accelerating convergence. In this paper, we have also conducted simulation experiments to verify the effectiveness and efficiency of TMSCRO upon a large set of randomly generated graphs and the graphs for real world problems. PMID:25143977
Jiang, Yuyi; Shao, Zhiqing; Guo, Yi
2014-01-01
A complex computing problem can be solved efficiently on a system with multiple computing nodes by dividing its implementation code into several parallel processing modules or tasks that can be formulated as directed acyclic graph (DAG) problems. The DAG jobs may be mapped to and scheduled on the computing nodes to minimize the total execution time. Searching an optimal DAG scheduling solution is considered to be NP-complete. This paper proposed a tuple molecular structure-based chemical reaction optimization (TMSCRO) method for DAG scheduling on heterogeneous computing systems, based on a very recently proposed metaheuristic method, chemical reaction optimization (CRO). Comparing with other CRO-based algorithms for DAG scheduling, the design of tuple reaction molecular structure and four elementary reaction operators of TMSCRO is more reasonable. TMSCRO also applies the concept of constrained critical paths (CCPs), constrained-critical-path directed acyclic graph (CCPDAG) and super molecule for accelerating convergence. In this paper, we have also conducted simulation experiments to verify the effectiveness and efficiency of TMSCRO upon a large set of randomly generated graphs and the graphs for real world problems.
Resource planning and scheduling of payload for satellite with particle swarm optimization
NASA Astrophysics Data System (ADS)
Li, Jian; Wang, Cheng
2007-11-01
The resource planning and scheduling technology of payload is a key technology to realize an automated control for earth observing satellite with limited resources on satellite, which is implemented to arrange the works states of various payloads to carry out missions by optimizing the scheme of the resources. The scheduling task is a difficult constraint optimization problem with various and mutative requests and constraints. Based on the analysis of the satellite's functions and the payload's resource constraints, a proactive planning and scheduling strategy based on the availability of consumable and replenishable resources in time-order is introduced along with dividing the planning and scheduling period to several pieces. A particle swarm optimization algorithm is proposed to address the problem with an adaptive mutation operator selection, where the swarm is divided into groups with different probabilities to employ various mutation operators viz., differential evolution, Gaussian and random mutation operators. The probabilities are adjusted adaptively by comparing the effectiveness of the groups to select a proper operator. The simulation results have shown the feasibility and effectiveness of the method.
Synthesis of optimal usage of available aggregates in highway construction and maintenance.
DOT National Transportation Integrated Search
2009-11-01
The optimization of available aggregates for highway construction and maintenance is vital both from an economic and environmental perspective. By not optimizing the aggregate supply, project costs escalate as a simple response to supply and demand. ...
A manpower scheduling heuristic for aircraft maintenance application
NASA Astrophysics Data System (ADS)
Sze, San-Nah; Sze, Jeeu-Fong; Chiew, Kang-Leng
2012-09-01
This research studies a manpower scheduling for aircraft maintenance, focusing on in-flight food loading operation. A group of loading teams with flexible shifts is required to deliver and upload packaged meals from the ground kitchen to aircrafts in multiple trips. All aircrafts must be served within predefined time windows. The scheduling process takes into account of various constraints such as meal break allocation, multi-trip traveling and food exposure time limit. Considering the aircrafts movement and predefined maximum working hours for each loading team, the main objective of this study is to form an efficient roster by assigning a minimum number of loading teams to the aircrafts. We proposed an insertion based heuristic to generate the solutions in a short period of time for large instances. This proposed algorithm is implemented in various stages for constructing trips due to the presence of numerous constraints. The robustness and efficiency of the algorithm is demonstrated in computational results. The results show that the insertion heuristic more efficiently outperforms the company's current practice.
Optimal maintenance of a multi-unit system under dependencies
NASA Astrophysics Data System (ADS)
Sung, Ho-Joon
The availability, or reliability, of an engineering component greatly influences the operational cost and safety characteristics of a modern system over its life-cycle. Until recently, the reliance on past empirical data has been the industry-standard practice to develop maintenance policies that provide the minimum level of system reliability. Because such empirically-derived policies are vulnerable to unforeseen or fast-changing external factors, recent advancements in the study of topic on maintenance, which is known as optimal maintenance problem, has gained considerable interest as a legitimate area of research. An extensive body of applicable work is available, ranging from those concerned with identifying maintenance policies aimed at providing required system availability at minimum possible cost, to topics on imperfect maintenance of multi-unit system under dependencies. Nonetheless, these existing mathematical approaches to solve for optimal maintenance policies must be treated with caution when considered for broader applications, as they are accompanied by specialized treatments to ease the mathematical derivation of unknown functions in both objective function and constraint for a given optimal maintenance problem. These unknown functions are defined as reliability measures in this thesis, and theses measures (e.g., expected number of failures, system renewal cycle, expected system up time, etc.) do not often lend themselves to possess closed-form formulas. It is thus quite common to impose simplifying assumptions on input probability distributions of components' lifetime or repair policies. Simplifying the complex structure of a multi-unit system to a k-out-of-n system by neglecting any sources of dependencies is another commonly practiced technique intended to increase the mathematical tractability of a particular model. This dissertation presents a proposal for an alternative methodology to solve optimal maintenance problems by aiming to achieve the same end-goals as Reliability Centered Maintenance (RCM). RCM was first introduced to the aircraft industry in an attempt to bridge the gap between the empirically-driven and theory-driven approaches to establishing optimal maintenance policies. Under RCM, qualitative processes that enable the prioritizing of functions based on the criticality and influence would be combined with mathematical modeling to obtain the optimal maintenance policies. Where this thesis work deviates from RCM is its proposal to directly apply quantitative processes to model the reliability measures in optimal maintenance problem. First, Monte Carlo (MC) simulation, in conjunction with a pre-determined Design of Experiments (DOE) table, can be used as a numerical means of obtaining the corresponding discrete simulated outcomes of the reliability measures based on the combination of decision variables (e.g., periodic preventive maintenance interval, trigger age for opportunistic maintenance, etc.). These discrete simulation results can then be regressed as Response Surface Equations (RSEs) with respect to the decision variables. Such an approach to represent the reliability measures with continuous surrogate functions (i.e., the RSEs) not only enables the application of the numerical optimization technique to solve for optimal maintenance policies, but also obviates the need to make mathematical assumptions or impose over-simplifications on the structure of a multi-unit system for the sake of mathematical tractability. The applicability of the proposed methodology to a real-world optimal maintenance problem is showcased through its application to a Time Limited Dispatch (TLD) of Full Authority Digital Engine Control (FADEC) system. In broader terms, this proof-of-concept exercise can be described as a constrained optimization problem, whose objective is to identify the optimal system inspection interval that guarantees a certain level of availability for a multi-unit system. A variety of reputable numerical techniques were used to model the problem as accurately as possible, including algorithms for the MC simulation, imperfect maintenance model from quasi renewal processes, repair time simulation, and state transition rules. Variance Reduction Techniques (VRTs) were also used in an effort to enhance MC simulation efficiency. After accurate MC simulation results are obtained, the RSEs are generated based on the goodness-of-fit measure to yield as parsimonious model as possible to construct the optimization problem. Under the assumption of constant failure rate for lifetime distributions, the inspection interval from the proposed methodology was found to be consistent with the one from the common approach used in industry that leverages Continuous Time Markov Chain (CTMC). While the latter does not consider maintenance cost settings, the proposed methodology enables an operator to consider different types of maintenance cost settings, e.g., inspection cost, system corrective maintenance cost, etc., to result in more flexible maintenance policies. When the proposed methodology was applied to the same TLD of FADEC example, but under the more generalized assumption of strictly Increasing Failure Rate (IFR) for lifetime distribution, it was shown to successfully capture component wear-out, as well as the economic dependencies among the system components.
Expert systems tools for Hubble Space Telescope observation scheduling
NASA Technical Reports Server (NTRS)
Miller, Glenn; Rosenthal, Don; Cohen, William; Johnston, Mark
1987-01-01
The utility of expert systems techniques for the Hubble Space Telescope (HST) planning and scheduling is discussed and a plan for development of expert system tools which will augment the existing ground system is described. Additional capabilities provided by these tools will include graphics-oriented plan evaluation, long-range analysis of the observation pool, analysis of optimal scheduling time intervals, constructing sequences of spacecraft activities which minimize operational overhead, and optimization of linkages between observations. Initial prototyping of a scheduler used the Automated Reasoning Tool running on a LISP workstation.
A modify ant colony optimization for the grid jobs scheduling problem with QoS requirements
NASA Astrophysics Data System (ADS)
Pu, Xun; Lu, XianLiang
2011-10-01
Job scheduling with customers' quality of service (QoS) requirement is challenging in grid environment. In this paper, we present a modify Ant colony optimization (MACO) for the Job scheduling problem in grid. Instead of using the conventional construction approach to construct feasible schedules, the proposed algorithm employs a decomposition method to satisfy the customer's deadline and cost requirements. Besides, a new mechanism of service instances state updating is embedded to improve the convergence of MACO. Experiments demonstrate the effectiveness of the proposed algorithm.
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).
Genetic algorithm parameters tuning for resource-constrained project scheduling problem
NASA Astrophysics Data System (ADS)
Tian, Xingke; Yuan, Shengrui
2018-04-01
Project Scheduling Problem (RCPSP) is a kind of important scheduling problem. To achieve a certain optimal goal such as the shortest duration, the smallest cost, the resource balance and so on, it is required to arrange the start and finish of all tasks under the condition of satisfying project timing constraints and resource constraints. In theory, the problem belongs to the NP-hard problem, and the model is abundant. Many combinatorial optimization problems are special cases of RCPSP, such as job shop scheduling, flow shop scheduling and so on. At present, the genetic algorithm (GA) has been used to deal with the classical RCPSP problem and achieved remarkable results. Vast scholars have also studied the improved genetic algorithm for the RCPSP problem, which makes it to solve the RCPSP problem more efficiently and accurately. However, for the selection of the main parameters of the genetic algorithm, there is no parameter optimization in these studies. Generally, we used the empirical method, but it cannot ensure to meet the optimal parameters. In this paper, the problem was carried out, which is the blind selection of parameters in the process of solving the RCPSP problem. We made sampling analysis, the establishment of proxy model and ultimately solved the optimal parameters.
Soolari, Ahmad
2002-05-01
Periodontal disease is a chronic disease that is perceived by many patients to be nonthreatening. Periodontal therapy has been shown to be less effective if a regular periodontal maintenance schedule is not followed after completion of active therapy. Periodontal maintenance is an integral part of successful periodontal therapy.
Conception of Self-Construction Production Scheduling System
NASA Astrophysics Data System (ADS)
Xue, Hai; Zhang, Xuerui; Shimizu, Yasuhiro; Fujimura, Shigeru
With the high speed innovation of information technology, many production scheduling systems have been developed. However, a lot of customization according to individual production environment is required, and then a large investment for development and maintenance is indispensable. Therefore now the direction to construct scheduling systems should be changed. The final objective of this research aims at developing a system which is built by it extracting the scheduling technique automatically through the daily production scheduling work, so that an investment will be reduced. This extraction mechanism should be applied for various production processes for the interoperability. Using the master information extracted by the system, production scheduling operators can be supported to accelerate the production scheduling work easily and accurately without any restriction of scheduling operations. By installing this extraction mechanism, it is easy to introduce scheduling system without a lot of expense for customization. In this paper, at first a model for expressing a scheduling problem is proposed. Then the guideline to extract the scheduling information and use the extracted information is shown and some applied functions are also proposed based on it.
Product modular design incorporating preventive maintenance issues
NASA Astrophysics Data System (ADS)
Gao, Yicong; Feng, Yixiong; Tan, Jianrong
2016-03-01
Traditional modular design methods lead to product maintenance problems, because the module form of a system is created according to either the function requirements or the manufacturing considerations. For solving these problems, a new modular design method is proposed with the considerations of not only the traditional function related attributes, but also the maintenance related ones. First, modularity parameters and modularity scenarios for product modularity are defined. Then the reliability and economic assessment models of product modularity strategies are formulated with the introduction of the effective working age of modules. A mathematical model used to evaluate the difference among the modules of the product so that the optimal module of the product can be established. After that, a multi-objective optimization problem based on metrics for preventive maintenance interval different degrees and preventive maintenance economics is formulated for modular optimization. Multi-objective GA is utilized to rapidly approximate the Pareto set of optimal modularity strategy trade-offs between preventive maintenance cost and preventive maintenance interval difference degree. Finally, a coordinate CNC boring machine is adopted to depict the process of product modularity. In addition, two factorial design experiments based on the modularity parameters are constructed and analyzed. These experiments investigate the impacts of these parameters on the optimal modularity strategies and the structure of module. The research proposes a new modular design method, which may help to improve the maintainability of product in modular design.
Pavement maintenance optimization model using Markov Decision Processes
NASA Astrophysics Data System (ADS)
Mandiartha, P.; Duffield, C. F.; Razelan, I. S. b. M.; Ismail, A. b. H.
2017-09-01
This paper presents an optimization model for selection of pavement maintenance intervention using a theory of Markov Decision Processes (MDP). There are some particular characteristics of the MDP developed in this paper which distinguish it from other similar studies or optimization models intended for pavement maintenance policy development. These unique characteristics include a direct inclusion of constraints into the formulation of MDP, the use of an average cost method of MDP, and the policy development process based on the dual linear programming solution. The limited information or discussions that are available on these matters in terms of stochastic based optimization model in road network management motivates this study. This paper uses a data set acquired from road authorities of state of Victoria, Australia, to test the model and recommends steps in the computation of MDP based stochastic optimization model, leading to the development of optimum pavement maintenance policy.
Feng, Qiang; Chen, Yiran; Sun, Bo; Li, Songjie
2014-01-01
An optimization method for condition based maintenance (CBM) of aircraft fleet considering prognostics uncertainty is proposed. The CBM and dispatch process of aircraft fleet is analyzed first, and the alternative strategy sets for single aircraft are given. Then, the optimization problem of fleet CBM with lower maintenance cost and dispatch risk is translated to the combinatorial optimization problem of single aircraft strategy. Remain useful life (RUL) distribution of the key line replaceable Module (LRM) has been transformed into the failure probability of the aircraft and the fleet health status matrix is established. And the calculation method of the costs and risks for mission based on health status matrix and maintenance matrix is given. Further, an optimization method for fleet dispatch and CBM under acceptable risk is proposed based on an improved genetic algorithm. Finally, a fleet of 10 aircrafts is studied to verify the proposed method. The results shows that it could realize optimization and control of the aircraft fleet oriented to mission success.
Chen, Yiran; Sun, Bo; Li, Songjie
2014-01-01
An optimization method for condition based maintenance (CBM) of aircraft fleet considering prognostics uncertainty is proposed. The CBM and dispatch process of aircraft fleet is analyzed first, and the alternative strategy sets for single aircraft are given. Then, the optimization problem of fleet CBM with lower maintenance cost and dispatch risk is translated to the combinatorial optimization problem of single aircraft strategy. Remain useful life (RUL) distribution of the key line replaceable Module (LRM) has been transformed into the failure probability of the aircraft and the fleet health status matrix is established. And the calculation method of the costs and risks for mission based on health status matrix and maintenance matrix is given. Further, an optimization method for fleet dispatch and CBM under acceptable risk is proposed based on an improved genetic algorithm. Finally, a fleet of 10 aircrafts is studied to verify the proposed method. The results shows that it could realize optimization and control of the aircraft fleet oriented to mission success. PMID:24892046
NASA Astrophysics Data System (ADS)
Foronda, Augusto; Ohta, Chikara; Tamaki, Hisashi
Dirty paper coding (DPC) is a strategy to achieve the region capacity of multiple input multiple output (MIMO) downlink channels and a DPC scheduler is throughput optimal if users are selected according to their queue states and current rates. However, DPC is difficult to implement in practical systems. One solution, zero-forcing beamforming (ZFBF) strategy has been proposed to achieve the same asymptotic sum rate capacity as that of DPC with an exhaustive search over the entire user set. Some suboptimal user group selection schedulers with reduced complexity based on ZFBF strategy (ZFBF-SUS) and proportional fair (PF) scheduling algorithm (PF-ZFBF) have also been proposed to enhance the throughput and fairness among the users, respectively. However, they are not throughput optimal, fairness and throughput decrease if each user queue length is different due to different users channel quality. Therefore, we propose two different scheduling algorithms: a throughput optimal scheduling algorithm (ZFBF-TO) and a reduced complexity scheduling algorithm (ZFBF-RC). Both are based on ZFBF strategy and, at every time slot, the scheduling algorithms have to select some users based on user channel quality, user queue length and orthogonality among users. Moreover, the proposed algorithms have to produce the rate allocation and power allocation for the selected users based on a modified water filling method. We analyze the schedulers complexity and numerical results show that ZFBF-RC provides throughput and fairness improvements compared to the ZFBF-SUS and PF-ZFBF scheduling algorithms.
NASA Astrophysics Data System (ADS)
Sivarami Reddy, N.; Ramamurthy, D. V., Dr.; Prahlada Rao, K., Dr.
2017-08-01
This article addresses simultaneous scheduling of machines, AGVs and tools where machines are allowed to share the tools considering transfer times of jobs and tools between machines, to generate best optimal sequences that minimize makespan in a multi-machine Flexible Manufacturing System (FMS). Performance of FMS is expected to improve by effective utilization of its resources, by proper integration and synchronization of their scheduling. Symbiotic Organisms Search (SOS) algorithm is a potent tool which is a better alternative for solving optimization problems like scheduling and proven itself. The proposed SOS algorithm is tested on 22 job sets with makespan as objective for scheduling of machines and tools where machines are allowed to share tools without considering transfer times of jobs and tools and the results are compared with the results of existing methods. The results show that the SOS has outperformed. The same SOS algorithm is used for simultaneous scheduling of machines, AGVs and tools where machines are allowed to share tools considering transfer times of jobs and tools to determine the best optimal sequences that minimize makespan.
Planning and Scheduling for Fleets of Earth Observing Satellites
NASA Technical Reports Server (NTRS)
Frank, Jeremy; Jonsson, Ari; Morris, Robert; Smith, David E.; Norvig, Peter (Technical Monitor)
2001-01-01
We address the problem of scheduling observations for a collection of earth observing satellites. This scheduling task is a difficult optimization problem, potentially involving many satellites, hundreds of requests, constraints on when and how to service each request, and resources such as instruments, recording devices, transmitters, and ground stations. High-fidelity models are required to ensure the validity of schedules; at the same time, the size and complexity of the problem makes it unlikely that systematic optimization search methods will be able to solve them in a reasonable time. This paper presents a constraint-based approach to solving the Earth Observing Satellites (EOS) scheduling problem, and proposes a stochastic heuristic search method for solving it.
A self-organizing neural network for job scheduling in distributed systems
NASA Astrophysics Data System (ADS)
Newman, Harvey B.; Legrand, Iosif C.
2001-08-01
The aim of this work is to describe a possible approach for the optimization of the job scheduling in large distributed systems, based on a self-organizing Neural Network. This dynamic scheduling system should be seen as adaptive middle layer software, aware of current available resources and making the scheduling decisions using the "past experience." It aims to optimize job specific parameters as well as the resource utilization. The scheduling system is able to dynamically learn and cluster information in a large dimensional parameter space and at the same time to explore new regions in the parameters space. This self-organizing scheduling system may offer a possible solution to provide an effective use of resources for the off-line data processing jobs for future HEP experiments.
Check-off logs for routine equipment maintenance.
Brewster, M A; Carver, P H; Randolph, B
1995-12-01
The regulatory requirement for appropriate routine instrument maintenance documentation is approached by laboratories in numerous ways. Standard operating procedures (SOPs) may refer to maintenance listed in instrument manuals, may indicate "periodic" performance of an action, or may indicate specific tasks to be performed at certain frequencies. The Quality Assurance Unit (QAU) task of assuring the performance of these indicated maintenance tasks can be extremely laborious if these records are merged with other analysis records. Further, the lack of written maintenance schedules often leads to omission of infrequently performed tasks. We recommend creation of routine maintenance check-off logs for instruments with tasks grouped by frequency of expected performance. Usage of such logs should result in better laboratory compliance with SOPs and the compliance can be readily monitored by QAU or by regulatory agencies.
Optimizing The Scheduling Of Recruitment And Initial Training For Soldiers In The Australian Army
2016-03-01
SCHEDULING OF RECRUITMENT AND INITIAL TRAINING FOR SOLDIERS IN THE AUSTRALIAN ARMY by Melissa T. Joy March 2016 Thesis Advisor: Kenneth...SOLDIERS IN THE AUSTRALIAN ARMY 5. FUNDING NUMBERS 6. AUTHOR(S) Melissa T. Joy 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) Naval...This thesis develops a master scheduling program to optimize recruitment into the Australian Army by employment category. The goal of the model
WEST ELEVATION OF USAIR MAINTENANCE HANGAR AT GREATER BUFFALO INTERNATIONAL ...
WEST ELEVATION OF USAIR MAINTENANCE HANGAR AT GREATER BUFFALO INTERNATIONAL AIRPORT. A BOEING 737-200 HAS BEEN TOWED IN FOR AN OVERNIGHT (BALANCE) CHECK. THE TAIL DOCK STANDS ARE IN POSITION AT THE REAR OF THE AIRCRAFT TO FACILITATE INSPECTION. MAINTENANCE CREWS PERFORM NIGHTLY SERVICE ON UP TO 6 AIRCRAFT. THE NORMAL SEQUENCE OF 12 ROUTINE CHECKS COVERS SEVEN BASIC AREAS: INTERIOR, EXTERIOR, WINGS, LANDING GEAR, TAIL, AUXILIARY POWER UNIT (APU), AND ENGINES. THE WORK FORCE CONSISTS OF 5 INSPECTORS, 3 LEAD MECHANICS, AND 24 MECHANICS; NIGHTLY SCHEDULES ARE COORDINATED BY A PLANNER. - Greater Buffalo International Airport, Maintenance Hangar, Buffalo, Erie County, NY
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kim, Minsun, E-mail: mk688@uw.edu; Stewart, Robert D.; Phillips, Mark H.
2015-11-15
Purpose: To investigate the impact of using spatiotemporal optimization, i.e., intensity-modulated spatial optimization followed by fractionation schedule optimization, to select the patient-specific fractionation schedule that maximizes the tumor biologically equivalent dose (BED) under dose constraints for multiple organs-at-risk (OARs). Methods: Spatiotemporal optimization was applied to a variety of lung tumors in a phantom geometry using a range of tumor sizes and locations. The optimal fractionation schedule for a patient using the linear-quadratic cell survival model depends on the tumor and OAR sensitivity to fraction size (α/β), the effective tumor doubling time (T{sub d}), and the size and location of tumormore » target relative to one or more OARs (dose distribution). The authors used a spatiotemporal optimization method to identify the optimal number of fractions N that maximizes the 3D tumor BED distribution for 16 lung phantom cases. The selection of the optimal fractionation schedule used equivalent (30-fraction) OAR constraints for the heart (D{sub mean} ≤ 45 Gy), lungs (D{sub mean} ≤ 20 Gy), cord (D{sub max} ≤ 45 Gy), esophagus (D{sub max} ≤ 63 Gy), and unspecified tissues (D{sub 05} ≤ 60 Gy). To assess plan quality, the authors compared the minimum, mean, maximum, and D{sub 95} of tumor BED, as well as the equivalent uniform dose (EUD) for optimized plans to conventional intensity-modulated radiation therapy plans prescribing 60 Gy in 30 fractions. A sensitivity analysis was performed to assess the effects of T{sub d} (3–100 days), tumor lag-time (T{sub k} = 0–10 days), and the size of tumors on optimal fractionation schedule. Results: Using an α/β ratio of 10 Gy, the average values of tumor max, min, mean BED, and D{sub 95} were up to 19%, 21%, 20%, and 19% larger than those from conventional prescription, depending on T{sub d} and T{sub k} used. Tumor EUD was up to 17% larger than the conventional prescription. For fast proliferating tumors with T{sub d} less than 10 days, there was no significant increase in tumor BED but the treatment course could be shortened without a loss in tumor BED. The improvement in the tumor mean BED was more pronounced with smaller tumors (p-value = 0.08). Conclusions: Spatiotemporal optimization of patient plans has the potential to significantly improve local tumor control (larger BED/EUD) of patients with a favorable geometry, such as smaller tumors with larger distances between the tumor target and nearby OAR. In patients with a less favorable geometry and for fast growing tumors, plans optimized using spatiotemporal optimization and conventional (spatial-only) optimization are equivalent (negligible differences in tumor BED/EUD). However, spatiotemporal optimization yields shorter treatment courses than conventional spatial-only optimization. Personalized, spatiotemporal optimization of treatment schedules can increase patient convenience and help with the efficient allocation of clinical resources. Spatiotemporal optimization can also help identify a subset of patients that might benefit from nonconventional (large dose per fraction) treatments that are ineligible for the current practice of stereotactic body radiation therapy.« less
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.
