scheduling problem jsp: Topics by Science.gov

Sample records for scheduling problem jsp

Performance of Extended Local Clustering Organization (LCO) for Large Scale Job-Shop Scheduling Problem (JSP)

NASA Astrophysics Data System (ADS)

Konno, Yohko; Suzuki, Keiji

This paper describes an approach to development of a solution algorithm of a general-purpose for large scale problems using “Local Clustering Organization (LCO)” as a new solution for Job-shop scheduling problem (JSP). Using a performance effective large scale scheduling in the study of usual LCO, a solving JSP keep stability induced better solution is examined. In this study for an improvement of a performance of a solution for JSP, processes to a optimization by LCO is examined, and a scheduling solution-structure is extended to a new solution-structure based on machine-division. A solving method introduced into effective local clustering for the solution-structure is proposed as an extended LCO. An extended LCO has an algorithm which improves scheduling evaluation efficiently by clustering of parallel search which extends over plural machines. A result verified by an application of extended LCO on various scale of problems proved to conduce to minimizing make-span and improving on the stable performance.
Performance evaluation of different types of particle representation procedures of Particle Swarm Optimization in Job-shop Scheduling Problems

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.
Innately Split Model for Job-shop Scheduling Problem

NASA Astrophysics Data System (ADS)

Ikeda, Kokolo; Kobayashi, Sigenobu

Job-shop Scheduling Problem (JSP) is one of the most difficult benchmark problems. GA approaches often fail searching the global optimum because of the deception UV-structure of JSPs. In this paper, we introduce a novel framework model of GA, Innately Split Model (ISM) which prevents UV-phenomenon, and discuss on its power particularly. Next we analyze the structure of JSPs with the help of the UV-structure hypothesys, and finally we show ISM's excellent performance on JSP.
Active Solution Space and Search on Job-shop Scheduling Problem

NASA Astrophysics Data System (ADS)

Watanabe, Masato; Ida, Kenichi; Gen, Mitsuo

In this paper we propose a new searching method of Genetic Algorithm for Job-shop scheduling problem (JSP). The coding method that represent job number in order to decide a priority to arrange a job to Gannt Chart (called the ordinal representation with a priority) in JSP, an active schedule is created by using left shift. We define an active solution at first. It is solution which can create an active schedule without using left shift, and set of its defined an active solution space. Next, we propose an algorithm named Genetic Algorithm with active solution space search (GA-asol) which can create an active solution while solution is evaluated, in order to search the active solution space effectively. We applied it for some benchmark problems to compare with other method. The experimental results show good performance.
Research on schedulers for astronomical observatories

NASA Astrophysics Data System (ADS)

Colome, Josep; Colomer, Pau; Guàrdia, Josep; Ribas, Ignasi; Campreciós, Jordi; Coiffard, Thierry; Gesa, Lluis; Martínez, Francesc; Rodler, Florian

2012-09-01

The main task of a scheduler applied to astronomical observatories is the time optimization of the facility and the maximization of the scientific return. Scheduling of astronomical observations is an example of the classical task allocation problem known as the job-shop problem (JSP), where N ideal tasks are assigned to M identical resources, while minimizing the total execution time. A problem of higher complexity, called the Flexible-JSP (FJSP), arises when the tasks can be executed by different resources, i.e. by different telescopes, and it focuses on determining a routing policy (i.e., which machine to assign for each operation) other than the traditional scheduling decisions (i.e., to determine the starting time of each operation). In most cases there is no single best approach to solve the planning system and, therefore, various mathematical algorithms (Genetic Algorithms, Ant Colony Optimization algorithms, Multi-Objective Evolutionary algorithms, etc.) are usually considered to adapt the application to the system configuration and task execution constraints. The scheduling time-cycle is also an important ingredient to determine the best approach. A shortterm scheduler, for instance, has to find a good solution with the minimum computation time, providing the system with the capability to adapt the selected task to varying execution constraints (i.e., environment conditions). We present in this contribution an analysis of the task allocation problem and the solutions currently in use at different astronomical facilities. We also describe the schedulers for three different projects (CTA, CARMENES and TJO) where the conclusions of this analysis are applied to develop a suitable routine.
A Solution Method of Job-shop Scheduling Problems by the Idle Time Shortening Type Genetic Algorithm

NASA Astrophysics Data System (ADS)