Lombardi, Giuseppe; Bellu, Luisa; Pambuku, Ardi; Della Puppa, Alessandro; Fiduccia, Pasquale; Farina, Miriam; D'Avella, Domenico; Zagonel, Vittorina
2016-07-01
The optimal treatment of recurrent glioblastoma (GBM) in elderly patients is unclear. Fotemustine (FTM) is a third-generation nitrosourea showing efficacy in gliomas and it has been used with different schedules in adult patients. We performed, for the first time anywhere, a mono-institutional retrospective study to analyze the clinical outcome of an alternative fotemustine schedule in elderly patients with recurrent GBM. Retrospectively, we analyzed all GBM patients 65 years or older previously treated with the combination of radiation therapy and temozolomide (TMZ), receiving an alternative FTM schedule as second-line treatment at our Oncological Center from October 2011 to October 2014 with an ECOG PS ≤ 2. FTM was administrated at 80 mg/m(2) every 2 weeks for five consecutive administrations (induction phase), and then every 4 weeks at 80 mg/m(2) as maintenance. We enrolled 44 patients, 33 males and 11 females; average age was 70 years. ECOG PS was 0-1 in 80 % of the patients. 38 patients relapsed during temozolomide (TMZ) therapy. MGMT methylation status was analyzed in 34 patients and MGMT was methylated in 53 % of the patients. The median progression free survival (PFS) and overall survival (OS) from FTM treatment was 4.1 months (95 % CI 3.1-5.2) and 7 months (95 % CI 5.2-8.4), respectively. Patients with MGMT methylated status and patients who relapsed after completing TMZ therapy had a longer PFS and OS from the beginning of FTM. Thrombocytopenia was the most frequent grade 3-4 haematological toxicity (9 %). The alternative schedule of FTM may be an active and safe treatment for elderly patients with recurrent glioblastoma, especially patients with methylated MGMT and who relapsed after completing temozolomide therapy.
A Method for Optimal Load Dispatch of a Multi-zone Power System with Zonal Exchange Constraints
NASA Astrophysics Data System (ADS)
Hazarika, Durlav; Das, Ranjay
2018-04-01
This paper presented a method for economic generation scheduling of a multi-zone power system having inter zonal operational constraints. For this purpose, the generator rescheduling for a multi area power system having inter zonal operational constraints has been represented as a two step optimal generation scheduling problem. At first, the optimal generation scheduling has been carried out for the zone having surplus or deficient generation with proper spinning reserve using co-ordination equation. The power exchange required for the deficit zones and zones having no generation are estimated based on load demand and generation for the zone. The incremental transmission loss formulas for the transmission lines participating in the power transfer process among the zones are formulated. Using these, incremental transmission loss expression in co-ordination equation, the optimal generation scheduling for the zonal exchange has been determined. Simulation is carried out on IEEE 118 bus test system to examine the applicability and validity of the method.
NASA Astrophysics Data System (ADS)
Gao, Kaizhou; Wang, Ling; Luo, Jianping; Jiang, Hua; Sadollah, Ali; Pan, Quanke
2018-06-01
In this article, scheduling and rescheduling problems with increasing processing time and new job insertion are studied for reprocessing problems in the remanufacturing process. To handle the unpredictability of reprocessing time, an experience-based strategy is used. Rescheduling strategies are applied for considering the effect of increasing reprocessing time and the new subassembly insertion. To optimize the scheduling and rescheduling objective, a discrete harmony search (DHS) algorithm is proposed. To speed up the convergence rate, a local search method is designed. The DHS is applied to two real-life cases for minimizing the maximum completion time and the mean of earliness and tardiness (E/T). These two objectives are also considered together as a bi-objective problem. Computational optimization results and comparisons show that the proposed DHS is able to solve the scheduling and rescheduling problems effectively and productively. Using the proposed approach, satisfactory optimization results can be achieved for scheduling and rescheduling on a real-life shop floor.
40 CFR 1065.303 - Summary of required calibration and verifications
Code of Federal Regulations, 2010 CFR
2010-07-01
.... THC FID optimization, and THC FID verification Optimize and determine CH4 response for THC FID analyzers: Upon initial installation and after major maintenance. Verify CH4 response for THC FID analyzers.... For THC FID analyzers: Upon initial installation, after major maintenance, and after FID optimization...
40 CFR 1065.303 - Summary of required calibration and verifications
Code of Federal Regulations, 2011 CFR
2011-07-01
.... THC FID optimization, and THC FID verification Optimize and determine CH4 response for THC FID analyzers: Upon initial installation and after major maintenance. Verify CH4 response for THC FID analyzers.... For THC FID analyzers: Upon initial installation, after major maintenance, and after FID optimization...
1988-09-01
maintenance programs. They use "a dedicated age exploration technique and actuarial analyses (31:847)" to Justify any changes to programs. RAAF. The...A066593). 8. Coffin, M.D. and C.F. Tiffany. "New Air Force Requirements for Structural Safety, Durability and Life Management," AIAA/ ASME /SAE 16th
Scheduling Earth Observing Satellites with Evolutionary Algorithms
NASA Technical Reports Server (NTRS)
Globus, Al; Crawford, James; Lohn, Jason; Pryor, Anna
2003-01-01
We hypothesize that evolutionary algorithms can effectively schedule coordinated fleets of Earth observing satellites. The constraints are complex and the bottlenecks are not well understood, a condition where evolutionary algorithms are often effective. This is, in part, because evolutionary algorithms require only that one can represent solutions, modify solutions, and evaluate solution fitness. To test the hypothesis we have developed a representative set of problems, produced optimization software (in Java) to solve them, and run experiments comparing techniques. This paper presents initial results of a comparison of several evolutionary and other optimization techniques; namely the genetic algorithm, simulated annealing, squeaky wheel optimization, and stochastic hill climbing. We also compare separate satellite vs. integrated scheduling of a two satellite constellation. While the results are not definitive, tests to date suggest that simulated annealing is the best search technique and integrated scheduling is superior.
Construction schedules slack time minimizing
NASA Astrophysics Data System (ADS)
Krzemiński, Michał
2017-07-01
The article presents two copyright models for minimizing downtime working brigades. Models have been developed for construction schedules performed using the method of work uniform. Application of flow shop models is possible and useful for the implementation of large objects, which can be divided into plots. The article also presents a condition describing gives which model should be used, as well as a brief example of optimization schedule. The optimization results confirm the legitimacy of the work on the newly-developed models.
Full glowworm swarm optimization algorithm for whole-set orders scheduling in single machine.
Yu, Zhang; Yang, Xiaomei
2013-01-01
By analyzing the characteristics of whole-set orders problem and combining the theory of glowworm swarm optimization, a new glowworm swarm optimization algorithm for scheduling is proposed. A new hybrid-encoding schema combining with two-dimensional encoding and random-key encoding is given. In order to enhance the capability of optimal searching and speed up the convergence rate, the dynamical changed step strategy is integrated into this algorithm. Furthermore, experimental results prove its feasibility and efficiency.
Nurse Scheduling by Cooperative GA with Effective Mutation Operator
NASA Astrophysics Data System (ADS)
Ohki, Makoto
In this paper, we propose an effective mutation operators for Cooperative Genetic Algorithm (CGA) to be applied to a practical Nurse Scheduling Problem (NSP). The nurse scheduling is a very difficult task, because NSP is a complex combinatorial optimizing problem for which many requirements must be considered. In real hospitals, the schedule changes frequently. The changes of the shift schedule yields various problems, for example, a fall in the nursing level. We describe a technique of the reoptimization of the nurse schedule in response to a change. The conventional CGA is superior in ability for local search by means of its crossover operator, but often stagnates at the unfavorable situation because it is inferior to ability for global search. When the optimization stagnates for long generation cycle, a searching point, population in this case, would be caught in a wide local minimum area. To escape such local minimum area, small change in a population should be required. Based on such consideration, we propose a mutation operator activated depending on the optimization speed. When the optimization stagnates, in other words, when the optimization speed decreases, the mutation yields small changes in the population. Then the population is able to escape from a local minimum area by means of the mutation. However, this mutation operator requires two well-defined parameters. This means that user have to consider the value of these parameters carefully. To solve this problem, we propose a periodic mutation operator which has only one parameter to define itself. This simplified mutation operator is effective over a wide range of the parameter value.
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.
NASA Astrophysics Data System (ADS)
Ausaf, Muhammad Farhan; Gao, Liang; Li, Xinyu
2015-12-01
For increasing the overall performance of modern manufacturing systems, effective integration of process planning and scheduling functions has been an important area of consideration among researchers. Owing to the complexity of handling process planning and scheduling simultaneously, most of the research work has been limited to solving the integrated process planning and scheduling (IPPS) problem for a single objective function. As there are many conflicting objectives when dealing with process planning and scheduling, real world problems cannot be fully captured considering only a single objective for optimization. Therefore considering multi-objective IPPS (MOIPPS) problem is inevitable. Unfortunately, only a handful of research papers are available on solving MOIPPS problem. In this paper, an optimization algorithm for solving MOIPPS problem is presented. The proposed algorithm uses a set of dispatching rules coupled with priority assignment to optimize the IPPS problem for various objectives like makespan, total machine load, total tardiness, etc. A fixed sized external archive coupled with a crowding distance mechanism is used to store and maintain the non-dominated solutions. To compare the results with other algorithms, a C-matric based method has been used. Instances from four recent papers have been solved to demonstrate the effectiveness of the proposed algorithm. The experimental results show that the proposed method is an efficient approach for solving the MOIPPS problem.
Atmospheric Science Data Center
2013-03-08
... Features ASDC's RSS feed with highlights about Earth Science Data at NASA Langley Research Center ASDC Scheduled ... about maintenance About RSS What is RSS? RSS (Really Simple Syndication, or Rich Site Summary) ...
Turnaround Time Modeling for Conceptual Rocket Engines
NASA Technical Reports Server (NTRS)
Nix, Michael; Staton, Eric J.
2004-01-01
Recent years have brought about a paradigm shift within NASA and the Space Launch Community regarding the performance of conceptual design. Reliability, maintainability, supportability, and operability are no longer effects of design; they have moved to the forefront and are affecting design. A primary focus of this shift has been a planned decrease in vehicle turnaround time. Potentials for instituting this decrease include attacking the issues of removing, refurbishing, and replacing the engines after each flight. less, it is important to understand the operational affects of an engine on turnaround time, ground support personnel and equipment. One tool for visualizing this relationship involves the creation of a Discrete Event Simulation (DES). A DES model can be used to run a series of trade studies to determine if the engine is meeting its requirements, and, if not, what can be altered to bring it into compliance. Using DES, it is possible to look at the ways in which labor requirements, parallel maintenance versus serial maintenance, and maintenance scheduling affect the overall turnaround time. A detailed DES model of the Space Shuttle Main Engines (SSME) has been developed. Trades may be performed using the SSME Processing Model to see where maintenance bottlenecks occur, what the benefits (if any) are of increasing the numbers of personnel, or the number and location of facilities, in addition to trades previously mentioned, all with the goal of optimizing the operational turnaround time and minimizing operational cost. The SSME Processing Model was developed in such a way that it can easily be used as a foundation for developing DES models of other operational or developmental reusable engines. Performing a DES on a developmental engine during the conceptual phase makes it easier to affect the design and make changes to bring about a decrease in turnaround time and costs.
A proven approach for more effective software development and maintenance
NASA Technical Reports Server (NTRS)
Pajerski, Rose; Hall, Dana; Sinclair, Craig
1994-01-01
Modern space flight mission operations and associated ground data systems are increasingly dependent upon reliable, quality software. Critical functions such as command load preparation, health and status monitoring, communications link scheduling and conflict resolution, and transparent gateway protocol conversion are routinely performed by software. Given budget constraints and the ever increasing capabilities of processor technology, the next generation of control centers and data systems will be even more dependent upon software across all aspects of performance. A key challenge now is to implement improved engineering, management, and assurance processes for the development and maintenance of that software; processes that cost less, yield higher quality products, and that self-correct for continual improvement evolution. The NASA Goddard Space Flight Center has a unique experience base that can be readily tapped to help solve the software challenge. Over the past eighteen years, the Software Engineering Laboratory within the code 500 Flight Dynamics Division has evolved a software development and maintenance methodology that accommodates the unique characteristics of an organization while optimizing and continually improving the organization's software capabilities. This methodology relies upon measurement, analysis, and feedback much analogous to that of control loop systems. It is an approach with a time-tested track record proven through repeated applications across a broad range of operational software development and maintenance projects. This paper describes the software improvement methodology employed by the Software Engineering Laboratory, and how it has been exploited within the Flight Dynamics Division with GSFC Code 500. Examples of specific improvement in the software itself and its processes are presented to illustrate the effectiveness of the methodology. Finally, the initial findings are given when this methodology was applied across the mission operations and ground data systems software domains throughout Code 500.
See, William A
2014-11-01
To explore the necessity of maintenance, efficacy of low-dose and superiority of various combination therapies of Bacillus Calmette-Guérin (BCG) in treatment of superficial bladder cancer (BCa). Comprehensive searches of electronic databases (PubMed, Embase, and the Cochrane Library), were performed, then a systematic review and cumulative meta-analysis of 21 randomized, controlled trials (RCTs) and 9 retrospective comparative studies were carried out according to, predefined inclusion criteria. Significantly better recurrence-free survivals (RFS) were observed respectively in patients who received BCG maintenance, standard-dose and BCG plus epirubicin therapy comparing to those received induction, low-dose and BCG alone. BCG maintenance therapy was also associated with significantly better progression-free survival (PFS), but there were more incidences of adverse events. Pooled results showed no remarkable advantage of BCG combined with Mitomycin C or with interferon α-2b in improving oncologic outcomes. Sensitivity-analyses stratified by study-design and tumor stage led to very similar overall results and often to a decrease of the between-study heterogeneity. Our data confirmed that non-RCT only affected strength rather than direction of the overall results. All patients with superficial BCa should be encouraged to accept BCG maintenance therapy with standard-dose if well tolerated. Patients can benefit from BCG combined with epirubicin but not from BCG combined with Mitomycin C or interferon α-2b. Copyright © 2014 Elsevier Inc. All rights reserved.
Transmission overhaul estimates for partial and full replacement at repair
NASA Technical Reports Server (NTRS)
Savage, M.; Lewicki, D. G.
1991-01-01
Timely transmission overhauls increase in-flight service reliability greater than the calculated design reliabilities of the individual aircraft transmission components. Although necessary for aircraft safety, transmission overhauls contribute significantly to aircraft expense. Predictions of a transmission's maintenance needs at the design stage should enable the development of more cost effective and reliable transmissions in the future. The frequency is estimated of overhaul along with the number of transmissions or components needed to support the overhaul schedule. Two methods based on the two parameter Weibull statistical distribution for component life are used to estimate the time between transmission overhauls. These methods predict transmission lives for maintenance schedules which repair the transmission with a complete system replacement or repair only failed components of the transmission. An example illustrates the methods.
An Expert System for Aviation Squadron Flight Scheduling
1991-09-01
SCHEDULING A. OVERVIEW A flight schedule is an organization’s plan to accomplish specific missions with its available resources. It details the mission...schedule for every 24 hour period, and will occasionally write a weekly flight schedule for long range planning purposes. The flight schedule is approved...requirements, and 11 aircraft, trainer, and aircrew availability to formulate the flight schedule. It basically is a plan to optimize the squadron’s resources
WFIRST: Exoplanet Target Selection and Scheduling with Greedy Optimization
NASA Astrophysics Data System (ADS)
Keithly, Dean; Garrett, Daniel; Delacroix, Christian; Savransky, Dmitry
2018-01-01
We present target selection and scheduling algorithms for missions with direct imaging of exoplanets, and the Wide Field Infrared Survey Telescope (WFIRST) in particular, which will be equipped with a coronagraphic instrument (CGI). Optimal scheduling of CGI targets can maximize the expected value of directly imaged exoplanets (completeness). Using target completeness as a reward metric and integration time plus overhead time as a cost metric, we can maximize the sum completeness for a mission with a fixed duration. We optimize over these metrics to create a list of target stars using a greedy optimization algorithm based off altruistic yield optimization (AYO) under ideal conditions. We simulate full missions using EXOSIMS by observing targets in this list for their predetermined integration times. In this poster, we report the theoretical maximum sum completeness, mean number of detected exoplanets from Monte Carlo simulations, and the ideal expected value of the simulated missions.
NASA Technical Reports Server (NTRS)
Wang, Yeou-Fang; Baldwin, John
2007-01-01
TIGRAS is client-side software, which provides tracking-station equipment planning, allocation, and scheduling services to the DSMS (Deep Space Mission System). TIGRAS provides functions for schedulers to coordinate the DSN (Deep Space Network) antenna usage time and to resolve the resource usage conflicts among tracking passes, antenna calibrations, maintenance, and system testing activities. TIGRAS provides a fully integrated multi-pane graphical user interface for all scheduling operations. This is a great improvement over the legacy VAX VMS command line user interface. TIGRAS has the capability to handle all DSN resource scheduling aspects from long-range to real time. TIGRAS assists NASA mission operations for DSN tracking of station equipment resource request processes from long-range load forecasts (ten years or longer), to midrange, short-range, and real-time (less than one week) emergency tracking plan changes. TIGRAS can be operated by NASA mission operations worldwide to make schedule requests for the DSN station equipment.
NASA Technical Reports Server (NTRS)
Brown, Aaron J.
2011-01-01
Orbit maintenance is the series of burns performed during a mission to ensure the orbit satisfies mission constraints. Low-altitude missions often require non-trivial orbit maintenance Delta V due to sizable orbital perturbations and minimum altitude thresholds. A strategy is presented for minimizing this Delta V using impulsive burn parameter optimization. An initial estimate for the burn parameters is generated by considering a feasible solution to the orbit maintenance problem. An low-lunar orbit example demonstrates the Delta V savings from the feasible solution to the optimal solution. The strategy s extensibility to more complex missions is discussed, as well as the limitations of its use.
2006-03-01
Requirements for the Degree of Master of Science in Logistics Management Dale L. Overholts II, BS Capt, USAF March 2006 APPROVED...distance (e. g . , travel time or cost, demand satisfaction) is fundamental to such problems” (Current et al, 2002:86). The set covering location... the total number of scheduled launch facilities, can be found in Appendix F. Appendix G provides detailed information regarding the impacts of
Permutation flow-shop scheduling problem to optimize a quadratic objective function
NASA Astrophysics Data System (ADS)
Ren, Tao; Zhao, Peng; Zhang, Da; Liu, Bingqian; Yuan, Huawei; Bai, Danyu
2017-09-01
A flow-shop scheduling model enables appropriate sequencing for each job and for processing on a set of machines in compliance with identical processing orders. The objective is to achieve a feasible schedule for optimizing a given criterion. Permutation is a special setting of the model in which the processing order of the jobs on the machines is identical for each subsequent step of processing. This article addresses the permutation flow-shop scheduling problem to minimize the criterion of total weighted quadratic completion time. With a probability hypothesis, the asymptotic optimality of the weighted shortest processing time schedule under a consistency condition (WSPT-CC) is proven for sufficiently large-scale problems. However, the worst case performance ratio of the WSPT-CC schedule is the square of the number of machines in certain situations. A discrete differential evolution algorithm, where a new crossover method with multiple-point insertion is used to improve the final outcome, is presented to obtain high-quality solutions for moderate-scale problems. A sequence-independent lower bound is designed for pruning in a branch-and-bound algorithm for small-scale problems. A set of random experiments demonstrates the performance of the lower bound and the effectiveness of the proposed algorithms.
NASA Technical Reports Server (NTRS)
Phillips, K.
1976-01-01
A mathematical model for job scheduling in a specified context is presented. The model uses both linear programming and combinatorial methods. While designed with a view toward optimization of scheduling of facility and plant operations at the Deep Space Communications Complex, the context is sufficiently general to be widely applicable. The general scheduling problem including options for scheduling objectives is discussed and fundamental parameters identified. Mathematical algorithms for partitioning problems germane to scheduling are presented.
ERIC Educational Resources Information Center
Kennedy, Mike
2003-01-01
Describes how facilities-management systems use technology to help schools and universities operate their buildings more efficiently, reduce energy consumption, manage inventory more accurately, keep track of supplies and maintenance schedules, and save money. (EV)
More Bang for the Buck: Integrating Green Infrastructure into Existing Public Works Projects
shares lessons learned from municipal and county officials experienced in coordinating green infrastructure applications with scheduled street maintenance, park improvements, and projects on public sites.
Crew interface specifications preparation for in-flight maintenance and stowage functions
NASA Technical Reports Server (NTRS)
Parker, F. W.; Carlton, B. E.
1972-01-01
The findings and data products developed during the Phase 2 crew interface specification study are presented. Five new NASA general specifications were prepared: operations location coding system for crew interfaces; loose equipment and stowage management requirements; loose equipment and stowage data base information requirements; spacecraft loose equipment stowage drawing requirements; and inflight stowage management data requirements. Additional data was developed defining inflight maintenance processes and related data concepts for inflight troubleshooting, remove/repair/replace and scheduled maintenance activities. The process of maintenance task and equipment definition during spacecraft design and development was also defined and related data concepts were identified for futher development into formal NASA specifications during future follow-on study phases of the contract.
Flight control electronics reliability/maintenance study
NASA Technical Reports Server (NTRS)
Dade, W. W.; Edwards, R. H.; Katt, G. T.; Mcclellan, K. L.; Shomber, H. A.
1977-01-01
Collection and analysis of data are reported that concern the reliability and maintenance experience of flight control system electronics currently in use on passenger carrying jet aircraft. Two airlines B-747 airplane fleets were analyzed to assess the component reliability, system functional reliability, and achieved availability of the CAT II configuration flight control system. Also assessed were the costs generated by this system in the categories of spare equipment, schedule irregularity, and line and shop maintenance. The results indicate that although there is a marked difference in the geographic location and route pattern between the airlines studied, there is a close similarity in the reliability and the maintenance costs associated with the flight control electronics.
Scheduling optimization of design stream line for production research and development projects
NASA Astrophysics Data System (ADS)
Liu, Qinming; Geng, Xiuli; Dong, Ming; Lv, Wenyuan; Ye, Chunming
2017-05-01
In a development project, efficient design stream line scheduling is difficult and important owing to large design imprecision and the differences in the skills and skill levels of employees. The relative skill levels of employees are denoted as fuzzy numbers. Multiple execution modes are generated by scheduling different employees for design tasks. An optimization model of a design stream line scheduling problem is proposed with the constraints of multiple executive modes, multi-skilled employees and precedence. The model considers the parallel design of multiple projects, different skills of employees, flexible multi-skilled employees and resource constraints. The objective function is to minimize the duration and tardiness of the project. Moreover, a two-dimensional particle swarm algorithm is used to find the optimal solution. To illustrate the validity of the proposed method, a case is examined in this article, and the results support the feasibility and effectiveness of the proposed model and algorithm.
Discrete Optimization Model for Vehicle Routing Problem with Scheduling Side Cosntraints
NASA Astrophysics Data System (ADS)
Juliandri, Dedy; Mawengkang, Herman; Bu'ulolo, F.
2018-01-01
Vehicle Routing Problem (VRP) is an important element of many logistic systems which involve routing and scheduling of vehicles from a depot to a set of customers node. This is a hard combinatorial optimization problem with the objective to find an optimal set of routes used by a fleet of vehicles to serve the demands a set of customers It is required that these vehicles return to the depot after serving customers’ demand. The problem incorporates time windows, fleet and driver scheduling, pick-up and delivery in the planning horizon. The goal is to determine the scheduling of fleet and driver and routing policies of the vehicles. The objective is to minimize the overall costs of all routes over the planning horizon. We model the problem as a linear mixed integer program. We develop a combination of heuristics and exact method for solving the model.