Ida, Kenichi; Osawa, Akira

In this paper, we propose a new idle time shortening method for Job-shop scheduling problems (JSPs). We insert its method into a genetic algorithm (GA). The purpose of JSP is to find a schedule with the minimum makespan. We suppose that it is effective to reduce idle time of a machine in order to improve the makespan. The left shift is a famous algorithm in existing algorithms for shortening idle time. The left shift can not arrange the work to idle time. For that reason, some idle times are not shortened by the left shift. We propose two kinds of algorithms which shorten such idle time. Next, we combine these algorithms and the reversal of a schedule. We apply GA with its algorithm to benchmark problems and we show its effectiveness.
Introduction to Software Design

DTIC Science & Technology

1989-01-01

Schedules 20 major contributions. We also acknowledge the helpful Worked Examples 20 comments of Larry Peters, Michael Jackson . and Bob Glass. Exercises 20...contrasted with the related For a more general approach to the use of JSP, see work of Warnner and Michael Jackson (JSP). The [Cameron83]. [Ingovaldsson86
An Adaptive Niching Genetic Algorithm using a niche size equalization mechanism

NASA Astrophysics Data System (ADS)

Nagata, Yuichi

Niching GAs have been widely investigated to apply genetic algorithms (GAs) to multimodal function optimization problems. In this paper, we suggest a new niching GA that attempts to form niches, each consisting of an equal number of individuals. The proposed GA can be applied also to combinatorial optimization problems by defining a distance metric in the search space. We apply the proposed GA to the job-shop scheduling problem (JSP) and demonstrate that the proposed niching method enhances the ability to maintain niches and improve the performance of GAs.
Linking search space structure, run-time dynamics, and problem difficulty : a step toward demystifying tabu search.

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

Whitley, L. Darrell; Howe, Adele E.; Watson, Jean-Paul

2004-09-01

Tabu search is one of the most effective heuristics for locating high-quality solutions to a diverse array of NP-hard combinatorial optimization problems. Despite the widespread success of tabu search, researchers have a poor understanding of many key theoretical aspects of this algorithm, including models of the high-level run-time dynamics and identification of those search space features that influence problem difficulty. We consider these questions in the context of the job-shop scheduling problem (JSP), a domain where tabu search algorithms have been shown to be remarkably effective. Previously, we demonstrated that the mean distance between random local optima and the nearestmore » optimal solution is highly correlated with problem difficulty for a well-known tabu search algorithm for the JSP introduced by Taillard. In this paper, we discuss various shortcomings of this measure and develop a new model of problem difficulty that corrects these deficiencies. We show that Taillard's algorithm can be modeled with high fidelity as a simple variant of a straightforward random walk. The random walk model accounts for nearly all of the variability in the cost required to locate both optimal and sub-optimal solutions to random JSPs, and provides an explanation for differences in the difficulty of random versus structured JSPs. Finally, we discuss and empirically substantiate two novel predictions regarding tabu search algorithm behavior. First, the method for constructing the initial solution is highly unlikely to impact the performance of tabu search. Second, tabu tenure should be selected to be as small as possible while simultaneously avoiding search stagnation; values larger than necessary lead to significant degradations in performance.« less
A Bee Evolutionary Guiding Nondominated Sorting Genetic Algorithm II for Multiobjective Flexible Job-Shop Scheduling.

PubMed

Deng, Qianwang; Gong, Guiliang; Gong, Xuran; Zhang, Like; Liu, Wei; Ren, Qinghua

2017-01-01

Flexible job-shop scheduling problem (FJSP) is an NP-hard puzzle which inherits the job-shop scheduling problem (JSP) characteristics. This paper presents a bee evolutionary guiding nondominated sorting genetic algorithm II (BEG-NSGA-II) for multiobjective FJSP (MO-FJSP) with the objectives to minimize the maximal completion time, the workload of the most loaded machine, and the total workload of all machines. It adopts a two-stage optimization mechanism during the optimizing process. In the first stage, the NSGA-II algorithm with T iteration times is first used to obtain the initial population N , in which a bee evolutionary guiding scheme is presented to exploit the solution space extensively. In the second stage, the NSGA-II algorithm with GEN iteration times is used again to obtain the Pareto-optimal solutions. In order to enhance the searching ability and avoid the premature convergence, an updating mechanism is employed in this stage. More specifically, its population consists of three parts, and each of them changes with the iteration times. What is more, numerical simulations are carried out which are based on some published benchmark instances. Finally, the effectiveness of the proposed BEG-NSGA-II algorithm is shown by comparing the experimental results and the results of some well-known algorithms already existed.
A Bee Evolutionary Guiding Nondominated Sorting Genetic Algorithm II for Multiobjective Flexible Job-Shop Scheduling