NASA Astrophysics Data System (ADS)
Wang, Ji-Bo; Wang, Ming-Zheng; Ji, Ping
2012-05-01
In this article, we consider a single machine scheduling problem with a time-dependent learning effect and deteriorating jobs. By the effects of time-dependent learning and deterioration, we mean that the job processing time is defined by a function of its starting time and total normal processing time of jobs in front of it in the sequence. The objective is to determine an optimal schedule so as to minimize the total completion time. This problem remains open for the case of -1 < a < 0, where a denotes the learning index; we show that an optimal schedule of the problem is V-shaped with respect to job normal processing times. Three heuristic algorithms utilising the V-shaped property are proposed, and computational experiments show that the last heuristic algorithm performs effectively and efficiently in obtaining near-optimal solutions.
Optimal manpower allocation in aircraft line maintenance (Case in GMF AeroAsia)
NASA Astrophysics Data System (ADS)
Puteri, V. E.; Yuniaristanto, Hisjam, M.
2017-11-01
This paper presents a mathematical modeling to find the optimal manpower allocation in an aircraft line maintenance. This research focuses on assigning the number and type of manpower that allocated to each service. This study considers the licenced worker or Aircraft Maintenance Engineer Licence (AMEL) and non licenced worker or Aircraft Maintenance Technician (AMT). In this paper, we also consider the relationship of each station in terms of the possibility to transfer the manpower among them. The optimization model considers the number of manpowers needed for each service and the requirement of AMEL worker. This paper aims to determine the optimal manpower allocation using the mathematical modeling. The objective function of the model is to find the minimum employee expenses. The model was solved using the ILOG CPLEX software. The results show that the manpower allocation can meet the manpower need and the all load can be served.
Cloud computing task scheduling strategy based on differential evolution and ant colony optimization
NASA Astrophysics Data System (ADS)
Ge, Junwei; Cai, Yu; Fang, Yiqiu
2018-05-01
This paper proposes a task scheduling strategy DEACO based on the combination of Differential Evolution (DE) and Ant Colony Optimization (ACO), aiming at the single problem of optimization objective in cloud computing task scheduling, this paper combines the shortest task completion time, cost and load balancing. DEACO uses the solution of the DE to initialize the initial pheromone of ACO, reduces the time of collecting the pheromone in ACO in the early, and improves the pheromone updating rule through the load factor. The proposed algorithm is simulated on cloudsim, and compared with the min-min and ACO. The experimental results show that DEACO is more superior in terms of time, cost, and load.
2018-01-01
In this work, a multi-hop string network with a single sink node is analyzed. A periodic optimal scheduling for TDMA operation that considers the characteristic long propagation delay of the underwater acoustic channel is presented. This planning of transmissions is obtained with the help of a new geometrical method based on a 2D lattice in the space-time domain. In order to evaluate the performance of this optimal scheduling, two service policies have been compared: FIFO and Round-Robin. Simulation results, including achievable throughput, packet delay, and queue length, are shown. The network fairness has also been quantified with the Gini index. PMID:29462966
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.
Scheduling IT Staff at a Bank: A Mathematical Programming Approach
Labidi, M.; Mrad, M.; Gharbi, A.; Louly, M. A.
2014-01-01
We address a real-world optimization problem: the scheduling of a Bank Information Technologies (IT) staff. This problem can be defined as the process of constructing optimized work schedules for staff. In a general sense, it requires the allocation of suitably qualified staff to specific shifts to meet the demands for services of an organization while observing workplace regulations and attempting to satisfy individual work preferences. A monthly shift schedule is prepared to determine the shift duties of each staff considering shift coverage requirements, seniority-based workload rules, and staff work preferences. Due to the large number of conflicting constraints, a multiobjective programming model has been proposed to automate the schedule generation process. The suggested mathematical model has been implemented using Lingo software. The results indicate that high quality solutions can be obtained within a few seconds compared to the manually prepared schedules. PMID:24772032
Scheduling IT staff at a bank: a mathematical programming approach.
Labidi, M; Mrad, M; Gharbi, A; Louly, M A
2014-01-01
We address a real-world optimization problem: the scheduling of a Bank Information Technologies (IT) staff. This problem can be defined as the process of constructing optimized work schedules for staff. In a general sense, it requires the allocation of suitably qualified staff to specific shifts to meet the demands for services of an organization while observing workplace regulations and attempting to satisfy individual work preferences. A monthly shift schedule is prepared to determine the shift duties of each staff considering shift coverage requirements, seniority-based workload rules, and staff work preferences. Due to the large number of conflicting constraints, a multiobjective programming model has been proposed to automate the schedule generation process. The suggested mathematical model has been implemented using Lingo software. The results indicate that high quality solutions can be obtained within a few seconds compared to the manually prepared schedules.
NASA Astrophysics Data System (ADS)
Divecha, Mia S.; Derby, Jeffrey J.
2017-12-01
Historically, the melt growth of II-VI crystals has benefitted from the application of the accelerated crucible rotation technique (ACRT). Here, we employ a comprehensive numerical model to assess the impact of two ACRT schedules designed for a cadmium zinc telluride growth system per the classical recommendations of Capper and co-workers. The ;flow maximizing; ACRT schedule, with higher rotation, effectively mixes the solutal field in the melt but does not reduce supercooling adjacent to the growth interface. The ACRT schedule derived for stable Ekman flow, with lower rotation, proves more effective in reducing supercooling and promoting stable growth. These counterintuitive results highlight the need for more comprehensive studies on the optimization of ACRT schedules for specific growth systems and for desired growth outcomes.
Carbohydrates for Soccer: A Focus on Skilled Actions and Half-Time Practices
Hills, Samuel P.; Russell, Mark
2017-01-01
Carbohydrate consumption is synonymous with soccer performance due to the established effects on endogenous energy store preservation, and physical capacity maintenance. For performance-enhancement purposes, exogenous energy consumption (in the form of drinks, bars, gels and snacks) is recommended on match-day; specifically, before and during match-play. Akin to the demands of soccer, limited opportunities exist to consume carbohydrates outside of scheduled breaks in competition, such as at half-time. The link between cognitive function and blood glucose availability suggests that carbohydrates may influence decision-making and technical proficiency (e.g., soccer skills). However, relatively few reviews have focused on technical, as opposed to physical, performance while also addressing the practicalities associated with carbohydrate consumption when limited in-play feeding opportunities exist. Transient physiological responses associated with reductions in activity prevalent in scheduled intra-match breaks (e.g., half-time) likely have important consequences for practitioners aiming to optimize match-day performance. Accordingly, this review evaluated novel developments in soccer literature regarding (1) the ergogenic properties of carbohydrates for skill performance; and (2) novel considerations concerning exogenous energy provision during half-time. Recommendations are made to modify half-time practices in an aim to enhance subsequent performance. Viable future research opportunities exist regarding a deeper insight into carbohydrate provision on match-day. PMID:29295583
A review on prognostics and health monitoring of Li-ion battery
NASA Astrophysics Data System (ADS)
Zhang, Jingliang; Lee, Jay
2011-08-01
The functionality and reliability of Li-ion batteries as major energy storage devices have received more and more attention from a wide spectrum of stakeholders, including federal/state policymakers, business leaders, technical researchers, environmental groups and the general public. Failures of Li-ion battery not only result in serious inconvenience and enormous replacement/repair costs, but also risk catastrophic consequences such as explosion due to overheating and short circuiting. In order to prevent severe failures from occurring, and to optimize Li-ion battery maintenance schedules, breakthroughs in prognostics and health monitoring of Li-ion batteries, with an emphasis on fault detection, correction and remaining-useful-life prediction, must be achieved. This paper reviews various aspects of recent research and developments in Li-ion battery prognostics and health monitoring, and summarizes the techniques, algorithms and models used for state-of-charge (SOC) estimation, current/voltage estimation, capacity estimation and remaining-useful-life (RUL) prediction.
24 CFR 886.105 - Content of application; Disclosure.
Code of Federal Regulations, 2011 CFR
2011-04-01
...) For projects having a history of financial default, financial difficulties or deferred maintenance, a plan and a schedule for remedying such defaulted or deferred obligations; (e) Total number of units by...
24 CFR 886.105 - Content of application; Disclosure.
Code of Federal Regulations, 2014 CFR
2014-04-01
...) For projects having a history of financial default, financial difficulties or deferred maintenance, a plan and a schedule for remedying such defaulted or deferred obligations; (e) Total number of units by...
24 CFR 886.105 - Content of application; Disclosure.
Code of Federal Regulations, 2013 CFR
2013-04-01
...) For projects having a history of financial default, financial difficulties or deferred maintenance, a plan and a schedule for remedying such defaulted or deferred obligations; (e) Total number of units by...
24 CFR 886.105 - Content of application; Disclosure.
Code of Federal Regulations, 2012 CFR
2012-04-01
...) For projects having a history of financial default, financial difficulties or deferred maintenance, a plan and a schedule for remedying such defaulted or deferred obligations; (e) Total number of units by...
Online stochastic optimization of radiotherapy patient scheduling.
Legrain, Antoine; Fortin, Marie-Andrée; Lahrichi, Nadia; Rousseau, Louis-Martin
2015-06-01
The effective management of a cancer treatment facility for radiation therapy depends mainly on optimizing the use of the linear accelerators. In this project, we schedule patients on these machines taking into account their priority for treatment, the maximum waiting time before the first treatment, and the treatment duration. We collaborate with the Centre Intégré de Cancérologie de Laval to determine the best scheduling policy. Furthermore, we integrate the uncertainty related to the arrival of patients at the center. We develop a hybrid method combining stochastic optimization and online optimization to better meet the needs of central planning. We use information on the future arrivals of patients to provide an accurate picture of the expected utilization of resources. Results based on real data show that our method outperforms the policies typically used in treatment centers.
NASA Astrophysics Data System (ADS)
Kumar, Girish; Jain, Vipul; Gandhi, O. P.
2018-03-01
Maintenance helps to extend equipment life by improving its condition and avoiding catastrophic failures. Appropriate model or mechanism is, thus, needed to quantify system availability vis-a-vis a given maintenance strategy, which will assist in decision-making for optimal utilization of maintenance resources. This paper deals with semi-Markov process (SMP) modeling for steady state availability analysis of mechanical systems that follow condition-based maintenance (CBM) and evaluation of optimal condition monitoring interval. The developed SMP model is solved using two-stage analytical approach for steady-state availability analysis of the system. Also, CBM interval is decided for maximizing system availability using Genetic Algorithm approach. The main contribution of the paper is in the form of a predictive tool for system availability that will help in deciding the optimum CBM policy. The proposed methodology is demonstrated for a centrifugal pump.
Microgrid Optimal Scheduling With Chance-Constrained Islanding Capability
Liu, Guodong; Starke, Michael R.; Xiao, B.; ...
2017-01-13
To facilitate the integration of variable renewable generation and improve the resilience of electricity sup-ply in a microgrid, this paper proposes an optimal scheduling strategy for microgrid operation considering constraints of islanding capability. A new concept, probability of successful islanding (PSI), indicating the probability that a microgrid maintains enough spinning reserve (both up and down) to meet local demand and accommodate local renewable generation after instantaneously islanding from the main grid, is developed. The PSI is formulated as mixed-integer linear program using multi-interval approximation taking into account the probability distributions of forecast errors of wind, PV and load. With themore » goal of minimizing the total operating cost while preserving user specified PSI, a chance-constrained optimization problem is formulated for the optimal scheduling of mirogrids and solved by mixed integer linear programming (MILP). Numerical simulations on a microgrid consisting of a wind turbine, a PV panel, a fuel cell, a micro-turbine, a diesel generator and a battery demonstrate the effectiveness of the proposed scheduling strategy. Lastly, we verify the relationship between PSI and various factors.« less
Idris, Hajara; Junaidu, Sahalu B.; Adewumi, Aderemi O.
2017-01-01
The Grid scheduler, schedules user jobs on the best available resource in terms of resource characteristics by optimizing job execution time. Resource failure in Grid is no longer an exception but a regular occurring event as resources are increasingly being used by the scientific community to solve computationally intensive problems which typically run for days or even months. It is therefore absolutely essential that these long-running applications are able to tolerate failures and avoid re-computations from scratch after resource failure has occurred, to satisfy the user’s Quality of Service (QoS) requirement. Job Scheduling with Fault Tolerance in Grid Computing using Ant Colony Optimization is proposed to ensure that jobs are executed successfully even when resource failure has occurred. The technique employed in this paper, is the use of resource failure rate, as well as checkpoint-based roll back recovery strategy. Check-pointing aims at reducing the amount of work that is lost upon failure of the system by immediately saving the state of the system. A comparison of the proposed approach with an existing Ant Colony Optimization (ACO) algorithm is discussed. The experimental results of the implemented Fault Tolerance scheduling algorithm show that there is an improvement in the user’s QoS requirement over the existing ACO algorithm, which has no fault tolerance integrated in it. The performance evaluation of the two algorithms was measured in terms of the three main scheduling performance metrics: makespan, throughput and average turnaround time. PMID:28545075
Mousavi, Maryam; Yap, Hwa Jen; Musa, Siti Nurmaya; Tahriri, Farzad; Md Dawal, Siti Zawiah
2017-01-01
Flexible manufacturing system (FMS) enhances the firm's flexibility and responsiveness to the ever-changing customer demand by providing a fast product diversification capability. Performance of an FMS is highly dependent upon the accuracy of scheduling policy for the components of the system, such as automated guided vehicles (AGVs). An AGV as a mobile robot provides remarkable industrial capabilities for material and goods transportation within a manufacturing facility or a warehouse. Allocating AGVs to tasks, while considering the cost and time of operations, defines the AGV scheduling process. Multi-objective scheduling of AGVs, unlike single objective practices, is a complex and combinatorial process. In the main draw of the research, a mathematical model was developed and integrated with evolutionary algorithms (genetic algorithm (GA), particle swarm optimization (PSO), and hybrid GA-PSO) to optimize the task scheduling of AGVs with the objectives of minimizing makespan and number of AGVs while considering the AGVs' battery charge. Assessment of the numerical examples' scheduling before and after the optimization proved the applicability of all the three algorithms in decreasing the makespan and AGV numbers. The hybrid GA-PSO produced the optimum result and outperformed the other two algorithms, in which the mean of AGVs operation efficiency was found to be 69.4, 74, and 79.8 percent in PSO, GA, and hybrid GA-PSO, respectively. Evaluation and validation of the model was performed by simulation via Flexsim software.
Yap, Hwa Jen; Musa, Siti Nurmaya; Tahriri, Farzad; Md Dawal, Siti Zawiah
2017-01-01
Flexible manufacturing system (FMS) enhances the firm’s flexibility and responsiveness to the ever-changing customer demand by providing a fast product diversification capability. Performance of an FMS is highly dependent upon the accuracy of scheduling policy for the components of the system, such as automated guided vehicles (AGVs). An AGV as a mobile robot provides remarkable industrial capabilities for material and goods transportation within a manufacturing facility or a warehouse. Allocating AGVs to tasks, while considering the cost and time of operations, defines the AGV scheduling process. Multi-objective scheduling of AGVs, unlike single objective practices, is a complex and combinatorial process. In the main draw of the research, a mathematical model was developed and integrated with evolutionary algorithms (genetic algorithm (GA), particle swarm optimization (PSO), and hybrid GA-PSO) to optimize the task scheduling of AGVs with the objectives of minimizing makespan and number of AGVs while considering the AGVs’ battery charge. Assessment of the numerical examples’ scheduling before and after the optimization proved the applicability of all the three algorithms in decreasing the makespan and AGV numbers. The hybrid GA-PSO produced the optimum result and outperformed the other two algorithms, in which the mean of AGVs operation efficiency was found to be 69.4, 74, and 79.8 percent in PSO, GA, and hybrid GA-PSO, respectively. Evaluation and validation of the model was performed by simulation via Flexsim software. PMID:28263994
Imbs, Diane-Charlotte; El Cheikh, Raouf; Boyer, Arnaud; Ciccolini, Joseph; Mascaux, Céline; Lacarelle, Bruno; Barlesi, Fabrice; Barbolosi, Dominique; Benzekry, Sébastien
2018-01-01
Concomitant administration of bevacizumab and pemetrexed-cisplatin is a common treatment for advanced nonsquamous non-small cell lung cancer (NSCLC). Vascular normalization following bevacizumab administration may transiently enhance drug delivery, suggesting improved efficacy with sequential administration. To investigate optimal scheduling, we conducted a study in NSCLC-bearing mice. First, experiments demonstrated improved efficacy when using sequential vs. concomitant scheduling of bevacizumab and chemotherapy. Combining this data with a mathematical model of tumor growth under therapy accounting for the normalization effect, we predicted an optimal delay of 2.8 days between bevacizumab and chemotherapy. This prediction was confirmed experimentally, with reduced tumor growth of 38% as compared to concomitant scheduling, and prolonged survival (74 vs. 70 days). Alternate sequencing of 8 days failed in achieving a similar increase in efficacy, thus emphasizing the utility of modeling support to identify optimal scheduling. The model could also be a useful tool in the clinic to personally tailor regimen sequences. © 2017 The Authors CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals, Inc. on behalf of American Society for Clinical Pharmacology and Therapeutics.
A derived heuristics based multi-objective optimization procedure for micro-grid scheduling
NASA Astrophysics Data System (ADS)
Li, Xin; Deb, Kalyanmoy; Fang, Yanjun
2017-06-01
With the availability of different types of power generators to be used in an electric micro-grid system, their operation scheduling as the load demand changes with time becomes an important task. Besides satisfying load balance constraints and the generator's rated power, several other practicalities, such as limited availability of grid power and restricted ramping of power output from generators, must all be considered during the operation scheduling process, which makes it difficult to decide whether the optimization results are accurate and satisfactory. In solving such complex practical problems, heuristics-based customized optimization algorithms are suggested. However, due to nonlinear and complex interactions of variables, it is difficult to come up with heuristics in such problems off-hand. In this article, a two-step strategy is proposed in which the first task deciphers important heuristics about the problem and the second task utilizes the derived heuristics to solve the original problem in a computationally fast manner. Specifically, the specific operation scheduling is considered from a two-objective (cost and emission) point of view. The first task develops basic and advanced level knowledge bases offline from a series of prior demand-wise optimization runs and then the second task utilizes them to modify optimized solutions in an application scenario. Results on island and grid connected modes and several pragmatic formulations of the micro-grid operation scheduling problem clearly indicate the merit of the proposed two-step procedure.
An Optimal Schedule for Urban Road Network Repair Based on the Greedy Algorithm
Lu, Guangquan; Xiong, Ying; Wang, Yunpeng
2016-01-01
The schedule of urban road network recovery caused by rainstorms, snow, and other bad weather conditions, traffic incidents, and other daily events is essential. However, limited studies have been conducted to investigate this problem. We fill this research gap by proposing an optimal schedule for urban road network repair with limited repair resources based on the greedy algorithm. Critical links will be given priority in repair according to the basic concept of the greedy algorithm. In this study, the link whose restoration produces the ratio of the system-wide travel time of the current network to the worst network is the minimum. We define such a link as the critical link for the current network. We will re-evaluate the importance of damaged links after each repair process is completed. That is, the critical link ranking will be changed along with the repair process because of the interaction among links. We repair the most critical link for the specific network state based on the greedy algorithm to obtain the optimal schedule. The algorithm can still quickly obtain an optimal schedule even if the scale of the road network is large because the greedy algorithm can reduce computational complexity. We prove that the problem can obtain the optimal solution using the greedy algorithm in theory. The algorithm is also demonstrated in the Sioux Falls network. The problem discussed in this paper is highly significant in dealing with urban road network restoration. PMID:27768732
Hannan, M A; Akhtar, Mahmuda; Begum, R A; Basri, H; Hussain, A; Scavino, Edgar
2018-01-01
Waste collection widely depends on the route optimization problem that involves a large amount of expenditure in terms of capital, labor, and variable operational costs. Thus, the more waste collection route is optimized, the more reduction in different costs and environmental effect will be. This study proposes a modified particle swarm optimization (PSO) algorithm in a capacitated vehicle-routing problem (CVRP) model to determine the best waste collection and route optimization solutions. In this study, threshold waste level (TWL) and scheduling concepts are applied in the PSO-based CVRP model under different datasets. The obtained results from different datasets show that the proposed algorithmic CVRP model provides the best waste collection and route optimization in terms of travel distance, total waste, waste collection efficiency, and tightness at 70-75% of TWL. The obtained results for 1 week scheduling show that 70% of TWL performs better than all node consideration in terms of collected waste, distance, tightness, efficiency, fuel consumption, and cost. The proposed optimized model can serve as a valuable tool for waste collection and route optimization toward reducing socioeconomic and environmental impacts. Copyright © 2017 Elsevier Ltd. All rights reserved.
40 CFR 86.428-80 - Maintenance, scheduled; test vehicles.
Code of Federal Regulations, 2011 CFR
2011-07-01
... necessary. For example, piston and cylinder replacement caused by piston seizure which results in the vehicle being inoperative; or in the case of two-stroke engines, decarbonization, the need for which is...
40 CFR 86.428-80 - Maintenance, scheduled; test vehicles.
Code of Federal Regulations, 2012 CFR
2012-07-01
... necessary. For example, piston and cylinder replacement caused by piston seizure which results in the vehicle being inoperative; or in the case of two-stroke engines, decarbonization, the need for which is...
40 CFR 86.428-80 - Maintenance, scheduled; test vehicles.
Code of Federal Regulations, 2010 CFR
2010-07-01
... necessary. For example, piston and cylinder replacement caused by piston seizure which results in the vehicle being inoperative; or in the case of two-stroke engines, decarbonization, the need for which is...
40 CFR 86.428-80 - Maintenance, scheduled; test vehicles.
Code of Federal Regulations, 2014 CFR
2014-07-01
... necessary. For example, piston and cylinder replacement caused by piston seizure which results in the vehicle being inoperative; or in the case of two-stroke engines, decarbonization, the need for which is...
DOE Office of Scientific and Technical Information (OSTI.GOV)
2016-02-10
The software was created in the process of developing a system known as the Smart Monitoring and Diagnostic System (SMDS) for packaged air conditioners and heat pumps used on commercial buildings (known as RTUs). The SMDS provides automated remote monitoring and detection of performance degradation and faults in these RTUs and could increase the awareness by building owners and maintenance providers of the condition of the equipment, the cost of operating it in degraded condition, and the quality of maintenance and repair service when it is performed. The SMDS provides these capabilities and would enable conditioned-based maintenance rather than themore » reactive and schedule-based preventive maintenance commonly used today, when maintenance of RTUs is done at all. Improved maintenance would help ensure persistent peak operating efficiencies, reducing energy consumption by an estimated 10% to 30%.« less
Planification de la maintenance d'un parc de turbines-alternateurs par programmation mathematique
NASA Astrophysics Data System (ADS)
Aoudjit, Hakim
A growing number of Hydro-Quebec's hydro generators are at the end of their useful life and maintenance managers fear to face a number of overhauls exceeding what can be handled. Maintenance crews and budgets are limited and these withdrawals may take up to a full year and mobilize significant resources in addition to the loss of electricity production. In addition, increased export sales forecasts and severe production patterns are expected to speed up wear that can lead to halting many units at the same time. Currently, expert judgment is at the heart of withdrawals which rely primarily on periodic inspections and in-situ measurements and the results are sent to the maintenance planning team who coordinate all the withdrawals decisions. The degradations phenomena taking place is random in nature and the prediction capability of wear using only inspections is limited to short-term at best. A long term planning of major overhauls is sought by managers for the sake of justifying and rationalizing budgets and resources. The maintenance managers are able to provide a huge amount of data. Among them, is the hourly production of each unit for several years, the repairs history on each part of a unit as well as major withdrawals since the 1950's. In this research, we tackle the problem of long term maintenance planning for a fleet of 90 hydro generators at Hydro-Quebec over a 50 years planning horizon period. We lay a scientific and rational framework to support withdrawals decisions by using part of the available data and maintenance history while fulfilling a set of technical and economic constraints. We propose a planning approach based on a constrained optimization framework. We begin by decomposing and sorting hydro generator components to highlight the most influential parts. A failure rate model is developed to take into account the technical characteristics and unit utilization. Then, replacement and repair policies are evaluated for each of the components then strategies are derived for the whole unit. Traditional univariate policies such as the age replacement policy and the minimal repair policy are calculated. These policies are extended to build alternative bivariate maintenance policy as well as a repair strategy where the state of a component after a repair is rejuvenated by a constant coefficient. These templates form the basis for the calculation of objective function for the scheduling problem. On one hand, this issue is treated as a nonlinear problem where the objective is to minimize the average total maintenance cost per unit of time on an infinite horizon for the fleet with technical and economic constraints. A formulation is also proposed in the case of a finite time horizon. In the event of electricity production variation, and given that the usage profile is known, the influence of production scenarios is reflected on the unit's components through their failure rate. In this context, prognoses on possible resources problems are made by studying the characteristics of the generated plans. On the second hand, the withdrawals are now subjected to two decision criteria. In addition to minimizing the average total maintenance cost per unit of time on an infinite time horizon, the best achievable reliability of remaining turbo generators is sought. This problem is treated as a biobjective nonlinear optimization problem. Finally a series of problems describing multiple contexts are solved for planning renovations of 90 turbo generators units considering 3 major components in each unit and 2 types of maintenance policies for each component.