PubMed Central

Deng, Qianwang; Gong, Xuran; Zhang, Like; Liu, Wei; Ren, Qinghua

2017-01-01

Flexible job-shop scheduling problem (FJSP) is an NP-hard puzzle which inherits the job-shop scheduling problem (JSP) characteristics. This paper presents a bee evolutionary guiding nondominated sorting genetic algorithm II (BEG-NSGA-II) for multiobjective FJSP (MO-FJSP) with the objectives to minimize the maximal completion time, the workload of the most loaded machine, and the total workload of all machines. It adopts a two-stage optimization mechanism during the optimizing process. In the first stage, the NSGA-II algorithm with T iteration times is first used to obtain the initial population N, in which a bee evolutionary guiding scheme is presented to exploit the solution space extensively. In the second stage, the NSGA-II algorithm with GEN iteration times is used again to obtain the Pareto-optimal solutions. In order to enhance the searching ability and avoid the premature convergence, an updating mechanism is employed in this stage. More specifically, its population consists of three parts, and each of them changes with the iteration times. What is more, numerical simulations are carried out which are based on some published benchmark instances. Finally, the effectiveness of the proposed BEG-NSGA-II algorithm is shown by comparing the experimental results and the results of some well-known algorithms already existed. PMID:28458687
An analysis of iterated local search for job-shop scheduling.

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

Whitley, L. Darrell; Howe, Adele E.; Watson, Jean-Paul

2003-08-01

Iterated local search, or ILS, is among the most straightforward meta-heuristics for local search. ILS employs both small-step and large-step move operators. Search proceeds via iterative modifications to a single solution, in distinct alternating phases. In the first phase, local neighborhood search (typically greedy descent) is used in conjunction with the small-step operator to transform solutions into local optima. In the second phase, the large-step operator is applied to generate perturbations to the local optima obtained in the first phase. Ideally, when local neighborhood search is applied to the resulting solution, search will terminate at a different local optimum, i.e.,more » the large-step perturbations should be sufficiently large to enable escape from the attractor basins of local optima. ILS has proven capable of delivering excellent performance on numerous N P-Hard optimization problems. [LMS03]. However, despite its implicity, very little is known about why ILS can be so effective, and under what conditions. The goal of this paper is to advance the state-of-the-art in the analysis of meta-heuristics, by providing answers to this research question. They focus on characterizing both the relationship between the structure of the underlying search space and ILS performance, and the dynamic behavior of ILS. The analysis proceeds in the context of the job-shop scheduling problem (JSP) [Tai94]. They begin by demonstrating that the attractor basins of local optima in the JSP are surprisingly weak, and can be escaped with high probaiblity by accepting a short random sequence of less-fit neighbors. this result is used to develop a new ILS algorithms for the JSP, I-JAR, whose performance is competitive with tabu search on difficult benchmark instances. They conclude by developing a very accurate behavioral model of I-JAR, which yields significant insights into the dynamics of search. The analysis is based on a set of 100 random 10 x 10 problem instances, in addition to some widely used benchmark instances. Both I-JAR and the tabu search algorithm they consider are based on the N1 move operator introduced by van Laarhoven et al. [vLAL92]. The N1 operator induces a connected search space, such that it is always possible to move from an arbitrary solution to an optimal solution; this property is integral to the development of a behavioral model of I-JAR. However, much of the analysis generalizes to other move operators, including that of Nowicki and Smutnick [NS96]. Finally the models are based on the distance between two solutions, which they take as the well-known disjunctive graph distance [MBK99].« less
Covariance and Uncertainty Realism in Space Surveillance and Tracking

DTIC Science & Technology

2016-06-27

control infrastructure , there are also further complications in the implementation of centralized scheduling of some of the SSN sensors due to their...this data however. 5.8.3 Long-Term Long-term developments of JSpOC processing, net-centric interfaces and sensor backends will provide the...with particle filters for mobile sensor network control. In Proceedings of the 45th IEEE Conference on Decision and Control, pages 1019–1024, December
Jellyfish skin polysaccharides: extraction and inhibitory activity on macrophage-derived foam cell formation.