NASA Astrophysics Data System (ADS)
Sembiring, N.; Panjaitan, N.; Angelita, S.
2018-02-01
PT. XYZ is a company owned by non-governmental organizations engaged in the field of production of rubber processing becoming crumb rubber. Part of the production is supported by some of machines and interacting equipment to achieve optimal productivity. Types of the machine that are used in the production process are Conveyor Breaker, Breaker, Rolling Pin, Hammer Mill, Mill Roll, Conveyor, Shredder Crumb, and Dryer. Maintenance system in PT. XYZ is corrective maintenance i.e. repairing or replacing the engine components after the crash on the machine. Replacement of engine components on corrective maintenance causes the machine to stop operating during the production process is in progress. The result is in the loss of production time due to the operator must replace the damaged engine components. The loss of production time can impact on the production targets which were not reached and lead to high loss costs. The cost for all components is Rp. 4.088.514.505. This cost is really high just for maintaining a Mill Roll Machine. Therefore PT. XYZ is needed to do preventive maintenance i.e. scheduling engine components and improving maintenance efficiency. The used methods are Reliability Engineering and Maintenance Value Stream Mapping (MVSM). The needed data in this research are the interval of time damage to engine components, opportunity cost, labor cost, component cost, corrective repair time, preventive repair time, Mean Time To Opportunity (MTTO), Mean Time To Repair (MTTR), and Mean Time To Yield (MTTY). In this research, the critical components of Mill Roll machine are Spier, Bushing, Bearing, Coupling and Roll. Determination of damage distribution, reliability, MTTF, cost of failure, cost of preventive, current state map, and future state map are done so that the replacement time for each critical component with the lowest maintenance cost and preparation of Standard Operation Procedure (SOP) are developed. For the critical component that has been determined, the Spier component replacement time interval is 228 days with a reliability value of 0,503171, Bushing component is 240 days with reliability value of 0.36861, Bearing component is 202 days with reliability value of 0,503058, Coupling component is 247 days with reliability value of 0,50108 and Roll component is 301 days with reliability value of 0,373525. The results show that the cost decreases from Rp 300,688,114 to Rp 244,384,371 obtained from corrective maintenance to preventive maintenance. While maintenance efficiency increases with the application of preventive maintenance i.e. for Spier component from 54,0540541% to 74,07407%, Bushing component from 52,3809524% to 68,75%, Bearing component from 40% to 52,63158%, Coupling component from 60.9756098% to 71.42857%, and Roll components from 64.516129% to 74.7663551%.
Simultaneously optimizing dose and schedule of a new cytotoxic agent.
Braun, Thomas M; Thall, Peter F; Nguyen, Hoang; de Lima, Marcos
2007-01-01
Traditionally, phase I clinical trial designs are based upon one predefined course of treatment while varying among patients the dose given at each administration. In actual medical practice, patients receive a schedule comprised of several courses of treatment, and some patients may receive one or more dose reductions or delays during treatment. Consequently, the overall risk of toxicity for each patient is a function of both actual schedule of treatment and the differing doses used at each adminstration. Our goal is to provide a practical phase I clinical trial design that more accurately reflects actual medical practice by accounting for both dose per administration and schedule. We propose an outcome-adaptive Bayesian design that simultaneously optimizes both dose and schedule in terms of the overall risk of toxicity, based on time-to-toxicity outcomes. We use computer simulation as a tool to calibrate design parameters. We describe a phase I trial in allogeneic bone marrow transplantation that was designed and is currently being conducted using our new method. Our computer simulations demonstrate that our method outperforms any method that searches for an optimal dose but does not allow schedule to vary, both in terms of the probability of identifying optimal (dose, schedule) combinations, and the numbers of patients assigned to those combinations in the trial. Our design requires greater sample sizes than those seen in traditional phase I studies due to the larger number of treatment combinations examined. Our design also assumes that the effects of multiple administrations are independent of each other and that the hazard of toxicity is the same for all administrations. Our design is the first for phase I clinical trials that is sufficiently flexible and practical to truly reflect clinical practice by varying both dose and the timing and number of administrations given to each patient.
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
Joint optimization of maintenance, buffers and machines in manufacturing lines
NASA Astrophysics Data System (ADS)
Nahas, Nabil; Nourelfath, Mustapha
2018-01-01
This article considers a series manufacturing line composed of several machines separated by intermediate buffers of finite capacity. The goal is to find the optimal number of preventive maintenance actions performed on each machine, the optimal selection of machines and the optimal buffer allocation plan that minimize the total system cost, while providing the desired system throughput level. The mean times between failures of all machines are assumed to increase when applying periodic preventive maintenance. To estimate the production line throughput, a decomposition method is used. The decision variables in the formulated optimal design problem are buffer levels, types of machines and times between preventive maintenance actions. Three heuristic approaches are developed to solve the formulated combinatorial optimization problem. The first heuristic consists of a genetic algorithm, the second is based on the nonlinear threshold accepting metaheuristic and the third is an ant colony system. The proposed heuristics are compared and their efficiency is shown through several numerical examples. It is found that the nonlinear threshold accepting algorithm outperforms the genetic algorithm and ant colony system, while the genetic algorithm provides better results than the ant colony system for longer manufacturing lines.
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.
Xu, Jiuping; Feng, Cuiying
2014-01-01
This paper presents an extension of the multimode resource-constrained project scheduling problem for a large scale construction project where multiple parallel projects and a fuzzy random environment are considered. By taking into account the most typical goals in project management, a cost/weighted makespan/quality trade-off optimization model is constructed. To deal with the uncertainties, a hybrid crisp approach is used to transform the fuzzy random parameters into fuzzy variables that are subsequently defuzzified using an expected value operator with an optimistic-pessimistic index. Then a combinatorial-priority-based hybrid particle swarm optimization algorithm is developed to solve the proposed model, where the combinatorial particle swarm optimization and priority-based particle swarm optimization are designed to assign modes to activities and to schedule activities, respectively. Finally, the results and analysis of a practical example at a large scale hydropower construction project are presented to demonstrate the practicality and efficiency of the proposed model and optimization method.
Mixed Integer Programming and Heuristic Scheduling for Space Communication Networks
NASA Technical Reports Server (NTRS)
Cheung, Kar-Ming; Lee, Charles H.
2012-01-01
We developed framework and the mathematical formulation for optimizing communication network using mixed integer programming. The design yields a system that is much smaller, in search space size, when compared to the earlier approach. Our constrained network optimization takes into account the dynamics of link performance within the network along with mission and operation requirements. A unique penalty function is introduced to transform the mixed integer programming into the more manageable problem of searching in a continuous space. The constrained optimization problem was proposed to solve in two stages: first using the heuristic Particle Swarming Optimization algorithm to get a good initial starting point, and then feeding the result into the Sequential Quadratic Programming algorithm to achieve the final optimal schedule. We demonstrate the above planning and scheduling methodology with a scenario of 20 spacecraft and 3 ground stations of a Deep Space Network site. Our approach and framework have been simple and flexible so that problems with larger number of constraints and network can be easily adapted and solved.
Xu, Jiuping
2014-01-01
This paper presents an extension of the multimode resource-constrained project scheduling problem for a large scale construction project where multiple parallel projects and a fuzzy random environment are considered. By taking into account the most typical goals in project management, a cost/weighted makespan/quality trade-off optimization model is constructed. To deal with the uncertainties, a hybrid crisp approach is used to transform the fuzzy random parameters into fuzzy variables that are subsequently defuzzified using an expected value operator with an optimistic-pessimistic index. Then a combinatorial-priority-based hybrid particle swarm optimization algorithm is developed to solve the proposed model, where the combinatorial particle swarm optimization and priority-based particle swarm optimization are designed to assign modes to activities and to schedule activities, respectively. Finally, the results and analysis of a practical example at a large scale hydropower construction project are presented to demonstrate the practicality and efficiency of the proposed model and optimization method. PMID:24550708
Evolutionarily stable learning schedules and cumulative culture in discrete generation models.
Aoki, Kenichi; Wakano, Joe Yuichiro; Lehmann, Laurent
2012-06-01
Individual learning (e.g., trial-and-error) and social learning (e.g., imitation) are alternative ways of acquiring and expressing the appropriate phenotype in an environment. The optimal choice between using individual learning and/or social learning may be dictated by the life-stage or age of an organism. Of special interest is a learning schedule in which social learning precedes individual learning, because such a schedule is apparently a necessary condition for cumulative culture. Assuming two obligatory learning stages per discrete generation, we obtain the evolutionarily stable learning schedules for the three situations where the environment is constant, fluctuates between generations, or fluctuates within generations. During each learning stage, we assume that an organism may target the optimal phenotype in the current environment by individual learning, and/or the mature phenotype of the previous generation by oblique social learning. In the absence of exogenous costs to learning, the evolutionarily stable learning schedules are predicted to be either pure social learning followed by pure individual learning ("bang-bang" control) or pure individual learning at both stages ("flat" control). Moreover, we find for each situation that the evolutionarily stable learning schedule is also the one that optimizes the learned phenotype at equilibrium. Copyright © 2012 Elsevier Inc. All rights reserved.
NASA Astrophysics Data System (ADS)
Izah Anuar, Nurul; Saptari, Adi
2016-02-01
This paper addresses the types of particle representation (encoding) procedures in a population-based stochastic optimization technique in solving scheduling problems known in the job-shop manufacturing environment. It intends to evaluate and compare the performance of different particle representation procedures in Particle Swarm Optimization (PSO) in the case of solving Job-shop Scheduling Problems (JSP). Particle representation procedures refer to the mapping between the particle position in PSO and the scheduling solution in JSP. It is an important step to be carried out so that each particle in PSO can represent a schedule in JSP. Three procedures such as Operation and Particle Position Sequence (OPPS), random keys representation and random-key encoding scheme are used in this study. These procedures have been tested on FT06 and FT10 benchmark problems available in the OR-Library, where the objective function is to minimize the makespan by the use of MATLAB software. Based on the experimental results, it is discovered that OPPS gives the best performance in solving both benchmark problems. The contribution of this paper is the fact that it demonstrates to the practitioners involved in complex scheduling problems that different particle representation procedures can have significant effects on the performance of PSO in solving JSP.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Divecha, Mia S.; Derby, Jeffrey J.
Historically, the melt growth of II-VI crystals has benefitted by the application of the accelerated crucible rotation technique (ACRT). Here, we employ a comprehensive numerical model to assess the impact of two ACRT schedules designed for a cadmium zinc telluride growth system per the classical recommendations of Capper and co-workers. The “flow maximizing” ACRT schedule, with higher rotation, effectively mixes the solutal field in the melt but does not reduce supercooling adjacent to the growth interface. The ACRT schedule derived for stable Ekman flow, with lower rotation, proves more effective in reducing supercooling and promoting stable growth. Furthermore, these counterintuitivemore » results highlight the need for more comprehensive studies on the optimization of ACRT schedules for specific growth systems and for desired growth outcomes.« less
Divecha, Mia S.; Derby, Jeffrey J.
2017-10-03
Historically, the melt growth of II-VI crystals has benefitted by the application of the accelerated crucible rotation technique (ACRT). Here, we employ a comprehensive numerical model to assess the impact of two ACRT schedules designed for a cadmium zinc telluride growth system per the classical recommendations of Capper and co-workers. The “flow maximizing” ACRT schedule, with higher rotation, effectively mixes the solutal field in the melt but does not reduce supercooling adjacent to the growth interface. The ACRT schedule derived for stable Ekman flow, with lower rotation, proves more effective in reducing supercooling and promoting stable growth. Furthermore, these counterintuitivemore » results highlight the need for more comprehensive studies on the optimization of ACRT schedules for specific growth systems and for desired growth outcomes.« less
Policy for equipment’s leasing period extension with minimum cost of maintenance
NASA Astrophysics Data System (ADS)
Lestari, C.; Kurniati, N.
2018-04-01
The cost structure for equipment investment including purchase cost and maintenance cost is getting more expensive. The company considers to lease the equipment instead of purchase it under a contractual agreement. Offering to extend the lease period, following to the base lease period, will provide more benefits for both the lessor (owner) and the lessee (user). Whenever the lease period extension offered at the beginning of the contract, there are some risks in finance e.g. uncertainty of the equipment performance and lessor responsibility. Therefore, this research attempts to model the optimal maintenance policy for lease period extension offered at the end of the contract. Minimal repair is performed to rectify a failed equipment, while imperfect preventive maintenance is conducted to improve the operational state of the equipment when reaches a certain control limit to avoid failures. The mathematical model is constructed to determine the optimal control limit, the number and degree of preventive maintenance, and the multiplication number of the lease period extension. Finally, numerical examples are given to illustrate the influences of the optimal length of the extended lease and the maintenance policy to minimize the maintenance cost.
Zhimeng, Li; Chuan, He; Dishan, Qiu; Jin, Liu; Manhao, Ma
2013-01-01
Aiming to the imaging tasks scheduling problem on high-altitude airship in emergency condition, the programming models are constructed by analyzing the main constraints, which take the maximum task benefit and the minimum energy consumption as two optimization objectives. Firstly, the hierarchy architecture is adopted to convert this scheduling problem into three subproblems, that is, the task ranking, value task detecting, and energy conservation optimization. Then, the algorithms are designed for the sub-problems, and the solving results are corresponding to feasible solution, efficient solution, and optimization solution of original problem, respectively. This paper makes detailed introduction to the energy-aware optimization strategy, which can rationally adjust airship's cruising speed based on the distribution of task's deadline, so as to decrease the total energy consumption caused by cruising activities. Finally, the application results and comparison analysis show that the proposed strategy and algorithm are effective and feasible. PMID:23864822
Optimizing energy for a ‘green’ vaccine supply chain
Lloyd, John; McCarney, Steve; Ouhichi, Ramzi; Lydon, Patrick; Zaffran, Michel
2015-01-01
This paper describes an approach piloted in the Kasserine region of Tunisia to increase the energy efficiency of the distribution of vaccines and temperature sensitive drugs. The objectives of an approach, known as the ‘net zero energy’ (NZE) supply chain were demonstrated within the first year of operation. The existing distribution system was modified to store vaccines and medicines in the same buildings and to transport them according to pre-scheduled and optimized delivery circuits. Electric utility vehicles, dedicated to the integrated delivery of vaccines and medicines, improved the regularity and reliability of the supply chains. Solar energy, linked to the electricity grid at regional and district stores, supplied over 100% of consumption meeting all energy needs for storage, cooling and transportation. Significant benefits to the quality and costs of distribution were demonstrated. Supply trips were scheduled, integrated and reliable, energy consumption was reduced, the recurrent cost of electricity was eliminated and the release of carbon to the atmosphere was reduced. Although the initial capital cost of scaling up implementation of NZE remain high today, commercial forecasts predict cost reduction for solar energy and electric vehicles that may permit a step-wise implementation over the next 7–10 years. Efficiency in the use of energy and in the deployment of transport is already a critical component of distribution logistics in both private and public sectors of industrialized countries. The NZE approach has an intensified rationale in countries where energy costs threaten the maintenance of public health services in areas of low population density. In these countries where the mobility of health personnel and timely arrival of supplies is at risk, NZE has the potential to reduce energy costs and release recurrent budget to other needs of service delivery while also improving the supply chain. PMID:25444811
User interface issues in supporting human-computer integrated scheduling
NASA Technical Reports Server (NTRS)
Cooper, Lynne P.; Biefeld, Eric W.
1991-01-01
Explored here is the user interface problems encountered with the Operations Missions Planner (OMP) project at the Jet Propulsion Laboratory (JPL). OMP uses a unique iterative approach to planning that places additional requirements on the user interface, particularly to support system development and maintenance. These requirements are necessary to support the concepts of heuristically controlled search, in-progress assessment, and iterative refinement of the schedule. The techniques used to address the OMP interface needs are given.
Perspectives on U.S. Competitiveness in Science and Technology
2007-01-01
nation is unlikely to receive some sudden “ wakeup ” call; rather, the problem is one that is likely to evidence itself gradually over a surprisingly...health care than on steel.3 US scheduled airlines currently outsource portions of their aircraft maintenance to China and El Salvador.4 IBM recently sold... schedules based on “duties classification.” This approach reflected the “scientific” management period by formalizing the “rank in position” principle of
Perspectives on U.S. Competitiveness in Science and Technology: Conference Proceedings
2006-11-01
that the nation is unlikely to receive some sudden “ wakeup ” call; rather, the problem is one that is likely to evidence itself gradually over a...on health care than on steel.3 US scheduled airlines currently outsource portions of their aircraft maintenance to China and El Salvador.4 IBM... schedules based on “duties classification.” This approach reflected the “scientific” management period by formalizing the “rank in position
Optimization of monitoring and inspections in the life-cycle of wind turbines
NASA Astrophysics Data System (ADS)
Hanish Nithin, Anu; Omenzetter, Piotr
2016-04-01
The past decade has witnessed a surge in the offshore wind farm developments across the world. Although this form of cleaner and greener energy is beneficial and eco-friendly, the production of wind energy entails high life-cycle costs. The costs associated with inspections, monitoring and repairs of wind turbines are primary contributors to the high costs of electricity produced in this way and are disadvantageous in today's competitive economic environment. There is limited research being done in the probabilistic optimization of life-cycle costs of offshore wind turbines structures and their components. This paper proposes a framework for assessing the life cycle cost of wind turbine structures subject to damage and deterioration. The objective of the paper is to develop a mathematical probabilistic cost assessment framework which considers deterioration, inspection, monitoring, repair and maintenance models and their uncertainties. The uncertainties are etched in the accuracy and precision of the monitoring and inspection methods and can be considered through the probability of damage detection of each method. Schedules for inspection, monitoring and repair actions are demonstrated using a decision tree. Examples of a generalised deterioration process integrated with the cost analysis using a decision tree are shown for a wind turbine foundation structure.
Plane Wave SH₀ Piezoceramic Transduction Optimized Using Geometrical Parameters.
Boivin, Guillaume; Viens, Martin; Belanger, Pierre
2018-02-10
Structural health monitoring is a prominent alternative to the scheduled maintenance of safety-critical components. The nondispersive nature as well as the through-thickness mode shape of the fundamental shear horizontal guided wave mode (SH 0 ) make it a particularly attractive candidate for ultrasonic guided wave structural health monitoring. However, plane wave excitation of SH 0 at a high level of purity remains challenging because of the existence of the fundamental Lamb modes (A 0 and S 0 ) below the cutoff frequency thickness product of high-order modes. This paper presents a piezoelectric transducer concept optimized for plane SH 0 wave transduction based on the transducer geometry. The transducer parameter exploration was initially performed using a simple analytical model. A 3D multiphysics finite element model was then used to refine the transducer design. Finally, an experimental validation was conducted with a 3D laser Doppler vibrometer system. The analytical model, the finite element model, and the experimental measurement showed excellent agreement. The modal selectivity of SH 0 within a 20 ∘ beam opening angle at the design frequency of 425 kHz in a 1.59 mm aluminum plate was 23 dB, and the angle of the 6 dB wavefront was 86 ∘ .
Guidelines for software inspections
NASA Technical Reports Server (NTRS)
1983-01-01
Quality control inspections are software problem finding procedures which provide defect removal as well as improvements in software functionality, maintenance, quality, and development and testing methodology is discussed. The many side benefits include education, documentation, training, and scheduling.
Multi-trip vehicle routing and scheduling problem with time window in real life
NASA Astrophysics Data System (ADS)
Sze, San-Nah; Chiew, Kang-Leng; Sze, Jeeu-Fong
2012-09-01
This paper studies a manpower scheduling problem with multiple maintenance operations and vehicle routing considerations. Service teams located at a common service centre are required to travel to different customer sites. All customers must be served within given time window, which are known in advance. The scheduling process must take into consideration complex constraints such as a meal break during the team's shift, multiple travelling trips, synchronisation of service teams and working shifts. The main objective of this study is to develop a heuristic that can generate high quality solution in short time for large problem instances. A Two-stage Scheduling Heuristic is developed for different variants of the problem. Empirical results show that the proposed solution performs effectively and efficiently. In addition, our proposed approximation algorithm is very flexible and can be easily adapted to different scheduling environments and operational requirements.
The air transportation industry birthplace of reliability-centered maintenance
DOE Office of Scientific and Technical Information (OSTI.GOV)
Matteson, T.D.
1996-08-01
The 1980s and 1970s provided a timely opportunity for examining and radically changing the process called {open_quotes}preventive maintenance{close_quotes} as it is applied to the aircraft used for scheduled air transportation. The Federal Aviation Administration and four major airlines, United, American, Pan American and Trans World, were the {open_quotes}principals{close_quotes} in that process. While United`s work with the FAA on the Boeing 737 had opened the door a crack, the Boeing 747 presented a major opportunity to radically improve the process for maintenance program design. That program was guided by the results of United`s analyses of failure data from operations of severalmore » fleets, each larger than 100 aircraft, and the concurrent experience of American, Pan American and Trans World. That knowledge provided the insights necessary to support an entirely different approach to maintenance program design. As a result, while United`s existing maintenance program required scheduled overhaul of 339 items on each DC-8, it required overhaul of only 8 items on the B-7471 Although the initial thrust of that work focused on components of active systems, there was concurrent work focused on items whose principal function was to carry the loads associated with operations. That program focused on the classification of structurally-significant items and their classification as {open_quotes}safe life{close_quotes} or {open_quotes}damage tolerant{close_quote} to determine what periodic replacements or repeated inspections were required. That work came to the attention of the Department of Defense which supported preparation of the book-length report by F. Stanley Nowlan and Howard F. Heap at United Airlines entitled {open_quote}Reliability-Centered maintenance{close_quotes}.« less
NASA Technical Reports Server (NTRS)
Zweben, Monte
1991-01-01
The GERRY scheduling system developed by NASA Ames with assistance from the Lockheed Space Operations Company, and the Lockheed Artificial Intelligence Center, uses a method called constraint-based iterative repair. Using this technique, one encodes both hard rules and preference criteria into data structures called constraints. GERRY repeatedly attempts to improve schedules by seeking repairs for violated constraints. The system provides a general scheduling framework which is being tested on two NASA applications. The larger of the two is the Space Shuttle Ground Processing problem which entails the scheduling of all the inspection, repair, and maintenance tasks required to prepare the orbiter for flight. The other application involves power allocation for the NASA Ames wind tunnels. Here the system will be used to schedule wind tunnel tests with the goal of minimizing power costs. In this paper, we describe the GERRY system and its application to the Space Shuttle problem. We also speculate as to how the system would be used for manufacturing, transportation, and military problems.
NASA Technical Reports Server (NTRS)
Zweben, Monte
1991-01-01
The GERRY scheduling system developed by NASA Ames with assistance from the Lockheed Space Operations Company, and the Lockheed Artificial Intelligence Center, uses a method called constraint based iterative repair. Using this technique, one encodes both hard rules and preference criteria into data structures called constraints. GERRY repeatedly attempts to improve schedules by seeking repairs for violated constraints. The system provides a general scheduling framework which is being tested on two NASA applications. The larger of the two is the Space Shuttle Ground Processing problem which entails the scheduling of all inspection, repair, and maintenance tasks required to prepare the orbiter for flight. The other application involves power allocations for the NASA Ames wind tunnels. Here the system will be used to schedule wind tunnel tests with the goal of minimizing power costs. In this paper, we describe the GERRY system and its applications to the Space Shuttle problem. We also speculate as to how the system would be used for manufacturing, transportation, and military problems.
NASA Technical Reports Server (NTRS)
Zweben, Monte
1993-01-01
The GERRY scheduling system developed by NASA Ames with assistance from the Lockheed Space Operations Company, and the Lockheed Artificial Intelligence Center, uses a method called constraint-based iterative repair. Using this technique, one encodes both hard rules and preference criteria into data structures called constraints. GERRY repeatedly attempts to improve schedules by seeking repairs for violated constraints. The system provides a general scheduling framework which is being tested on two NASA applications. The larger of the two is the Space Shuttle Ground Processing problem which entails the scheduling of all the inspection, repair, and maintenance tasks required to prepare the orbiter for flight. The other application involves power allocation for the NASA Ames wind tunnels. Here the system will be used to schedule wind tunnel tests with the goal of minimizing power costs. In this paper, we describe the GERRY system and its application to the Space Shuttle problem. We also speculate as to how the system would be used for manufacturing, transportation, and military problems.
Utilization Bound of Non-preemptive Fixed Priority Schedulers
NASA Astrophysics Data System (ADS)
Park, Moonju; Chae, Jinseok
It is known that the schedulability of a non-preemptive task set with fixed priority can be determined in pseudo-polynomial time. However, since Rate Monotonic scheduling is not optimal for non-preemptive scheduling, the applicability of existing polynomial time tests that provide sufficient schedulability conditions, such as Liu and Layland's bound, is limited. This letter proposes a new sufficient condition for non-preemptive fixed priority scheduling that can be used for any fixed priority assignment scheme. It is also shown that the proposed schedulability test has a tighter utilization bound than existing test methods.
Optimal updating magnitude in adaptive flat-distribution sampling
NASA Astrophysics Data System (ADS)
Zhang, Cheng; Drake, Justin A.; Ma, Jianpeng; Pettitt, B. Montgomery
2017-11-01
We present a study on the optimization of the updating magnitude for a class of free energy methods based on flat-distribution sampling, including the Wang-Landau (WL) algorithm and metadynamics. These methods rely on adaptive construction of a bias potential that offsets the potential of mean force by histogram-based updates. The convergence of the bias potential can be improved by decreasing the updating magnitude with an optimal schedule. We show that while the asymptotically optimal schedule for the single-bin updating scheme (commonly used in the WL algorithm) is given by the known inverse-time formula, that for the Gaussian updating scheme (commonly used in metadynamics) is often more complex. We further show that the single-bin updating scheme is optimal for very long simulations, and it can be generalized to a class of bandpass updating schemes that are similarly optimal. These bandpass updating schemes target only a few long-range distribution modes and their optimal schedule is also given by the inverse-time formula. Constructed from orthogonal polynomials, the bandpass updating schemes generalize the WL and Langfeld-Lucini-Rago algorithms as an automatic parameter tuning scheme for umbrella sampling.
Optimal updating magnitude in adaptive flat-distribution sampling.
Zhang, Cheng; Drake, Justin A; Ma, Jianpeng; Pettitt, B Montgomery
2017-11-07
We present a study on the optimization of the updating magnitude for a class of free energy methods based on flat-distribution sampling, including the Wang-Landau (WL) algorithm and metadynamics. These methods rely on adaptive construction of a bias potential that offsets the potential of mean force by histogram-based updates. The convergence of the bias potential can be improved by decreasing the updating magnitude with an optimal schedule. We show that while the asymptotically optimal schedule for the single-bin updating scheme (commonly used in the WL algorithm) is given by the known inverse-time formula, that for the Gaussian updating scheme (commonly used in metadynamics) is often more complex. We further show that the single-bin updating scheme is optimal for very long simulations, and it can be generalized to a class of bandpass updating schemes that are similarly optimal. These bandpass updating schemes target only a few long-range distribution modes and their optimal schedule is also given by the inverse-time formula. Constructed from orthogonal polynomials, the bandpass updating schemes generalize the WL and Langfeld-Lucini-Rago algorithms as an automatic parameter tuning scheme for umbrella sampling.
Optimizing Maintenance Manpower for USMC F/A-18 Squadrons
2016-06-01
experience level, with the requirement of keeping a standard number of aircraft operationally ready. MVP results show areas of deficit, either manpower ...MAINTENANCE MANPOWER FOR USMC F/A-18 SQUADRONS by Kevin J. Goodwin June 2016 Thesis Co-Advisors: W. Matthew Carlyle Robert F. Dell Second...REPORT TYPE AND DATES COVERED Master’s thesis 4. TITLE AND SUBTITLE OPTIMIZING MAINTENANCE MANPOWER FOR USMC F/A-18 SQUADRONS 5. FUNDING NUMBERS 6
NASA Astrophysics Data System (ADS)
Mortazavi-Naeini, Mohammad; Kuczera, George; Cui, Lijie
2014-06-01
Significant population increase in urban areas is likely to result in a deterioration of drought security and level of service provided by urban water resource systems. One way to cope with this is to optimally schedule the expansion of system resources. However, the high capital costs and environmental impacts associated with expanding or building major water infrastructure warrant the investigation of scheduling system operational options such as reservoir operating rules, demand reduction policies, and drought contingency plans, as a way of delaying or avoiding the expansion of water supply infrastructure. Traditionally, minimizing cost has been considered the primary objective in scheduling capacity expansion problems. In this paper, we consider some of the drawbacks of this approach. It is shown that there is no guarantee that the social burden of coping with drought emergencies is shared equitably across planning stages. In addition, it is shown that previous approaches do not adequately exploit the benefits of joint optimization of operational and infrastructure options and do not adequately address the need for the high level of drought security expected for urban systems. To address these shortcomings, a new multiobjective optimization approach to scheduling capacity expansion in an urban water resource system is presented and illustrated in a case study involving the bulk water supply system for Canberra. The results show that the multiobjective approach can address the temporal equity issue of sharing the burden of drought emergencies and that joint optimization of operational and infrastructure options can provide solutions superior to those just involving infrastructure options.
Application of the Software as a Service Model to the Control of Complex Building Systems
DOE Office of Scientific and Technical Information (OSTI.GOV)
Stadler, Michael; Donadee, Jonathan; Marnay, Chris
2011-03-17
In an effort to create broad access to its optimization software, Lawrence Berkeley National Laboratory (LBNL), in collaboration with the University of California at Davis (UC Davis) and OSISoft, has recently developed a Software as a Service (SaaS) Model for reducing energy costs, cutting peak power demand, and reducing carbon emissions for multipurpose buildings. UC Davis currently collects and stores energy usage data from buildings on its campus. Researchers at LBNL sought to demonstrate that a SaaS application architecture could be built on top of this data system to optimize the scheduling of electricity and heat delivery in the building.more » The SaaS interface, known as WebOpt, consists of two major parts: a) the investment& planning and b) the operations module, which builds on the investment& planning module. The operational scheduling and load shifting optimization models within the operations module use data from load prediction and electrical grid emissions models to create an optimal operating schedule for the next week, reducing peak electricity consumption while maintaining quality of energy services. LBNL's application also provides facility managers with suggested energy infrastructure investments for achieving their energy cost and emission goals based on historical data collected with OSISoft's system. This paper describes these models as well as the SaaS architecture employed by LBNL researchers to provide asset scheduling services to UC Davis. The peak demand, emissions, and cost implications of the asset operation schedule and investments suggested by this optimization model are analysed.« less
Application of the Software as a Service Model to the Control of Complex Building Systems
DOE Office of Scientific and Technical Information (OSTI.GOV)
Stadler, Michael; Donadee, Jon; Marnay, Chris
2011-03-18
In an effort to create broad access to its optimization software, Lawrence Berkeley National Laboratory (LBNL), in collaboration with the University of California at Davis (UC Davis) and OSISoft, has recently developed a Software as a Service (SaaS) Model for reducing energy costs, cutting peak power demand, and reducing carbon emissions for multipurpose buildings. UC Davis currently collects and stores energy usage data from buildings on its campus. Researchers at LBNL sought to demonstrate that a SaaS application architecture could be built on top of this data system to optimize the scheduling of electricity and heat delivery in the building.more » The SaaS interface, known as WebOpt, consists of two major parts: a) the investment& planning and b) the operations module, which builds on the investment& planning module. The operational scheduling and load shifting optimization models within the operations module use data from load prediction and electrical grid emissions models to create an optimal operating schedule for the next week, reducing peak electricity consumption while maintaining quality of energy services. LBNL's application also provides facility managers with suggested energy infrastructure investments for achieving their energy cost and emission goals based on historical data collected with OSISoft's system. This paper describes these models as well as the SaaS architecture employed by LBNL researchers to provide asset scheduling services to UC Davis. The peak demand, emissions, and cost implications of the asset operation schedule and investments suggested by this optimization model are analyzed.« less
Incentive-compatible guaranteed renewable health insurance premiums.
Herring, Bradley; Pauly, Mark V
2006-05-01
Theoretical models of guaranteed renewable insurance display front-loaded premium schedules. Such schedules both cover lifetime total claims of low-risk and high-risk individuals and provide an incentive for those who remain low-risk to continue to purchase the policy. Questions have been raised of whether actual individual insurance markets in the US approximate the behavior predicted by these models, both because young consumers may not be able to "afford" front-loading and because insurers may behave strategically in ways that erode the value of protection against risk reclassification. In this paper, the optimal competitive age-based premium schedule for a benchmark guaranteed renewable health insurance policy is estimated using medical expenditure data. Several factors are shown to reduce the amount of front-loading necessary. Indeed, the resulting optimal premium path increases with age. Actual premium paths exhibited by purchasers of individual insurance are close to the optimal renewable schedule we estimate. Finally, consumer utility associated with the feature is examined.
Applications of colored petri net and genetic algorithms to cluster tool scheduling
NASA Astrophysics Data System (ADS)
Liu, Tung-Kuan; Kuo, Chih-Jen; Hsiao, Yung-Chin; Tsai, Jinn-Tsong; Chou, Jyh-Horng
2005-12-01
In this paper, we propose a method, which uses Coloured Petri Net (CPN) and genetic algorithm (GA) to obtain an optimal deadlock-free schedule and to solve re-entrant problem for the flexible process of the cluster tool. The process of the cluster tool for producing a wafer usually can be classified into three types: 1) sequential process, 2) parallel process, and 3) sequential parallel process. But these processes are not economical enough to produce a variety of wafers in small volume. Therefore, this paper will propose the flexible process where the operations of fabricating wafers are randomly arranged to achieve the best utilization of the cluster tool. However, the flexible process may have deadlock and re-entrant problems which can be detected by CPN. On the other hand, GAs have been applied to find the optimal schedule for many types of manufacturing processes. Therefore, we successfully integrate CPN and GAs to obtain an optimal schedule with the deadlock and re-entrant problems for the flexible process of the cluster tool.
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
VAXELN Experimentation: Programming a Real-Time Periodic Task Dispatcher Using VAXELN Ada 1.1
1987-11-01
synchronization to the SQM and VAXELN semaphores. Based on real-time scheduling theory, the optimal rate-monotonic scheduling algorithm [Lui 73...schedulability test based on the rate-monotonic algorithm , namely task-lumping [Sha 871, was necessary to cal- culate the theoretically expected schedulability...8217 Guide Digital Equipment Corporation, Maynard, MA, 1986. [Lui 73] Liu, C.L., Layland, J.W. Scheduling Algorithms for Multi-programming in a Hard-Real-Time
Strategies GeoCape Intelligent Observation Studies @ GSFC
NASA Technical Reports Server (NTRS)
Cappelaere, Pat; Frye, Stu; Moe, Karen; Mandl, Dan; LeMoigne, Jacqueline; Flatley, Tom; Geist, Alessandro
2015-01-01
This presentation provides information a summary of the tradeoff studies conducted for GeoCape by the GSFC team in terms of how to optimize GeoCape observation efficiency. Tradeoffs include total ground scheduling with simple priorities, ground scheduling with cloud forecast, ground scheduling with sub-area forecast, onboard scheduling with onboard cloud detection and smart onboard scheduling and onboard image processing. The tradeoffs considered optimzing cost, downlink bandwidth and total number of images acquired.
1980-11-01
structural manager. The designation "ASIMISH is used in the subsequent discussions to avoid the impression that a new organization must be created to...mission changes on the structural integrity of the airframe. New maintenance action schedules are created to conform with the operational realities of... created to further divide this information. In fact, the ASIP maintenance action parameters and data for the A-7D ( and other airplanes) is being
Fast Optimization for Aircraft Descent and Approach Trajectory
NASA Technical Reports Server (NTRS)
Luchinsky, Dmitry G.; Schuet, Stefan; Brenton, J.; Timucin, Dogan; Smith, David; Kaneshige, John
2017-01-01
We address problem of on-line scheduling of the aircraft descent and approach trajectory. We formulate a general multiphase optimal control problem for optimization of the descent trajectory and review available methods of its solution. We develop a fast algorithm for solution of this problem using two key components: (i) fast inference of the dynamical and control variables of the descending trajectory from the low dimensional flight profile data and (ii) efficient local search for the resulting reduced dimensionality non-linear optimization problem. We compare the performance of the proposed algorithm with numerical solution obtained using optimal control toolbox General Pseudospectral Optimal Control Software. We present results of the solution of the scheduling problem for aircraft descent using novel fast algorithm and discuss its future applications.
Airline Maintenance Manpower Optimization from the De Novo Perspective
NASA Astrophysics Data System (ADS)
Liou, James J. H.; Tzeng, Gwo-Hshiung
Human resource management (HRM) is an important issue for today’s competitive airline marketing. In this paper, we discuss a multi-objective model designed from the De Novo perspective to help airlines optimize their maintenance manpower portfolio. The effectiveness of the model and solution algorithm is demonstrated in an empirical study of the optimization of the human resources needed for airline line maintenance. Both De Novo and traditional multiple objective programming (MOP) methods are analyzed. A comparison of the results with those of traditional MOP indicates that the proposed model and solution algorithm does provide better performance and an improved human resource portfolio.
Beyond reliability to profitability
DOE Office of Scientific and Technical Information (OSTI.GOV)
Bond, T.H.; Mitchell, J.S.
1996-07-01
Reliability concerns have controlled much of power generation design and operations. Emerging from a strictly regulated environment, profitability is becoming a much more important concept for today`s power generation executives. This paper discusses the conceptual advance-view power plant maintenance as a profit center, go beyond reliability, and embrace profitability. Profit Centered Maintenance begins with the premise that financial considerations, namely profitability, drive most aspects of modern process and manufacturing operations. Profit Centered Maintenance is a continuous process of reliability and administrative improvement and optimization. For the power generation executives with troublesome maintenance programs, Profit Centered Maintenance can be the blueprintmore » to increased profitability. It requires the culture change to make decisions based on value, to reengineer the administration of maintenance, and to enable the people performing and administering maintenance to make the most of available maintenance information technology. The key steps are to optimize the physical function of maintenance and to resolve recurring maintenance problems so that the need for maintenance can be reduced. Profit Centered Maintenance is more than just an attitude it is a path to profitability, be it resulting in increased profits or increased market share.« less
7 CFR 654.15 - Operation and maintenance.
Code of Federal Regulations, 2014 CFR
2014-01-01
... installed as set forth in the watershed or RC&D measure plan. (d) Compliance with the time frames and O&M... the schedule for withdrawal of water in water impounding structures as specified in the watershed or...
7 CFR 654.15 - Operation and maintenance.
Code of Federal Regulations, 2010 CFR
2010-01-01
... installed as set forth in the watershed or RC&D measure plan. (d) Compliance with the time frames and O&M... the schedule for withdrawal of water in water impounding structures as specified in the watershed or...
On metaheuristic "failure modes": a case study in Tabu search for job-shop scheduling.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Watson, Jean-Paul
2005-06-01
In this paper, we analyze the relationship between pool maintenance schemes, long-term memory mechanisms, and search space structure, with the goal of placing metaheuristic design on a more concrete foundation.
What to Do until the Microprocesser Arrives.
ERIC Educational Resources Information Center
Barzilla, Frank
1983-01-01
Advises administrators how to develop an energy master plan and how to reduce the usage of heating, ventilating, and air conditioning (HVAC) systems by means of a time clock, thermostat, and a scheduled preventive maintenance program. (MLF)
Evapotranspiration-based irrigation scheduling of lettuce and broccoli
USDA-ARS?s Scientific Manuscript database
Estimation of crop evapotranspiration supports efficient irrigation water management, which in turn supports water conservation, mitigation of groundwater depletion/degradation, energy savings, and crop quality maintenance. Past research in California has revealed strong relationships between fract...
A Busy School Year for Spacecraft.
ERIC Educational Resources Information Center
Riddle, Bob
2001-01-01
Discusses the five upcoming shuttle missions, two Russian missions to the International Space Station, a scheduled visit to the Hubble Space Telescope for maintenance, and other events in the solar system. Includes a list of monthly events. (YDS)
Plant Operation: Exterior Maintenance, Work Hours
ERIC Educational Resources Information Center
Nation's Schools and Colleges, 1975
1975-01-01
A pitched roof built over a flat roof prevented leaking at a Vermont school. The University of New Hampshire paint shop has a flexible scheduling system that allows employees to choose their work hours each day. (Author/MLF)
Plant maintenance and advanced reactors, 2005
DOE Office of Scientific and Technical Information (OSTI.GOV)
Agnihotri, Newal
2005-09-15
The focus of the September-October issue is on plant maintenance and advanced reactors. Major articles/reports in this issue include: First U.S. EPRs in 2015, by Ray Ganthner, Framatome ANP; Pursuing several opportunities, by William E. (Ed) Cummins, Westinghouse Electric Company; Vigorous plans to develop advanced reactors, by Yuliang Sun, Tsinghua University, China; Multiple designs, small and large, by Kumiaki Moriya, Hitachi Ltd., Japan; Sealed and embedded for safety and security, by Handa Norihiko, Toshiba Corporation, Japan; Scheduled online in 2010, by Johan Slabber, PMBR (Pty) Ltd., South Africa; Multi-application reactors, by Nikolay G. Kodochigov, OKBM, Russia; Six projects under budgetmore » and on schedule, by David F. Togerson, AECL, Canada; Creating a positive image, by Scott Peterson, Nuclear Energy Institute (NEI); Advanced plans for nuclear power's renaissance, by John Cleveland, International Atomic Energy Agency, Austria; and, Plant profile: last five outages in less than 20 days, by Beth Rapczynski, Exelon Nuclear.« less
40 CFR 1065.303 - Summary of required calibration and verifications.
Code of Federal Regulations, 2012 CFR
2012-07-01
... initial installation and after major maintenance. THC FID optimization, and THC FID verification Optimize and determine CH4 response for THC FID analyzers: upon initial installation and after major maintenance. Verify CH4 response for THC FID analyzers: upon initial installation, within 185 days before...
40 CFR 1065.303 - Summary of required calibration and verifications.
Code of Federal Regulations, 2013 CFR
2013-07-01
... initial installation and after major maintenance. THC FID optimization, and THC FID verification Optimize and determine CH4 response for THC FID analyzers: upon initial installation and after major maintenance. Verify CH4 response for THC FID analyzers: upon initial installation, within 185 days before...
Dose Schedule Optimization and the Pharmacokinetic Driver of Neutropenia
Patel, Mayankbhai; Palani, Santhosh; Chakravarty, Arijit; Yang, Johnny; Shyu, Wen Chyi; Mettetal, Jerome T.
2014-01-01
Toxicity often limits the utility of oncology drugs, and optimization of dose schedule represents one option for mitigation of this toxicity. Here we explore the schedule-dependency of neutropenia, a common dose-limiting toxicity. To this end, we analyze previously published mathematical models of neutropenia to identify a pharmacokinetic (PK) predictor of the neutrophil nadir, and confirm this PK predictor in an in vivo experimental system. Specifically, we find total AUC and Cmax are poor predictors of the neutrophil nadir, while a PK measure based on the moving average of the drug concentration correlates highly with neutropenia. Further, we confirm this PK parameter for its ability to predict neutropenia in vivo following treatment with different doses and schedules. This work represents an attempt at mechanistically deriving a fundamental understanding of the underlying pharmacokinetic drivers of neutropenia, and provides insights that can be leveraged in a translational setting during schedule selection. PMID:25360756
Optimizing Chemotherapy Dose and Schedule by Norton-Simon Mathematical Modeling
Traina, Tiffany A.; Dugan, Ute; Higgins, Brian; Kolinsky, Kenneth; Theodoulou, Maria; Hudis, Clifford A.; Norton, Larry
2011-01-01
Background To hasten and improve anticancer drug development, we created a novel approach to generating and analyzing preclinical dose-scheduling data so as to optimize benefit-to-toxicity ratios. Methods We applied mathematical methods based upon Norton-Simon growth kinetic modeling to tumor-volume data from breast cancer xenografts treated with capecitabine (Xeloda®, Roche) at the conventional schedule of 14 days of treatment followed by a 7-day rest (14 - 7). Results The model predicted that 7 days of treatment followed by a 7-day rest (7 - 7) would be superior. Subsequent preclinical studies demonstrated that this biweekly capecitabine schedule allowed for safe delivery of higher daily doses, improved tumor response, and prolonged animal survival. Conclusions We demonstrated that the application of Norton-Simon modeling to the design and analysis of preclinical data predicts an improved capecitabine dosing schedule in xenograft models. This method warrants further investigation and application in clinical drug development. PMID:20519801
Prognostics Methodology for Complex Systems
NASA Technical Reports Server (NTRS)
Gulati, Sandeep; Mackey, Ryan
2003-01-01
An automatic method to schedule maintenance and repair of complex systems is produced based on a computational structure called the Informed Maintenance Grid (IMG). This method provides solutions to the two fundamental problems in autonomic logistics: (1) unambiguous detection of deterioration or impending loss of function and (2) determination of the time remaining to perform maintenance or other corrective action based upon information from the system. The IMG provides a health determination over the medium-to-longterm operation of the system, from one or more days to years of study. The IMG is especially applicable to spacecraft and both piloted and autonomous aircraft, or industrial control processes.
A Three-Stage Enhanced Reactive Power and Voltage Optimization Method for High Penetration of Solar
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ke, Xinda; Huang, Renke; Vallem, Mallikarjuna R.
This paper presents a three-stage enhanced volt/var optimization method to stabilize voltage fluctuations in transmission networks by optimizing the usage of reactive power control devices. In contrast with existing volt/var optimization algorithms, the proposed method optimizes the voltage profiles of the system, while keeping the voltage and real power output of the generators as close to the original scheduling values as possible. This allows the method to accommodate realistic power system operation and market scenarios, in which the original generation dispatch schedule will not be affected. The proposed method was tested and validated on a modified IEEE 118-bus system withmore » photovoltaic data.« less
System and method for optimal load and source scheduling in context aware homes
DOE Office of Scientific and Technical Information (OSTI.GOV)
Shetty, Pradeep; Foslien Graber, Wendy; Mangsuli, Purnaprajna R.
A controller for controlling energy consumption in a home includes a constraints engine to define variables for multiple appliances in the home corresponding to various home modes and persona of an occupant of the home. A modeling engine models multiple paths of energy utilization of the multiple appliances to place the home into a desired state from a current context. An optimal scheduler receives the multiple paths of energy utilization and generates a schedule as a function of the multiple paths and a selected persona to place the home in a desired state.
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.
40 CFR 1065.303 - Summary of required calibration and verifications.
Code of Federal Regulations, 2014 CFR
2014-07-01
...: FID calibrationTHC FID optimization, and THC FID verification Calibrate all FID analyzers: upon initial installation and after major maintenance.Optimize and determine CH4 response for THC FID analyzers: upon initial installation and after major maintenance. Verify CH4 response for THC FID analyzers: upon...