PubMed

Zhang, Hai-Lin; Cui, Shao-Hua; Zha, Xue-Qiang; Bansal, Vibha; Xue, Lei; Li, Xiao-Long; Hao, Ran; Pan, Li-Hua; Luo, Jian-Ping

2014-06-15

In this work, response surface methodology was used to determine optimum conditions for extraction of polysaccharides from jellyfish skin (JSP). The optimum parameters were found to be raw material to water ratio 1:7.5 (w/v), extraction temperature 100°C and extraction time 4h. Under these conditions, the JSP yield reached 1.007 mg/g. Papain (15 U/mL) in combination with Sevag reagent was beneficial in removing proteins from JSP. After precipitation with ethanol at final concentration of 40%, 60% and 80% in turn, three polysaccharide fractions of JSP1, JSP2 and JSP3 were obtained from JSP, respectively. The three fractions exhibited different physicochemical properties with respect to molecular weight distribution, monosaccharide composition, infrared absorption spectra, and glycosyl bond composition. In addition, JSP3 showed strong inhibitory effects on oxidized low-density lipoprotein (oxLDL) induced conversion of macrophages into foam cells, which possibly attributed to the down-regulation of some atherogenesis-related gene expressions. Copyright © 2014 Elsevier Ltd. All rights reserved.
Web-Based Distributed Simulation of Aeronautical Propulsion System

NASA Technical Reports Server (NTRS)

Zheng, Desheng; Follen, Gregory J.; Pavlik, William R.; Kim, Chan M.; Liu, Xianyou; Blaser, Tammy M.; Lopez, Isaac

2001-01-01

An application was developed to allow users to run and view the Numerical Propulsion System Simulation (NPSS) engine simulations from web browsers. Simulations were performed on multiple INFORMATION POWER GRID (IPG) test beds. The Common Object Request Broker Architecture (CORBA) was used for brokering data exchange among machines and IPG/Globus for job scheduling and remote process invocation. Web server scripting was performed by JavaServer Pages (JSP). This application has proven to be an effective and efficient way to couple heterogeneous distributed components.
Space Weather Forecasting at the Joint Space Operations Center (JSpOC)

NASA Astrophysics Data System (ADS)

Nava, O.

2012-12-01

The Joint Space Operations Center (JSpOC) at Vandenberg Air Force Base is the command and control focal point for the operational employment of worldwide joint space forces. The JSpOC focuses on planning and executing US Strategic Command's Joint Functional Component Command for Space (JFCC SPACE) mission. Through the JSpOC, the Weather Specialty Team (WST) monitors space and terrestrial weather effects, plans and assesses weather impacts on military operations, and provides reach-back support for deployed theater solar and terrestrial needs. This presentation will detail how space weather affects the JSpOC mission set and how the scientific community can enhance the WST's capabilities and effectiveness.
Quinoxalinylurea derivatives as a novel class of JSP-1 inhibitors.

PubMed

Zhang, Li; Qiu, Beiying; Xiong, Bing; Li, Xin; Li, Jingya; Wang, Xin; Li, Jia; Shen, Jingkang

2007-04-15

A series of quinoxalinylurea-based inhibitors are synthesized and shown to be the novel and potent inhibitors against Jnk Stimulatory Phosphatase-1 (JSP-1), which is a special member of dual-specificity protein phosphatase (DSP) family. Biological assay and computational modeling studies showed the compounds were reversible and noncompetitive inhibitors of JSP-1. JSP-1 inhibitors may be useful for the treatment of inflammatory, vascular, neurodegenerative, metabolic, and oncological diseases in humans associated with dysfunctional Jnk signaling.
Gamma irradiation and steam pretreatment of jute stick powder for the enhancement of dye adsorption efficiency

NASA Astrophysics Data System (ADS)