Planning Risk-Based SQC Schedules for Bracketed Operation of Continuous Production Analyzers.
Westgard, James O; Bayat, Hassan; Westgard, Sten A
2018-02-01
To minimize patient risk, "bracketed" statistical quality control (SQC) is recommended in the new CLSI guidelines for SQC (C24-Ed4). Bracketed SQC requires that a QC event both precedes and follows (brackets) a group of patient samples. In optimizing a QC schedule, the frequency of QC or run size becomes an important planning consideration to maintain quality and also facilitate responsive reporting of results from continuous operation of high production analytic systems. Different plans for optimizing a bracketed SQC schedule were investigated on the basis of Parvin's model for patient risk and CLSI C24-Ed4's recommendations for establishing QC schedules. A Sigma-metric run size nomogram was used to evaluate different QC schedules for processes of different sigma performance. For high Sigma performance, an effective SQC approach is to employ a multistage QC procedure utilizing a "startup" design at the beginning of production and a "monitor" design periodically throughout production. Example QC schedules are illustrated for applications with measurement procedures having 6-σ, 5-σ, and 4-σ performance. Continuous production analyzers that demonstrate high σ performance can be effectively controlled with multistage SQC designs that employ a startup QC event followed by periodic monitoring or bracketing QC events. Such designs can be optimized to minimize the risk of harm to patients. © 2017 American Association for Clinical Chemistry.
Optimizing human activity patterns using global sensitivity analysis.
Fairchild, Geoffrey; Hickmann, Kyle S; Mniszewski, Susan M; Del Valle, Sara Y; Hyman, James M
2014-12-01
Implementing realistic activity patterns for a population is crucial for modeling, for example, disease spread, supply and demand, and disaster response. Using the dynamic activity simulation engine, DASim, we generate schedules for a population that capture regular (e.g., working, eating, and sleeping) and irregular activities (e.g., shopping or going to the doctor). We use the sample entropy (SampEn) statistic to quantify a schedule's regularity for a population. We show how to tune an activity's regularity by adjusting SampEn, thereby making it possible to realistically design activities when creating a schedule. The tuning process sets up a computationally intractable high-dimensional optimization problem. To reduce the computational demand, we use Bayesian Gaussian process regression to compute global sensitivity indices and identify the parameters that have the greatest effect on the variance of SampEn. We use the harmony search (HS) global optimization algorithm to locate global optima. Our results show that HS combined with global sensitivity analysis can efficiently tune the SampEn statistic with few search iterations. We demonstrate how global sensitivity analysis can guide statistical emulation and global optimization algorithms to efficiently tune activities and generate realistic activity patterns. Though our tuning methods are applied to dynamic activity schedule generation, they are general and represent a significant step in the direction of automated tuning and optimization of high-dimensional computer simulations.
NASA Astrophysics Data System (ADS)
Nasrum, A.; Pasaribu, U. S.; Husniah, H.
2016-02-01
This paper deals with maintenance service contract for a dump truck sold with a two-dimensional warranties. We consider a situation where an agent offers two maintenance contract options and the owner of the equipment has to select the optimal option either the OEM carried out all repairs and preventive maintenance activities (option one) or the OEM only carries out failure while the costumer undertakes preventive maintenance action in-house (option two). As the number of preventive maintenance and corrective maintenance that occurs in the area of servicing contracts is very influential in determining the value of the contract, we have to determine the optimal time between preventive maintenance that can minimize the cost of repair in the contract area. Moreover, we also study the maintenance service contract considering reduction of the intensity function after preventive maintenance from both the owner and OEM point of views. In this paper, we use a Weibull intensity function to consider a product with increasing failure intensity. We use a non-cooperative game formulation to determine the optimal price structure (i.e., the contract price and repair cost) for the OEM and the owner. A numerical example derived from the model has shown that if the owner choose option one then the owner obtain a higher profit compared with the profit resulted from option two. The result agree with earlier work which uses the accelerated failure time (AFT) for the failure modeling, while here we model the failure of the dump truck without the use of the AFT.
Integrating Reservations and Queuing in Remote Laboratory Scheduling
ERIC Educational Resources Information Center
Lowe, D.
2013-01-01
Remote laboratories (RLs) have become increasingly seen as a useful tool in supporting flexible shared access to scarce laboratory resources. An important element in supporting shared access is coordinating the scheduling of the laboratory usage. Optimized scheduling can significantly decrease access waiting times and improve the utilization level…
Irrigation scheduling by ET and soil water sensing
USDA-ARS?s Scientific Manuscript database
Irrigation scheduling is the process of deciding when, where and how much to irrigate, usually with the goal of optimizing economic return on investment in land, equipment, inputs and personnel. This hour-long seminar presents methods of irrigation scheduling based, on the one hand on estimates of t...
DOT National Transportation Integrated Search
2016-06-01
The purpose of this project is to study the optimal scheduling of work zones so that they have minimum negative impact (e.g., travel delay, gas consumption, accidents, etc.) on transport service vehicle flows. In this project, a mixed integer linear ...
Naval Postgraduate School Scheduling Support System (NPS4)
1992-03-01
NPSS ...... .................. 156 2. Final Exam Scheduler .. .......... 159 F. PRESENTATION SYSTEM ... ............. . 160 G. USER INTERFACE... NPSS ...... .................. 185 2. Final Exam Model ... ............ 186 3. The Class Schedulers .. .......... 186 4. Assessment of Problem Model...Information Distribution ....... 150 4.13 NPSS Optimization Process .... ............ . 157 4.14 NPSS Performance ..... ................ . 159 4.15 Department
Evolutionary Scheduler for the Deep Space Network
NASA Technical Reports Server (NTRS)
Guillaume, Alexandre; Lee, Seungwon; Wang, Yeou-Fang; Zheng, Hua; Chau, Savio; Tung, Yu-Wen; Terrile, Richard J.; Hovden, Robert
2010-01-01
A computer program assists human schedulers in satisfying, to the maximum extent possible, competing demands from multiple spacecraft missions for utilization of the transmitting/receiving Earth stations of NASA s Deep Space Network. The program embodies a concept of optimal scheduling to attain multiple objectives in the presence of multiple constraints.
Dietz, Dennis C.
2014-01-01
A cogent method is presented for computing the expected cost of an appointment schedule where customers are statistically identical, the service time distribution has known mean and variance, and customer no-shows occur with time-dependent probability. The approach is computationally efficient and can be easily implemented to evaluate candidate schedules within a schedule optimization algorithm. PMID:24605070
The Microcomputer and School Transportation.
ERIC Educational Resources Information Center
Dembowski, Frederick L.
1984-01-01
Microcomputers have many cost- and time-saving uses in school transportation management. Applications include routing and scheduling, demographic analysis, fleet maintenance, and personnel and contract management. Word processing is especially promising for storing and updating documents like specifications. Enrollment forecasting and inventory…
Software For Integer Programming
NASA Technical Reports Server (NTRS)
Fogle, F. R.
1992-01-01
Improved Exploratory Search Technique for Pure Integer Linear Programming Problems (IESIP) program optimizes objective function of variables subject to confining functions or constraints, using discrete optimization or integer programming. Enables rapid solution of problems up to 10 variables in size. Integer programming required for accuracy in modeling systems containing small number of components, distribution of goods, scheduling operations on machine tools, and scheduling production in general. Written in Borland's TURBO Pascal.
Fog computing job scheduling optimization based on bees swarm
NASA Astrophysics Data System (ADS)
Bitam, Salim; Zeadally, Sherali; Mellouk, Abdelhamid
2018-04-01
Fog computing is a new computing architecture, composed of a set of near-user edge devices called fog nodes, which collaborate together in order to perform computational services such as running applications, storing an important amount of data, and transmitting messages. Fog computing extends cloud computing by deploying digital resources at the premise of mobile users. In this new paradigm, management and operating functions, such as job scheduling aim at providing high-performance, cost-effective services requested by mobile users and executed by fog nodes. We propose a new bio-inspired optimization approach called Bees Life Algorithm (BLA) aimed at addressing the job scheduling problem in the fog computing environment. Our proposed approach is based on the optimized distribution of a set of tasks among all the fog computing nodes. The objective is to find an optimal tradeoff between CPU execution time and allocated memory required by fog computing services established by mobile users. Our empirical performance evaluation results demonstrate that the proposal outperforms the traditional particle swarm optimization and genetic algorithm in terms of CPU execution time and allocated memory.
Optimal non-linear health insurance.
Blomqvist, A
1997-06-01
Most theoretical and empirical work on efficient health insurance has been based on models with linear insurance schedules (a constant co-insurance parameter). In this paper, dynamic optimization techniques are used to analyse the properties of optimal non-linear insurance schedules in a model similar to one originally considered by Spence and Zeckhauser (American Economic Review, 1971, 61, 380-387) and reminiscent of those that have been used in the literature on optimal income taxation. The results of a preliminary numerical example suggest that the welfare losses from the implicit subsidy to employer-financed health insurance under US tax law may be a good deal smaller than previously estimated using linear models.
Contribution to the Optimization of Strategy of Maintenance by Lean Six Sigma
NASA Astrophysics Data System (ADS)
Youssouf, Ayadi; Rachid, Chaib; Ion, Verzea
The efficiency of the maintenance of the industrial systems is a major economic stake for their business concern. The main difficulties and the sources of ineffectiveness live in the choice of the actions of maintenance especially when the machine plays a vital role in the process of production. But as Algeria has embarked on major infrastructure projects in transport, housing, automobile, manufacturing industry and construction (factories, housing, highway, subway, tram, etc.) requiring new implications on maintenance strategies that meet industry requirements imposed by the exploitation. From then on and seen the importance of the maintenance on the economic market and sound impacts on the performances of the installations, methods of optimization were developed. For this purpose, to ensure the survival of businesses, be credible, contributing and competitive in the market, maintenance services must continually adapt to the progress of technical areas, technological and organizational even help maintenance managers to construct or to modify maintenance strategies, objective of this work. Our contribution in this work focuses on the optimization of maintenance for industrial systems by the use of Lean six Sigma bases. Lean Six Sigma is a method of improving the quality and profitability based on mastering statically of process and it is also a management style that based on a highly regulated organization dedicated to managing project. The method is based on five main steps summarized in the acronym (DMAIC): Define Measure, Analyze, Improve and Control. Application of the method on the maintenance processes with using maintenance methods during the five phases of the method will help to reduce costs and losses in order to strive for optimum results in terms of profit and quality.
Reducing maintenance costs in agreement with CNC machine tools reliability
NASA Astrophysics Data System (ADS)
Ungureanu, A. L.; Stan, G.; Butunoi, P. A.
2016-08-01
Aligning maintenance strategy with reliability is a challenge due to the need to find an optimal balance between them. Because the various methods described in the relevant literature involve laborious calculations or use of software that can be costly, this paper proposes a method that is easier to implement on CNC machine tools. The new method, called the Consequence of Failure Analysis (CFA) is based on technical and economic optimization, aimed at obtaining a level of required performance with minimum investment and maintenance costs.
Borescope Inspection Management for Engine
NASA Astrophysics Data System (ADS)
Zhongda, Yuan
2018-03-01
In this paper, we try to explain the problems need to be improved from the two perspectives of maintenance program management and maintenance human risk control. On the basis of optimization analysis of borescope inspection maintenance scheme, the defect characteristics and expansion rules of engine heat terminal components are summarized, and some optimization measures are introduced. This paper analyses human risk problem of engine hole from the aspects of qualification management, training requirements and perfection of system, and puts forward some suggestions on management.
Bandwidth reduction for video-on-demand broadcasting using secondary content insertion
NASA Astrophysics Data System (ADS)
Golynski, Alexander; Lopez-Ortiz, Alejandro; Poirier, Guillaume; Quimper, Claude-Guy
2005-01-01
An optimal broadcasting scheme under the presence of secondary content (i.e. advertisements) is proposed. The proposed scheme works both for movies encoded in a Constant Bit Rate (CBR) or a Variable Bit Rate (VBR) format. It is shown experimentally that secondary content in movies can make Video-on-Demand (VoD) broadcasting systems more efficient. An efficient algorithm is given to compute the optimal broadcasting schedule with secondary content, which in particular significantly improves over the best previously known algorithm for computing the optimal broadcasting schedule without secondary content.
2009-07-01
Comments from the Department of Defense 33 Appendix IV GAO Contact and Staff Acknowledgments 36 Related GAO Products 37 Tables Table...work of the U.S. government and is not subject to copyright protection in the United States. The published product may be reproduced and distributed in...disrupting maintenance production schedules due to personnel transfers since the employees are already experienced in performing these jobs. DLA Has
NASA Astrophysics Data System (ADS)
Sahelgozin, M.; Alimohammadi, A.
2015-12-01
Increasing distances between locations of residence and services leads to a large number of daily commutes in urban areas. Developing subway systems has been taken into consideration of transportation managers as a response to this huge amount of travel demands. In developments of subway infrastructures, representing a temporal schedule for trains is an important task; because an appropriately designed timetable decreases Total passenger travel times, Total Operation Costs and Energy Consumption of trains. Since these variables are not positively correlated, subway scheduling is considered as a multi-criteria optimization problem. Therefore, proposing a proper solution for subway scheduling has been always a controversial issue. On the other hand, research on a phenomenon requires a summarized representation of the real world that is known as Model. In this study, it is attempted to model temporal schedule of urban trains that can be applied in Multi-Criteria Subway Schedule Optimization (MCSSO) problems. At first, a conceptual framework is represented for MCSSO. Then, an agent-based simulation environment is implemented to perform Sensitivity Analysis (SA) that is used to extract the interrelations between the framework components. These interrelations is then taken into account in order to construct the proposed model. In order to evaluate performance of the model in MCSSO problems, Tehran subway line no. 1 is considered as the case study. Results of the study show that the model was able to generate an acceptable distribution of Pareto-optimal solutions which are applicable in the real situations while solving a MCSSO is the goal. Also, the accuracy of the model in representing the operation of subway systems was significant.
Multi-time Scale Joint Scheduling Method Considering the Grid of Renewable Energy
NASA Astrophysics Data System (ADS)
Zhijun, E.; Wang, Weichen; Cao, Jin; Wang, Xin; Kong, Xiangyu; Quan, Shuping
2018-01-01
Renewable new energy power generation prediction error like wind and light, brings difficulties to dispatch the power system. In this paper, a multi-time scale robust scheduling method is set to solve this problem. It reduces the impact of clean energy prediction bias to the power grid by using multi-time scale (day-ahead, intraday, real time) and coordinating the dispatching power output of various power supplies such as hydropower, thermal power, wind power, gas power and. The method adopts the robust scheduling method to ensure the robustness of the scheduling scheme. By calculating the cost of the abandon wind and the load, it transforms the robustness into the risk cost and optimizes the optimal uncertainty set for the smallest integrative costs. The validity of the method is verified by simulation.
Dataflow Design Tool: User's Manual
NASA Technical Reports Server (NTRS)
Jones, Robert L., III
1996-01-01
The Dataflow Design Tool is a software tool for selecting a multiprocessor scheduling solution for a class of computational problems. The problems of interest are those that can be described with a dataflow graph and are intended to be executed repetitively on a set of identical processors. Typical applications include signal processing and control law problems. The software tool implements graph-search algorithms and analysis techniques based on the dataflow paradigm. Dataflow analyses provided by the software are introduced and shown to effectively determine performance bounds, scheduling constraints, and resource requirements. The software tool provides performance optimization through the inclusion of artificial precedence constraints among the schedulable tasks. The user interface and tool capabilities are described. Examples are provided to demonstrate the analysis, scheduling, and optimization functions facilitated by the tool.
Open shop scheduling problem to minimize total weighted completion time
NASA Astrophysics Data System (ADS)
Bai, Danyu; Zhang, Zhihai; Zhang, Qiang; Tang, Mengqian
2017-01-01
A given number of jobs in an open shop scheduling environment must each be processed for given amounts of time on each of a given set of machines in an arbitrary sequence. This study aims to achieve a schedule that minimizes total weighted completion time. Owing to the strong NP-hardness of the problem, the weighted shortest processing time block (WSPTB) heuristic is presented to obtain approximate solutions for large-scale problems. Performance analysis proves the asymptotic optimality of the WSPTB heuristic in the sense of probability limits. The largest weight block rule is provided to seek optimal schedules in polynomial time for a special case. A hybrid discrete differential evolution algorithm is designed to obtain high-quality solutions for moderate-scale problems. Simulation experiments demonstrate the effectiveness of the proposed algorithms.
Artificial Intelligent Platform as Decision Tool for Asset Management, Operations and Maintenance.
2018-01-04
An Artificial Intelligence (AI) system has been developed and implemented for water, wastewater and reuse plants to improve management of sensors, short and long term maintenance plans, asset and investment management plans. It is based on an integrated approach to capture data from different computer systems and files. It adds a layer of intelligence to the data. It serves as a repository of key current and future operations and maintenance conditions that a plant needs have knowledge of. With this information, it is able to simulate the configuration of processes and assets for those conditions to improve or optimize operations, maintenance and asset management, using the IViewOps (Intelligent View of Operations) model. Based on the optimization through model runs, it is able to create output files that can feed data to other systems and inform the staff regarding optimal solutions to the conditions experienced or anticipated in the future.
IMIS: Integrated Maintenance Information System. A maintenance information delivery concept
NASA Technical Reports Server (NTRS)
Vonholle, Joseph C.
1987-01-01
The Integrated Maintenance Information System (IMIS) will optimize the use of available manpower, enhance technical performance, improve training, and reduce the support equipment and documentation needed for deployment. It will serve as the technician's single, integrated source of all the technical information required to perform modern aircraft maintenance.
Bankole, Temitayo; Jones, Dustin; Bhattacharyya, Debangsu; ...
2017-11-03
In this study, a two-level control methodology consisting of an upper-level scheduler and a lower-level supervisory controller is proposed for an advanced load-following energy plant with CO 2 capture. With the use of an economic objective function that considers fluctuation in electricity demand and price at the upper level, optimal scheduling of energy plant electricity production and carbon capture with respect to several carbon tax scenarios is implemented. The optimal operational profiles are then passed down to corresponding lower-level supervisory controllers designed using a methodological approach that balances control complexity with performance. Finally, it is shown how optimal carbon capturemore » and electricity production rate profiles for an energy plant such as the integrated gasification combined cycle (IGCC) plant are affected by electricity demand and price fluctuations under different carbon tax scenarios. As a result, the paper also presents a Lyapunov stability analysis of the proposed scheme.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Bankole, Temitayo; Jones, Dustin; Bhattacharyya, Debangsu
In this study, a two-level control methodology consisting of an upper-level scheduler and a lower-level supervisory controller is proposed for an advanced load-following energy plant with CO 2 capture. With the use of an economic objective function that considers fluctuation in electricity demand and price at the upper level, optimal scheduling of energy plant electricity production and carbon capture with respect to several carbon tax scenarios is implemented. The optimal operational profiles are then passed down to corresponding lower-level supervisory controllers designed using a methodological approach that balances control complexity with performance. Finally, it is shown how optimal carbon capturemore » and electricity production rate profiles for an energy plant such as the integrated gasification combined cycle (IGCC) plant are affected by electricity demand and price fluctuations under different carbon tax scenarios. As a result, the paper also presents a Lyapunov stability analysis of the proposed scheme.« less
A COTS-Based Attitude Dependent Contact Scheduling System
NASA Technical Reports Server (NTRS)
DeGumbia, Jonathan D.; Stezelberger, Shane T.; Woodard, Mark
2006-01-01
The mission architecture of the Gamma-ray Large Area Space Telescope (GLAST) requires a sophisticated ground system component for scheduling the downlink of science data. Contacts between the ````````````````` satellite and the Tracking and Data Relay Satellite System (TDRSS) are restricted by the limited field-of-view of the science data downlink antenna. In addition, contacts must be scheduled when permitted by the satellite s complex and non-repeating attitude profile. Complicating the matter further, the long lead-time required to schedule TDRSS services, combined with the short duration of the downlink contact opportunities, mandates accurate GLAST orbit and attitude modeling. These circumstances require the development of a scheduling system that is capable of predictively and accurately modeling not only the orbital position of GLAST but also its attitude. This paper details the methods used in the design of a Commercial Off The Shelf (COTS)-based attitude-dependent. TDRSS contact Scheduling system that meets the unique scheduling requirements of the GLAST mission, and it suggests a COTS-based scheduling approach to support future missions. The scheduling system applies filtering and smoothing algorithms to telemetered GPS data to produce high-accuracy predictive GLAST orbit ephemerides. Next, bus pointing commands from the GLAST Science Support Center are used to model the complexities of the two dynamic science gathering attitude modes. Attitude-dependent view periods are then generated between GLAST and each of the supporting TDRSs. Numerous scheduling constraints are then applied to account for various mission specific resource limitations. Next, an optimization engine is used to produce an optimized TDRSS contact schedule request which is sent to TDRSS scheduling for confirmation. Lastly, the confirmed TDRSS contact schedule is rectified with an updated ephemeris and adjusted bus pointing commands to produce a final science downlink contact schedule.
NASA Astrophysics Data System (ADS)
Seo, Junyeong; Sung, Youngchul
2018-06-01
In this paper, an efficient transmit beam design and user scheduling method is proposed for multi-user (MU) multiple-input single-output (MISO) non-orthogonal multiple access (NOMA) downlink, based on Pareto-optimality. The proposed beam design and user scheduling method groups simultaneously-served users into multiple clusters with practical two users in each cluster, and then applies spatical zeroforcing (ZF) across clusters to control inter-cluster interference (ICI) and Pareto-optimal beam design with successive interference cancellation (SIC) to two users in each cluster to remove interference to strong users and leverage signal-to-interference-plus-noise ratios (SINRs) of interference-experiencing weak users. The proposed method has flexibility to control the rates of strong and weak users and numerical results show that the proposed method yields good performance.
NASA Astrophysics Data System (ADS)
Hsieh, Tsu-Pang; Cheng, Mei-Chuan; Dye, Chung-Yuan; Ouyang, Liang-Yuh
2011-01-01
In this article, we extend the classical economic production quantity (EPQ) model by proposing imperfect production processes and quality-dependent unit production cost. The demand rate is described by any convex decreasing function of the selling price. In addition, we allow for shortages and a time-proportional backlogging rate. For any given selling price, we first prove that the optimal production schedule not only exists but also is unique. Next, we show that the total profit per unit time is a concave function of price when the production schedule is given. We then provide a simple algorithm to find the optimal selling price and production schedule for the proposed model. Finally, we use a couple of numerical examples to illustrate the algorithm and conclude this article with suggestions for possible future research.
Optimal scheduling of micro grids based on single objective programming
NASA Astrophysics Data System (ADS)
Chen, Yue
2018-04-01
Faced with the growing demand for electricity and the shortage of fossil fuels, how to optimally optimize the micro-grid has become an important research topic to maximize the economic, technological and environmental benefits of the micro-grid. This paper considers the role of the battery and the micro-grid and power grid to allow the exchange of power not exceeding 150kW preconditions, the main study of the economy to load for the goal is to minimize the electricity cost (abandonment of wind), to establish an optimization model, and to solve the problem by genetic algorithm. The optimal scheduling scheme is obtained and the utilization of renewable energy and the impact of the battery involved in regulation are analyzed.
Research on logistics scheduling based on PSO
NASA Astrophysics Data System (ADS)
Bao, Huifang; Zhou, Linli; Liu, Lei
2017-08-01
With the rapid development of e-commerce based on the network, the logistics distribution support of e-commerce is becoming more and more obvious. The optimization of vehicle distribution routing can improve the economic benefit and realize the scientific of logistics [1]. Therefore, the study of logistics distribution vehicle routing optimization problem is not only of great theoretical significance, but also of considerable value of value. Particle swarm optimization algorithm is a kind of evolutionary algorithm, which is based on the random solution and the optimal solution by iteration, and the quality of the solution is evaluated through fitness. In order to obtain a more ideal logistics scheduling scheme, this paper proposes a logistics model based on particle swarm optimization algorithm.
The Business Change Initiative: A Novel Approach to Improved Cost and Schedule Management
NASA Technical Reports Server (NTRS)
Shinn, Stephen A.; Bryson, Jonathan; Klein, Gerald; Lunz-Ruark, Val; Majerowicz, Walt; McKeever, J.; Nair, Param
2016-01-01
Goddard Space Flight Center's Flight Projects Directorate employed a Business Change Initiative (BCI) to infuse a series of activities coordinated to drive improved cost and schedule performance across Goddard's missions. This sustaining change framework provides a platform to manage and implement cost and schedule control techniques throughout the project portfolio. The BCI concluded in December 2014, deploying over 100 cost and schedule management changes including best practices, tools, methods, training, and knowledge sharing. The new business approach has driven the portfolio to improved programmatic performance. The last eight launched GSFC missions have optimized cost, schedule, and technical performance on a sustained basis to deliver on time and within budget, returning funds in many cases. While not every future mission will boast such strong performance, improved cost and schedule tools, management practices, and ongoing comprehensive evaluations of program planning and control methods to refine and implement best practices will continue to provide a framework for sustained performance. This paper will describe the tools, techniques, and processes developed during the BCI and the utilization of collaborative content management tools to disseminate project planning and control techniques to ensure continuous collaboration and optimization of cost and schedule management in the future.
The nurse scheduling problem: a goal programming and nonlinear optimization approaches
NASA Astrophysics Data System (ADS)
Hakim, L.; Bakhtiar, T.; Jaharuddin
2017-01-01
Nurses scheduling is an activity of allocating nurses to conduct a set of tasks at certain room at a hospital or health centre within a certain period. One of obstacles in the nurse scheduling is the lack of resources in order to fulfil the needs of the hospital. Nurse scheduling which is undertaken manually will be at risk of not fulfilling some nursing rules set by the hospital. Therefore, this study aimed to perform scheduling models that satisfy all the specific rules set by the management of Bogor State Hospital. We have developed three models to overcome the scheduling needs. Model 1 is designed to schedule nurses who are solely assigned to a certain inpatient unit and Model 2 is constructed to manage nurses who are assigned to an inpatient room as well as at Polyclinic room as conjunct nurses. As the assignment of nurses on each shift is uneven, then we propose Model 3 to minimize the variance of the workload in order to achieve equitable assignment on every shift. The first two models are formulated in goal programming framework, while the last model is in nonlinear optimization form.
Optimizing an F-16 Squadron Weekly Pilot Schedule for the Turkish Air Force
2010-03-01
disrupted schedules are rescheduled , minimizing the total number of changes with respect to the previous schedule’s objective function. Output...producing rosters for a nursing staff in a large general hospital (Dowsland, 1998) and afterwards Aickelin and Dowsland use an Indirect Genetic...algorithm to improve the solutions of the nurse scheduling problem which is similar to the fighter squadron pilot scheduling problem (Aickelin and
Optimization of nas lemoore scheduling to support a growing aircraft population
2017-03-01
requirements, and, without knowing the other squadrons’ flight plans , creates his or her squadron’s flight schedule. Figure 2 illustrates the process each...Lemoore, they do not communicate their flight schedules among themselves; hence, the daily flight plan generated by each squadron is independently...manual process for aircraft flight scheduling at Naval Air Station (NAS) Lemoore accommodates the independent needs of 16 fighter resident squadrons as
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
ERIC Educational Resources Information Center
Lewis, Barbara
1982-01-01
Beginning on the front cover, this article tells how school districts are reducing their transportation costs. Particularly effective measures include the use of computers for bus maintenance and scheduling, school board ownership of buses, and the conversion of gasoline-powered buses to alternative fuels. (Author/MLF)
Energy latency tradeoffs for medium access and sleep scheduling in wireless sensor networks
NASA Astrophysics Data System (ADS)
Gang, Lu
Wireless sensor networks are expected to be used in a wide range of applications from environment monitoring to event detection. The key challenge is to provide energy efficient communication; however, latency remains an important concern for many applications that require fast response. The central thesis of this work is that energy efficient medium access and sleep scheduling mechanisms can be designed without necessarily sacrificing application-specific latency performance. We validate this thesis through results from four case studies that cover various aspects of medium access and sleep scheduling design in wireless sensor networks. Our first effort, DMAC, is to design an adaptive low latency and energy efficient MAC for data gathering to reduce the sleep latency. We propose staggered schedule, duty cycle adaptation, data prediction and the use of more-to-send packets to enable seamless packet forwarding under varying traffic load and channel contentions. Simulation and experimental results show significant energy savings and latency reduction while ensuring high data reliability. The second research effort, DESS, investigates the problem of designing sleep schedules in arbitrary network communication topologies to minimize the worst case end-to-end latency (referred to as delay diameter). We develop a novel graph-theoretical formulation, derive and analyze optimal solutions for the tree and ring topologies and heuristics for arbitrary topologies. The third study addresses the problem of minimum latency joint scheduling and routing (MLSR). By constructing a novel delay graph, the optimal joint scheduling and routing can be solved by M node-disjoint paths algorithm under multiple channel model. We further extended the algorithm to handle dynamic traffic changes and topology changes. A heuristic solution is proposed for MLSR under single channel interference. In the fourth study, EEJSPC, we first formulate a fundamental optimization problem that provides tunable energy-latency-throughput tradeoffs with joint scheduling and power control and present both exponential and polynomial complexity solutions. Then we investigate the problem of minimizing total transmission energy while satisfying transmission requests within a latency bound, and present an iterative approach which converges rapidly to the optimal parameter settings.
Study of turboprop systems reliability and maintenance costs
NASA Technical Reports Server (NTRS)
1978-01-01
The overall reliability and maintenance costs (R&MC's) of past and current turboprop systems were examined. Maintenance cost drivers were found to be scheduled overhaul (40%), lack of modularity particularly in the propeller and reduction gearbox, and lack of inherent durability (reliability) of some parts. Comparisons were made between the 501-D13/54H60 turboprop system and the widely used JT8D turbofan. It was found that the total maintenance cost per flight hour of the turboprop was 75% higher than that of the JT8D turbofan. Part of this difference was due to propeller and gearbox costs being higher than those of the fan and reverser, but most of the difference was in the engine core where the older technology turboprop core maintenance costs were nearly 70 percent higher than for the turbofan. The estimated maintenance cost of both the advanced turboprop and advanced turbofan were less than the JT8D. The conclusion was that an advanced turboprop and an advanced turbofan, using similar cores, will have very competitive maintenance costs per flight hour.
User’s guide to SNAP for ArcGIS® :ArcGIS interface for scheduling and network analysis program
Woodam Chung; Dennis Dykstra; Fred Bower; Stephen O’Brien; Richard Abt; John. and Sessions
2012-01-01
This document introduces a computer software named SNAP for ArcGIS® , which has been developed to streamline scheduling and transportation planning for timber harvest areas. Using modern optimization techniques, it can be used to spatially schedule timber harvest with consideration of harvesting costs, multiple products, alternative...
NASA Technical Reports Server (NTRS)
Chang, H.
1976-01-01
A computer program using Lemke, Salkin and Spielberg's Set Covering Algorithm (SCA) to optimize a traffic model problem in the Scheduling Algorithm for Mission Planning and Logistics Evaluation (SAMPLE) was documented. SCA forms a submodule of SAMPLE and provides for input and output, subroutines, and an interactive feature for performing the optimization and arranging the results in a readily understandable form for output.
Model-based optimization of G-CSF treatment during cytotoxic chemotherapy.
Schirm, Sibylle; Engel, Christoph; Loibl, Sibylle; Loeffler, Markus; Scholz, Markus
2018-02-01
Although G-CSF is widely used to prevent or ameliorate leukopenia during cytotoxic chemotherapies, its optimal use is still under debate and depends on many therapy parameters such as dosing and timing of cytotoxic drugs and G-CSF, G-CSF pharmaceuticals used and individual risk factors of patients. We integrate available biological knowledge and clinical data regarding cell kinetics of bone marrow granulopoiesis, the cytotoxic effects of chemotherapy and pharmacokinetics and pharmacodynamics of G-CSF applications (filgrastim or pegfilgrastim) into a comprehensive model. The model explains leukocyte time courses of more than 70 therapy scenarios comprising 10 different cytotoxic drugs. It is applied to develop optimized G-CSF schedules for a variety of clinical scenarios. Clinical trial results showed validity of model predictions regarding alternative G-CSF schedules. We propose modifications of G-CSF treatment for the chemotherapies 'BEACOPP escalated' (Hodgkin's disease), 'ETC' (breast cancer), and risk-adapted schedules for 'CHOP-14' (aggressive non-Hodgkin's lymphoma in elderly patients). We conclude that we established a model of human granulopoiesis under chemotherapy which allows predictions of yet untested G-CSF schedules, comparisons between them, and optimization of filgrastim and pegfilgrastim treatment. As a general rule of thumb, G-CSF treatment should not be started too early and patients could profit from filgrastim treatment continued until the end of the chemotherapy cycle.
Scheduling Jobs with Variable Job Processing Times on Unrelated Parallel Machines
Zhang, Guang-Qian; Wang, Jian-Jun; Liu, Ya-Jing
2014-01-01
m unrelated parallel machines scheduling problems with variable job processing times are considered, where the processing time of a job is a function of its position in a sequence, its starting time, and its resource allocation. The objective is to determine the optimal resource allocation and the optimal schedule to minimize a total cost function that dependents on the total completion (waiting) time, the total machine load, the total absolute differences in completion (waiting) times on all machines, and total resource cost. If the number of machines is a given constant number, we propose a polynomial time algorithm to solve the problem. PMID:24982933
Hubble Systems Optimize Hospital Schedules
NASA Technical Reports Server (NTRS)
2009-01-01
Don Rosenthal, a former Ames Research Center computer scientist who helped design the Hubble Space Telescope's scheduling software, co-founded Allocade Inc. of Menlo Park, California, in 2004. Allocade's OnCue software helps hospitals reclaim unused capacity and optimize constantly changing schedules for imaging procedures. After starting to use the software, one medical center soon reported noticeable improvements in efficiency, including a 12 percent increase in procedure volume, 35 percent reduction in staff overtime, and significant reductions in backlog and technician phone time. Allocade now offers versions for outpatient and inpatient magnetic resonance imaging (MRI), ultrasound, interventional radiology, nuclear medicine, Positron Emission Tomography (PET), radiography, radiography-fluoroscopy, and mammography.
(n, N) type maintenance policy for multi-component systems with failure interactions
NASA Astrophysics Data System (ADS)
Zhang, Zhuoqi; Wu, Su; Li, Binfeng; Lee, Seungchul
2015-04-01
This paper studies maintenance policies for multi-component systems in which failure interactions and opportunistic maintenance (OM) involve. This maintenance problem can be formulated as a Markov decision process (MDP). However, since an action set and state space in MDP exponentially expand as the number of components increase, traditional approaches are computationally intractable. To deal with curse of dimensionality, we decompose such a multi-component system into mutually influential single-component systems. Each single-component system is formulated as an MDP with the objective of minimising its long-run average maintenance cost. Under some reasonable assumptions, we prove the existence of the optimal (n, N) type policy for a single-component system. An algorithm to obtain the optimal (n, N) type policy is also proposed. Based on the proposed algorithm, we develop an iterative approximation algorithm to obtain an acceptable maintenance policy for a multi-component system. Numerical examples find that failure interactions and OM pose significant effects on a maintenance policy.
Cascaded Optimization for a Persistent Data Ferrying Unmanned Aircraft
NASA Astrophysics Data System (ADS)
Carfang, Anthony
This dissertation develops and assesses a cascaded method for designing optimal periodic trajectories and link schedules for an unmanned aircraft to ferry data between stationary ground nodes. This results in a fast solution method without the need to artificially constrain system dynamics. Focusing on a fundamental ferrying problem that involves one source and one destination, but includes complex vehicle and Radio-Frequency (RF) dynamics, a cascaded structure to the system dynamics is uncovered. This structure is exploited by reformulating the nonlinear optimization problem into one that reduces the independent control to the vehicle's motion, while the link scheduling control is folded into the objective function and implemented as an optimal policy that depends on candidate motion control. This formulation is proven to maintain optimality while reducing computation time in comparison to traditional ferry optimization methods. The discrete link scheduling problem takes the form of a combinatorial optimization problem that is known to be NP-Hard. A derived necessary condition for optimality guides the development of several heuristic algorithms, specifically the Most-Data-First Algorithm and the Knapsack Adaptation. These heuristics are extended to larger ferrying scenarios, and assessed analytically and through Monte Carlo simulation, showing better throughput performance in the same order of magnitude of computation time in comparison to other common link scheduling policies. The cascaded optimization method is implemented with a novel embedded software system on a small, unmanned aircraft to validate the simulation results with field experiments. To address the sensitivity of results on trajectory tracking performance, a system that combines motion and link control with waypoint-based navigation is developed and assessed through field experiments. The data ferrying algorithms are further extended by incorporating a Gaussian process to opportunistically learn the RF environment. By continuously improving RF models, the cascaded planner can continually improve the ferrying system's overall performance.
Genetic algorithm to solve the problems of lectures and practicums scheduling
NASA Astrophysics Data System (ADS)
Syahputra, M. F.; Apriani, R.; Sawaluddin; Abdullah, D.; Albra, W.; Heikal, M.; Abdurrahman, A.; Khaddafi, M.
2018-02-01
Generally, the scheduling process is done manually. However, this method has a low accuracy level, along with possibilities that a scheduled process collides with another scheduled process. When doing theory class and practicum timetable scheduling process, there are numerous problems, such as lecturer teaching schedule collision, schedule collision with another schedule, practicum lesson schedules that collides with theory class, and the number of classrooms available. In this research, genetic algorithm is implemented to perform theory class and practicum timetable scheduling process. The algorithm will be used to process the data containing lists of lecturers, courses, and class rooms, obtained from information technology department at University of Sumatera Utara. The result of scheduling process using genetic algorithm is the most optimal timetable that conforms to available time slots, class rooms, courses, and lecturer schedules.
Minimizing metastatic risk in radiotherapy fractionation schedules
NASA Astrophysics Data System (ADS)
Badri, Hamidreza; Ramakrishnan, Jagdish; Leder, Kevin
2015-11-01
Metastasis is the process by which cells from a primary tumor disperse and form new tumors at distant anatomical locations. The treatment and prevention of metastatic cancer remains an extremely challenging problem. This work introduces a novel biologically motivated objective function to the radiation optimization community that takes into account metastatic risk instead of the status of the primary tumor. In this work, we consider the problem of developing fractionated irradiation schedules that minimize production of metastatic cancer cells while keeping normal tissue damage below an acceptable level. A dynamic programming framework is utilized to determine the optimal fractionation scheme. We evaluated our approach on a breast cancer case using the heart and the lung as organs-at-risk (OAR). For small tumor α /β values, hypo-fractionated schedules were optimal, which is consistent with standard models. However, for relatively larger α /β values, we found the type of schedule depended on various parameters such as the time when metastatic risk was evaluated, the α /β values of the OARs, and the normal tissue sparing factors. Interestingly, in contrast to standard models, hypo-fractionated and semi-hypo-fractionated schedules (large initial doses with doses tapering off with time) were suggested even with large tumor α/β values. Numerical results indicate the potential for significant reduction in metastatic risk.
Low-Cost Oil Quality Sensor Based on Changes in Complex Permittivity
Pérez, Angel Torres; Hadfield, Mark
2011-01-01
Real time oil quality monitoring techniques help to protect important industry assets, minimize downtime and reduce maintenance costs. The measurement of a lubricant’s complex permittivity is an effective indicator of the oil degradation process and it can be useful in condition based maintenance (CBM) to select the most adequate oil replacement maintenance schedules. A discussion of the working principles of an oil quality sensor based on a marginal oscillator to monitor the losses of the dielectric at high frequencies (>1 MHz) is presented. An electronic design procedure is covered which results in a low cost, effective and ruggedized sensor implementation suitable for use in harsh environments. PMID:22346666
NASA Technical Reports Server (NTRS)
Momoh, James; Chattopadhyay, Deb; Basheer, Omar Ali AL
1996-01-01
The space power system has two sources of energy: photo-voltaic blankets and batteries. The optimal power management problem on-board has two broad operations: off-line power scheduling to determine the load allocation schedule of the next several hours based on the forecast of load and solar power availability. The nature of this study puts less emphasis on speed requirement for computation and more importance on the optimality of the solution. The second category problem, on-line power rescheduling, is needed in the event of occurrence of a contingency to optimally reschedule the loads to minimize the 'unused' or 'wasted' energy while keeping the priority on certain type of load and minimum disturbance of the original optimal schedule determined in the first-stage off-line study. The computational performance of the on-line 'rescheduler' is an important criterion and plays a critical role in the selection of the appropriate tool. The Howard University Center for Energy Systems and Control has developed a hybrid optimization-expert systems based power management program. The pre-scheduler has been developed using a non-linear multi-objective optimization technique called the Outer Approximation method and implemented using the General Algebraic Modeling System (GAMS). The optimization model has the capability of dealing with multiple conflicting objectives viz. maximizing energy utilization, minimizing the variation of load over a day, etc. and incorporates several complex interaction between the loads in a space system. The rescheduling is performed using an expert system developed in PROLOG which utilizes a rule-base for reallocation of the loads in an emergency condition viz. shortage of power due to solar array failure, increase of base load, addition of new activity, repetition of old activity etc. Both the modules handle decision making on battery charging and discharging and allocation of loads over a time-horizon of a day divided into intervals of 10 minutes. The models have been extensively tested using a case study for the Space Station Freedom and the results for the case study will be presented. Several future enhancements of the pre-scheduler and the 'rescheduler' have been outlined which include graphic analyzer for the on-line module, incorporating probabilistic considerations, including spatial location of the loads and the connectivity using a direct current (DC) load flow model.
Efficiently Scheduling Multi-core Guest Virtual Machines on Multi-core Hosts in Network Simulation
DOE Office of Scientific and Technical Information (OSTI.GOV)
Yoginath, Srikanth B; Perumalla, Kalyan S
2011-01-01
Virtual machine (VM)-based simulation is a method used by network simulators to incorporate realistic application behaviors by executing actual VMs as high-fidelity surrogates for simulated end-hosts. A critical requirement in such a method is the simulation time-ordered scheduling and execution of the VMs. Prior approaches such as time dilation are less efficient due to the high degree of multiplexing possible when multiple multi-core VMs are simulated on multi-core host systems. We present a new simulation time-ordered scheduler to efficiently schedule multi-core VMs on multi-core real hosts, with a virtual clock realized on each virtual core. The distinguishing features of ourmore » approach are: (1) customizable granularity of the VM scheduling time unit on the simulation time axis, (2) ability to take arbitrary leaps in virtual time by VMs to maximize the utilization of host (real) cores when guest virtual cores idle, and (3) empirically determinable optimality in the tradeoff between total execution (real) time and time-ordering accuracy levels. Experiments show that it is possible to get nearly perfect time-ordered execution, with a slight cost in total run time, relative to optimized non-simulation VM schedulers. Interestingly, with our time-ordered scheduler, it is also possible to reduce the time-ordering error from over 50% of non-simulation scheduler to less than 1% realized by our scheduler, with almost the same run time efficiency as that of the highly efficient non-simulation VM schedulers.« less
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.
Gallucci, Luca; Menna, Costantino; Angrisani, Leopoldo; Asprone, Domenico; Moriello, Rosario Schiano Lo; Bonavolontà, Francesco; Fabbrocino, Francesco
2017-11-07
Maintenance strategies based on structural health monitoring can provide effective support in the optimization of scheduled repair of existing structures, thus enabling their lifetime to be extended. With specific regard to reinforced concrete (RC) structures, the state of the art seems to still be lacking an efficient and cost-effective technique capable of monitoring material properties continuously over the lifetime of a structure. Current solutions can typically only measure the required mechanical variables in an indirect, but economic, manner, or directly, but expensively. Moreover, most of the proposed solutions can only be implemented by means of manual activation, making the monitoring very inefficient and then poorly supported. This paper proposes a structural health monitoring system based on a wireless sensor network (WSN) that enables the automatic monitoring of a complete structure. The network includes wireless distributed sensors embedded in the structure itself, and follows the monitoring-based maintenance (MBM) approach, with its ABCDE paradigm, namely: accuracy, benefit, compactness, durability, and easiness of operations. The system is structured in a node level and has a network architecture that enables all the node data to converge in a central unit. Human control is completely unnecessary until the periodic evaluation of the collected data. Several tests are conducted in order to characterize the system from a metrological point of view and assess its performance and effectiveness in real RC conditions.
Autonomous Hybrid Priority Queueing for Scheduling Residential Energy Demands
NASA Astrophysics Data System (ADS)
Kalimullah, I. Q.; Shamroukh, M.; Sahar, N.; Shetty, S.
2017-05-01
The advent of smart grid technologies has opened up opportunities to manage the energy consumption of the users within a residential smart grid system. Demand response management is particularly being employed to reduce the overall load on an electricity network which could in turn reduce outages and electricity costs. The objective of this paper is to develop an intelligible scheduler to optimize the energy available to a micro grid through hybrid queueing algorithm centered around the consumers’ energy demands. This is achieved by shifting certain schedulable load appliances to light load hours. Various factors such as the type of demand, grid load, consumers’ energy usage patterns and preferences are considered while formulating the logical constraints required for the algorithm. The algorithm thus obtained is then implemented in MATLAB workspace to simulate its execution by an Energy Consumption Scheduler (ECS) found within smart meters, which automatically finds the optimal energy consumption schedule tailor made to fit each consumer within the micro grid network.
Using the principles of circadian physiology enhances shift schedule design
DOE Office of Scientific and Technical Information (OSTI.GOV)
Connolly, J.J.; Moore-Ede, M.C.
1987-01-01
Nuclear power plants must operate 24 h, 7 days a week. For the most part, shift schedules currently in use at nuclear power plants have been designed to meet operational needs without considering the biological clocks of the human operators. The development of schedules that also take circadian principles into account is a positive step that can be taken to improve plant safety by optimizing operator alertness. These schedules reduce the probability of human errors especially during backshifts. In addition, training programs that teach round-the-clock workers how to deal with the problems of shiftwork can help to optimize performance andmore » alertness. These programs teach shiftworkers the underlying causes of the sleep problems associated with shiftwork and also provide coping strategies for improving sleep and dealing with the transition between shifts. When these training programs are coupled with an improved schedule, the problems associated with working round-the-clock can be significantly reduced.« less
Neural Network Prediction of New Aircraft Design Coefficients
NASA Technical Reports Server (NTRS)
Norgaard, Magnus; Jorgensen, Charles C.; Ross, James C.
1997-01-01
This paper discusses a neural network tool for more effective aircraft design evaluations during wind tunnel tests. Using a hybrid neural network optimization method, we have produced fast and reliable predictions of aerodynamical coefficients, found optimal flap settings, and flap schedules. For validation, the tool was tested on a 55% scale model of the USAF/NASA Subsonic High Alpha Research Concept aircraft (SHARC). Four different networks were trained to predict coefficients of lift, drag, moment of inertia, and lift drag ratio (C(sub L), C(sub D), C(sub M), and L/D) from angle of attack and flap settings. The latter network was then used to determine an overall optimal flap setting and for finding optimal flap schedules.
Multi-time scale energy management of wind farms based on comprehensive evaluation technology
NASA Astrophysics Data System (ADS)
Xu, Y. P.; Huang, Y. H.; Liu, Z. J.; Wang, Y. F.; Li, Z. Y.; Guo, L.
2017-11-01
A novel energy management of wind farms is proposed in this paper. Firstly, a novel comprehensive evaluation system is proposed to quantify economic properties of each wind farm to make the energy management more economical and reasonable. Then, a combination of multi time-scale schedule method is proposed to develop a novel energy management. The day-ahead schedule optimizes unit commitment of thermal power generators. The intraday schedule is established to optimize power generation plan for all thermal power generating units, hydroelectric generating sets and wind power plants. At last, the power generation plan can be timely revised in the process of on-line schedule. The paper concludes with simulations conducted on a real provincial integrated energy system in northeast China. Simulation results have validated the proposed model and corresponding solving algorithms.
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
Artificial Bee Colony Optimization for Short-Term Hydrothermal Scheduling
NASA Astrophysics Data System (ADS)
Basu, M.
2014-12-01
Artificial bee colony optimization is applied to determine the optimal hourly schedule of power generation in a hydrothermal system. Artificial bee colony optimization is a swarm-based algorithm inspired by the food foraging behavior of honey bees. The algorithm is tested on a multi-reservoir cascaded hydroelectric system having prohibited operating zones and thermal units with valve point loading. The ramp-rate limits of thermal generators are taken into consideration. The transmission losses are also accounted for through the use of loss coefficients. The algorithm is tested on two hydrothermal multi-reservoir cascaded hydroelectric test systems. The results of the proposed approach are compared with those of differential evolution, evolutionary programming and particle swarm optimization. From numerical results, it is found that the proposed artificial bee colony optimization based approach is able to provide better solution.
Scheduling, revenue management, and fairness in an academic-hospital radiology division.
Baum, Richard; Bertsimas, Dimitris; Kallus, Nathan
2014-10-01
Physician staff of academic hospitals today practice in several geographic locations including their main hospital. This is referred to as the extended campus. With extended campuses expanding, the growing complexity of a single division's schedule means that a naive approach to scheduling compromises revenue. Moreover, it may provide an unfair allocation of individual revenue, desirable or burdensome assignments, and the extent to which the preferences of each individual are met. This has adverse consequences on incentivization and employee satisfaction and is simply against business policy. We identify the daily scheduling of physicians in this context as an operational problem that incorporates scheduling, revenue management, and fairness. Noting previous success of operations research and optimization in each of these disciplines, we propose a simple unified optimization formulation of this scheduling problem using mixed-integer optimization. Through a study of implementing the approach at the Division of Angiography and Interventional Radiology at the Brigham and Women's Hospital, which is directed by one of the authors, we exemplify the flexibility of the model to adapt to specific applications, the tractability of solving the model in practical settings, and the significant impact of the approach, most notably in increasing revenue by 8.2% over previous operating revenue while adhering strictly to a codified fairness and objectivity. We found that the investment in implementing such a system is far outweighed by the large potential revenue increase and the other benefits outlined. Copyright © 2014 AUR. Published by Elsevier Inc. All rights reserved.
Deep Space Network Scheduling Using Evolutionary Computational Methods
NASA Technical Reports Server (NTRS)
Guillaume, Alexandre; Lee, Seugnwon; Wang, Yeou-Fang; Terrile, Richard J.
2007-01-01
The paper presents the specific approach taken to formulate the problem in terms of gene encoding, fitness function, and genetic operations. The genome is encoded such that a subset of the scheduling constraints is automatically satisfied. Several fitness functions are formulated to emphasize different aspects of the scheduling problem. The optimal solutions of the different fitness functions demonstrate the trade-off of the scheduling problem and provide insight into a conflict resolution process.
Enhanced Specification and Verification for Timed Planning
2009-02-28
Scheduling Problem The job-shop scheduling problem ( JSSP ) is a generic resource allocation problem in which common resources (“machines”) are required...interleaving of all processes Pi with the non-delay and mutual exclusion constraints: JSSP =̂ |||0<i6n Pi Where mutual-exclusion( JSSP ) For every complete...execution of JSSP (which terminates), its associated sched- ule S is a feasible schedule. An optimal schedule is a trace of JSSP with the minimum ending
ERIC Educational Resources Information Center
Frank, David J.
1998-01-01
Discusses the creation of an effective carpet vacuuming program by combining area usage assessment and vacuuming requirements with a scheduling plan. Also explains vacuum cleaner suction and filtration and how it makes custodian work more efficient. A complementary article discusses creating an effective floor-maintenance plan for resilient…
41 CFR 109-38.502 - Guidelines.
Code of Federal Regulations, 2010 CFR
2010-07-01
... 38-MOTOR EQUIPMENT MANAGEMENT 38.5-Scheduled Maintenance § 109-38.502 Guidelines. ... 41 Public Contracts and Property Management 3 2010-07-01 2010-07-01 false Guidelines. 109-38.502 Section 109-38.502 Public Contracts and Property Management Federal Property Management Regulations System...
18 CFR 125.3 - Schedule of records and periods of retention.
Code of Federal Regulations, 2010 CFR
2010-04-01
... and agreements. 4. Accountants' and auditors' reports. Information Technology Management 5. Automatic.... Vouchers. Insurance 12. Insurance records. Operations and Maintenance 13.1. Production—Public utilities and licensees (less nuclear). 13.2 Production—Nuclear. 14. Transmission and distribution—Public utilities and...
Kuipers uses vacuum cleaner while performing maintenance in the Columbus Module
2012-02-22
ISS030-E-093398 (22 Feb. 2012) --- European Space Agency astronaut Andre Kuipers, Expedition 30 flight engineer, uses a vacuum cleaner while performing the scheduled extensive cleanup of ventilation systems in the Columbus laboratory of the International Space Station.
DOT National Transportation Integrated Search
1984-07-01
Rail descriptive and defect occurrence information from the Burlington Northern and Atchison, Topeka and Santa Fe railroads is given and analyzed. Track data includes information on track type, when laid, maintenance schedules, etc.
40 CFR 243.204-2 - Recommended procedures: Operations.
Code of Federal Regulations, 2010 CFR
2010-07-01
... collection system. These records should be used for scheduling maintenance and replacement, for budgeting, and for system evaluation and comparison. (b) The collection system should be reviewed on a regular...) SOLID WASTES GUIDELINES FOR THE STORAGE AND COLLECTION OF RESIDENTIAL, COMMERCIAL, AND INSTITUTIONAL...
Research on large equipment maintenance system in life cycle
NASA Astrophysics Data System (ADS)
Xu, Xiaowei; Wang, Hongxia; Liu, Zhenxing; Zhang, Nan
2017-06-01
In order to change the current disadvantages of traditional large equipment maintenance concept, this article plans to apply the technical method of prognostics and health management to optimize equipment maintenance strategy and develop large equipment maintenance system. Combined with the maintenance procedures of various phases in life cycle, it concluded the formulation methods of maintenance program and implement plans of maintenance work. In the meantime, it takes account into the example of the dredger power system of the Waterway Bureau to establish the auxiliary platform of ship maintenance system in life cycle.
Ren, Tao; Zhang, Chuan; Lin, Lin; Guo, Meiting; Xie, Xionghang
2014-01-01
We address the scheduling problem for a no-wait flow shop to optimize total completion time with release dates. With the tool of asymptotic analysis, we prove that the objective values of two SPTA-based algorithms converge to the optimal value for sufficiently large-sized problems. To further enhance the performance of the SPTA-based algorithms, an improvement scheme based on local search is provided for moderate scale problems. New lower bound is presented for evaluating the asymptotic optimality of the algorithms. Numerical simulations demonstrate the effectiveness of the proposed algorithms.
Ren, Tao; Zhang, Chuan; Lin, Lin; Guo, Meiting; Xie, Xionghang
2014-01-01
We address the scheduling problem for a no-wait flow shop to optimize total completion time with release dates. With the tool of asymptotic analysis, we prove that the objective values of two SPTA-based algorithms converge to the optimal value for sufficiently large-sized problems. To further enhance the performance of the SPTA-based algorithms, an improvement scheme based on local search is provided for moderate scale problems. New lower bound is presented for evaluating the asymptotic optimality of the algorithms. Numerical simulations demonstrate the effectiveness of the proposed algorithms. PMID:24764774
DOE Office of Scientific and Technical Information (OSTI.GOV)
Russell, J.S.
Several factors in the development of the East Wilmington oil field by THUMS Long Beach Co. are described. These include: critical path scheduling, complex stratigraphy, reservoir engineering, drilling program, production methods, pressure maintenance, crude oil processing, automation, transportation facilities, service lines, and electrical facilities. The complexity and closely scheduled operational events interwoven in the THUMS project demands a method for the carefully planned sequence of jobs to be done, beginning with island construction up through routine production and to the LACT system. These demanding requirements necessitated the use of a critical path scheduling program. It was decided to use themore » program evaluation technique. This technique is used to assign responsibilities for individual assignments to time assignments, and to keep the overall program on schedule. The stratigraphy of East Wilmington complicates all engineering functions associated with recovery methods and reservoir evaluation. At least 5 major faults are anticipated.« less
DOT National Transportation Integrated Search
1978-01-01
Economic design of new subways requires optimization of installation and maintenance costs of all the major constituent items. A prerequisite for this is an awareness of the rigorous environmental and other conditions imposed on the subway. Changing ...
The Offering, Scheduling and Maintenance of Elective Advanced Pharmacy Practice Experiences
Brown, Rex O.; Patel, Zalak V.; Foster, Stephan L.
2015-01-01
The Accreditation Council for Pharmacy Education (ACPE) provides standards for colleges of pharmacy to assist in the provision of pharmacy education to student pharmacists. An integral part of all college educational programs includes the provision of experiential learning. Experiential learning allows students to gain real-world experience in direct patient care during completion of the curriculum. All college of pharmacy programs provide several Advanced Pharmacy Practice Experiences (APPEs), which include a balance between the four required experiences and a number of other required or elective APPEs. Required APPEs include advanced community, advanced institutional, ambulatory care, and general medicine. The elective APPEs include a myriad of opportunities to help provide a balanced education in experiential learning for student pharmacists. These unique opportunities help to expose student pharmacists to different career tracks that they may not have been able to experience otherwise. Not all colleges offer enough elective APPEs to enable the student pharmacist to obtain experiences in a defined area. Such an approach is required to produce skilled pharmacy graduates that are capable to enter practice in various settings. Elective APPEs are scheduled logically and are based upon student career interest and site availability. This article describes the offering, scheduling and maintenance of different elective APPEs offered by The University of Tennessee College of Pharmacy. PMID:28975920
The Use of Megestrol Acetate in Some Feline Dermatological Problems
Gosselin, Y.; Chalifoux, A.; Papageorges, M.
1981-01-01
Twenty-one cats were treated with megestrol acetate because they were showing clinical signs associated with one of the following problems: eosinophilic ulcer, eosinophilic plaque, neurodermatitis, endocrine alopecia and miliary dermatitis. The dosage schedule was 5 mg orally per day per cat for seven days, then 5 mg every three days for 21 days. In all cats, we noted a good improvement of the lesions as soon as treatment was started. In 25% of the patients, one treatment schedule was sufficient to control the skin disease for at least 18 months. In the remaining 75%, two treatment schedules and/or a maintenance dosage had to be established. Side effects encountered were increased appetite, personality changes and depression. PMID:7337916
NASA Astrophysics Data System (ADS)
Chang, Yung-Chia; Li, Vincent C.; Chiang, Chia-Ju
2014-04-01
Make-to-order or direct-order business models that require close interaction between production and distribution activities have been adopted by many enterprises in order to be competitive in demanding markets. This article considers an integrated production and distribution scheduling problem in which jobs are first processed by one of the unrelated parallel machines and then distributed to corresponding customers by capacitated vehicles without intermediate inventory. The objective is to find a joint production and distribution schedule so that the weighted sum of total weighted job delivery time and the total distribution cost is minimized. This article presents a mathematical model for describing the problem and designs an algorithm using ant colony optimization. Computational experiments illustrate that the algorithm developed is capable of generating near-optimal solutions. The computational results also demonstrate the value of integrating production and distribution in the model for the studied problem.
Transmission Scheduling and Routing Algorithms for Delay Tolerant Networks
NASA Technical Reports Server (NTRS)
Dudukovich, Rachel; Raible, Daniel E.
2016-01-01
The challenges of data processing, transmission scheduling and routing within a space network present a multi-criteria optimization problem. Long delays, intermittent connectivity, asymmetric data rates and potentially high error rates make traditional networking approaches unsuitable. The delay tolerant networking architecture and protocols attempt to mitigate many of these issues, yet transmission scheduling is largely manually configured and routes are determined by a static contact routing graph. A high level of variability exists among the requirements and environmental characteristics of different missions, some of which may allow for the use of more opportunistic routing methods. In all cases, resource allocation and constraints must be balanced with the optimization of data throughput and quality of service. Much work has been done researching routing techniques for terrestrial-based challenged networks in an attempt to optimize contact opportunities and resource usage. This paper examines several popular methods to determine their potential applicability to space networks.
1993-09-01
goal ( Heizer , Render , and Stair, 1993:94). Integer Prgronmming. Integer programming is a general purpose approach used to optimally solve job shop...Scheduling," Operations Research Journal. 29, No 4: 646-667 (July-August 1981). Heizer , Jay, Barry Render and Ralph M. Stair, Jr. Production and Operations
Scheduling time-critical graphics on multiple processors
NASA Technical Reports Server (NTRS)
Meyer, Tom W.; Hughes, John F.
1995-01-01
This paper describes an algorithm for the scheduling of time-critical rendering and computation tasks on single- and multiple-processor architectures, with minimal pipelining. It was developed to manage scientific visualization scenes consisting of hundreds of objects, each of which can be computed and displayed at thousands of possible resolution levels. The algorithm generates the time-critical schedule using progressive-refinement techniques; it always returns a feasible schedule and, when allowed to run to completion, produces a near-optimal schedule which takes advantage of almost the entire multiple-processor system.
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.
Wen, Tingxi; Zhang, Zhongnan; Wong, Kelvin K. L.
2016-01-01
Unmanned aerial vehicle (UAV) has been widely used in many industries. In the medical environment, especially in some emergency situations, UAVs play an important role such as the supply of medicines and blood with speed and efficiency. In this paper, we study the problem of multi-objective blood supply by UAVs in such emergency situations. This is a complex problem that includes maintenance of the supply blood’s temperature model during transportation, the UAVs’ scheduling and routes’ planning in case of multiple sites requesting blood, and limited carrying capacity. Most importantly, we need to study the blood’s temperature change due to the external environment, the heating agent (or refrigerant) and time factor during transportation, and propose an optimal method for calculating the mixing proportion of blood and appendage in different circumstances and delivery conditions. Then, by introducing the idea of transportation appendage into the traditional Capacitated Vehicle Routing Problem (CVRP), this new problem is proposed according to the factors of distance and weight. Algorithmically, we use the combination of decomposition-based multi-objective evolutionary algorithm and local search method to perform a series of experiments on the CVRP public dataset. By comparing our technique with the traditional ones, our algorithm can obtain better optimization results and time performance. PMID:27163361
Wen, Tingxi; Zhang, Zhongnan; Wong, Kelvin K L
2016-01-01
Unmanned aerial vehicle (UAV) has been widely used in many industries. In the medical environment, especially in some emergency situations, UAVs play an important role such as the supply of medicines and blood with speed and efficiency. In this paper, we study the problem of multi-objective blood supply by UAVs in such emergency situations. This is a complex problem that includes maintenance of the supply blood's temperature model during transportation, the UAVs' scheduling and routes' planning in case of multiple sites requesting blood, and limited carrying capacity. Most importantly, we need to study the blood's temperature change due to the external environment, the heating agent (or refrigerant) and time factor during transportation, and propose an optimal method for calculating the mixing proportion of blood and appendage in different circumstances and delivery conditions. Then, by introducing the idea of transportation appendage into the traditional Capacitated Vehicle Routing Problem (CVRP), this new problem is proposed according to the factors of distance and weight. Algorithmically, we use the combination of decomposition-based multi-objective evolutionary algorithm and local search method to perform a series of experiments on the CVRP public dataset. By comparing our technique with the traditional ones, our algorithm can obtain better optimization results and time performance.
A B-52H, tail number 61-0025, arrives at NASA's Dryden Flight Research Center after landing July 30,
NASA Technical Reports Server (NTRS)
2001-01-01
NASA Dryden Flight Research Center, Edwards, California, received an 'H' model B-52 Stratofortress aircraft on July 30, 2001. The B-52H will be used as an air-launch aircraft supporting NASA's flight research and advanced technology demonstration efforts. Dryden received the B-52H from the U.S. Air Force's (USAF) 23rd Bomb Squadron, 5th Bombardment Wing (Air Combat Command), located at Minot AFB, N.D. A USAF crew flew the aircraft to Dryden. The aircraft, USAF tail number 61-0025, will be loaned initially, then later transferred from the USAF to NASA. The B-52H is scheduled to leave Dryden Aug. 2 for de-militarization and Programmed Depot Maintenance (PDM) at Tinker Air Force Base (AFB), Oklahoma. The depot-level maintenance is scheduled to last about six months and includes a thorough maintenance and inspection process. The newly arrived B-52H is slated to replace Dryden's famous B-52B '008,' in the 2003-2004 timeframe. It will take about one year for the B-52H to be ready for flight research duties. This time includes PDM, construction of the new pylon, installation of the flight research instrumentation equipment, and aircraft envelope clearance flights.
A B-52H, on loan to NASA's Dryden Flight Research Center, makes a pass down the runway prior to land
NASA Technical Reports Server (NTRS)
2001-01-01
NASA Dryden Flight Research Center, Edwards, California, received an 'H' model B-52 Stratofortress aircraft on July 30, 2001. The B-52H will be used as an air-launch aircraft supporting NASA's flight research and advanced technology demonstration efforts. Dryden received the B-52H from the U.S. Air Force's (USAF) 23rd Bomb Squadron, 5th Bombardment Wing (Air Combat Command), located at Minot AFB, N.D. A USAF crew flew the aircraft to Dryden. The aircraft, USAF tail number 61-0025, will be loaned initially, then later transferred from the USAF to NASA. The B-52H is scheduled to leave Dryden Aug. 2 for de-militarization and Programmed Depot Maintenance (PDM) at Tinker Air Force Base (AFB), Oklahoma. The depot-level maintenance is scheduled to last about six months and includes a thorough maintenance and inspection process. The newly arrived B-52H is slated to replace Dryden's famous B-52B '008,' in the 2003-2004 timeframe. It will take about one year for the B-52H to be ready for flight research duties. This time includes PDM, construction of the new pylon, installation of the flight research instrumentation equipment, and aircraft envelope clearance flights.
Guidelines to Language Teaching in Classroom and Laboratory.
ERIC Educational Resources Information Center
Iodice, Don R.
Guidelines for evaluating, establishing, and administrating classroom and laboratory language programs are offered in this report. Attention is focused on the language laboratory, with sections on its use, scheduling, materials and texts, preparation of audio materials, preparation of tests, supervision, discipline, and maintenance. Briefer…
76 FR 10233 - Schedule of Water Charges
Federal Register 2010, 2011, 2012, 2013, 2014
2011-02-24
..., operation, maintenance, replacement, reserves and associated administrative costs.'' Id., par. A.2.b. The...'s Beltzville and Blue Marsh reservoirs. The rates established in 1978--$60 per million gallons for... reference, Water resources, Water reservoirs, Water supply, Watersheds. For the reasons set forth in the...
Fuzzy usage pattern in customizing public transport fleet and its maintenance options
NASA Astrophysics Data System (ADS)
Husniah, H.; Herdiani, L.; Kusmaya; Supriatna, A. K.
2018-05-01
In this paper we study a two-dimensional maintenance contract for a fleet of public transport, such as buses, shuttle etc. The buses are sold with a two-dimensional warranty. The warranty and the maintenance contract are characterized by two parameters – age and usage – which define a two-dimensional region. However, we use one dimensional approach to model these age and usage of the buses. The under-laying maintenance service contracts is the one which offers policy limit cost to protect a service provider (an agent) from over claim and to pursue the owner to do maintenance under specified cost in house. This in turn gives benefit for both the owner of the buses and the agent of service contract. The decision problem for an agent is to determine the optimal price for each option offered, and for the owner is to select the best contract option. We use a Nash game theory formulation in order to obtain a win-win solution – i.e. the optimal price for the agent and the optimal option for the owner. We further assume that there will be three different usage pattern of the buses, i.e. low, medium, and high pattern of the usage rate. In many situations it is often that we face a blur boundary between the adjacent patterns. In this paper we look for the optimal price for the agent and the optimal option for the owner, which minimizes the expected total cost while considering the fuzziness of the usage rate pattern.
Reusable Rocket Engine Operability Modeling and Analysis
NASA Technical Reports Server (NTRS)
Christenson, R. L.; Komar, D. R.
1998-01-01
This paper describes the methodology, model, input data, and analysis results of a reusable launch vehicle engine operability study conducted with the goal of supporting design from an operations perspective. Paralleling performance analyses in schedule and method, this requires the use of metrics in a validated operations model useful for design, sensitivity, and trade studies. Operations analysis in this view is one of several design functions. An operations concept was developed given an engine concept and the predicted operations and maintenance processes incorporated into simulation models. Historical operations data at a level of detail suitable to model objectives were collected, analyzed, and formatted for use with the models, the simulations were run, and results collected and presented. The input data used included scheduled and unscheduled timeline and resource information collected into a Space Transportation System (STS) Space Shuttle Main Engine (SSME) historical launch operations database. Results reflect upon the importance not only of reliable hardware but upon operations and corrective maintenance process improvements.
NASA Astrophysics Data System (ADS)
Louzon, E.
1989-12-01
Quality, cost, and schedule are three factors affecting the competitiveness of a company; they require balancing so that products of acceptable quality are delivered, on time and at a competitive cost. Quality costs comprise investment in quality maintenance and failure costs which arise from failure to maintain standards. The basic principle for achieving the required quality at minimum cost is that of prevention of failures, etc., through production control, attention to manufacturing practices, and appropriate management and training. Total quality control involves attention to the product throughout its life cycle, including in-service performance evaluation, servicing, and maintenance.
NASA Technical Reports Server (NTRS)
Hazelton, Lyman R., Jr.
1990-01-01
Some of the logical components of a rule based planning and scheduling system are described. The researcher points out a deficiency in the conventional truth maintenance approach to this class of problems and suggests a new mechanism which overcomes the problem. This extension of the idea of justification truth maintenance may seem at first to be a small philosophical step. However, it embodies a process of basic human reasoning which is so common and automatic as to escape conscious detection without careful introspection. It is vital to any successful implementation of a rule based planning reasoner.
Incentive-compatible demand-side management for smart grids based on review strategies
NASA Astrophysics Data System (ADS)
Xu, Jie; van der Schaar, Mihaela
2015-12-01
Demand-side load management is able to significantly improve the energy efficiency of smart grids. Since the electricity production cost depends on the aggregate energy usage of multiple consumers, an important incentive problem emerges: self-interested consumers want to increase their own utilities by consuming more than the socially optimal amount of energy during peak hours since the increased cost is shared among the entire set of consumers. To incentivize self-interested consumers to take the socially optimal scheduling actions, we design a new class of protocols based on review strategies. These strategies work as follows: first, a review stage takes place in which a statistical test is performed based on the daily prices of the previous billing cycle to determine whether or not the other consumers schedule their electricity loads in a socially optimal way. If the test fails, the consumers trigger a punishment phase in which, for a certain time, they adjust their energy scheduling in such a way that everybody in the consumer set is punished due to an increased price. Using a carefully designed protocol based on such review strategies, consumers then have incentives to take the socially optimal load scheduling to avoid entering this punishment phase. We rigorously characterize the impact of deploying protocols based on review strategies on the system's as well as the users' performance and determine the optimal design (optimal billing cycle, punishment length, etc.) for various smart grid deployment scenarios. Even though this paper considers a simplified smart grid model, our analysis provides important and useful insights for designing incentive-compatible demand-side management schemes based on aggregate energy usage information in a variety of practical scenarios.
Optimization and Flight Schedules of Pioneer Routes in Papua Province
NASA Astrophysics Data System (ADS)
Ronting, Y.; Adisasmita, S. A.; Hamid, S.; Hustim, M.
2018-04-01
The province of Papua has a very varied topography, ranging from swampy lowlands, hills, and plateaus up steep hills. The total area of land is 410,660 km2, which consists of 28 counties and one city, 389 districts and 5.420 villages. The population of Papua Province in 2017 was 3.265.202 people with an average growth of 4.21% per year. The transportation services is still low, especially in the mountainous region, which is isolated and could only be reached by an air transportation mode, causing a considerable price disparity between coastal and mountainous areas. The purpose of this paper is to develop the route optimization and pioneer flight schedules models as an airbridge. This research is conducted by collecting primary data and secondary data. Data is based on field surveys; interviews; discussions with airport authority, official government, etc; and also from various agencies. The analytical tools used to optimization flight schedule and route are analyzed by add-in solver in Microsoft Excel. The results of the analysis we can get a more optimal route so that it can save transportation costs by 7.26%.