Parvin, Fahmida; Sultana, Nargis; Habib, S. M. Ahsan; Bhoumik, Nikhil Chandra

2017-11-01

The aim of this study is to find out the facile and effective pretreatment technique to enhance the capacity of jute stick powder (JSP) in adsorbing dye from raw textile effluent. Hence, different pretreatment techniques, i.e., radiation treatment, alkali treatment, ammonia treatment, steam treatment and CaCl2 treatment were applied to JSP and the adsorbing performance were examined for synthetic dye solutions (Blue FCL and Red RL dye). Different gamma radiation doses were applied on JSP and optimum dye removal efficiency was found at 500 krad in removing these two dyes (50 ppm) from solutions. Among the different pretreatment techniques, gamma irradiated JSP (500 Krad) exhibits highest dye uptake capacity for RED RL dye, whereas steam-treated JSP shows highest performance in adsorbing blue FCL dye. Subsequently, we applied the gamma irradiated and steam-treated JSP on real textile effluent (RTE) and these two techniques shows potentiality in adsorbing dye from raw textile effluent and in reducing BOD5, COD load and TOC to some extent as well. Fourier transform infrared spectroscopy (FTIR) analysis also proved that dye has been adsorbed on pretreated JSP.
Protective effects of Jiashen Prescription () on myocardial infarction in rats.

PubMed

Zhu, Ming-Jun; Wang, You-Ping; Xie, Shi-Yang; Liu, Wei-Hong; Li, Bin; Wang, Yong-Xia; Wang, He; Zhang, Bo-Li

2015-06-01

To evaluate the effects of Jiashen Prescription (, JSP) on myocardial infarction (MI) size and cardiac function at the early stage of MI in rats. One hundred male Sprague-Dawley rats were subjected to sham-operation or MI induced by ligating the left anterior descending coronary artery. The rats with MI were treated with vehicle, JSP 3 and 6 g/(kg·d), or losartan 10 mg/(kg·d) for 1 week. Compared with the vehicle-treated MI rats, 6 g/(kg·d) JSP reduced MI size 3 days after MI (P<0.05), and attenuated the MI-induced increases in left ventricular end-diastolic and end-systolic dimension and decreases in fractional shortening and ejection fraction 1 week after MI (P<0.05). In addition, 6 g/(kg·d) JSP and losartan were equally effective in reducing MI size and enhancing cardiac functional recovery. JSP reduces MI size and improves cardiac function after MI, suggesting that JSP has potential as a therapy for MI.
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Joint Space Operations Center (JSpOC) Mission System Increment 3 (JMS Inc 3)

DTIC Science & Technology

2016-03-01

2016 Major Automated Information System Annual Report Joint Space Operations Center (JSpOC) Mission System Increment 3 (JMS Inc 3) Defense...1725 DSN Phone: DSN Fax: Date Assigned: May 16, 2014 Program Information Program Name Joint Space Operations Center (JSpOC) Mission System...approved program baseline; therefore, no Original Estimate has been established. JMS Inc 3 2016 MAR UNCLASSIFIED 4 Program Description The Joint Space
Crystal structure of human dual specificity phosphatase, JNK stimulatory phosphatase-1, at 1.5 A resolution.

PubMed

Yokota, Takehiro; Nara, Yukinori; Kashima, Akiko; Matsubara, Keiko; Misawa, Satoru; Kato, Ryohei; Sugio, Shigetoshi

2007-02-01

Human JNK stimulatory phosphatase-1 (JSP-1) is a novel member of dual specificity phosphatases. A C-terminus truncated JSP-1 was expressed in Escherichia coli and was crystallized using the sitting-drop vapor diffusion method. Thin-plate crystals obtained at 278 K belong to a monoclinic space group, C2, with unit-cell parameters a = 84.0 A, b = 49.3 A, c = 47.3 A, and beta = 119.5 degrees , and diffract up to 1.5 A resolution at 100 K. The structure of JSP-1 has a single compact (alpha/beta) domain, which consists of six alpha-helices and five beta-strands, and shows a conserved structural scaffold in regard to both DSPs and PTPs. A cleft formed by a PTP-loop at the active site is very shallow, and is occupied by one sulfonate compound, MES, at the bottom. In the binary complex structure of JSP-1 with MES, the conformations of three important segments in regard to the catalytic mechanism are not similar to those in PTP1B. JSP-1 has no loop corresponding to the Lys120-loop of PTP1B, and tryptophan residue corresponding to the substrate-stacking in PTP1B is substituted by alanine residue in JSP-1. Copyright 2006 Wiley-Liss, Inc.
Coupled oscillations of vortex cores confined in a ferromagnetic elliptical disk

NASA Astrophysics Data System (ADS)

Hata, Hiroshi; Goto, Minori; Yamaguchi, Akinobu; Sato, Tomonori; Nakatani, Yoshinobu; Nozaki, Yukio

2014-09-01

By solving the Thiele equation with simultaneous application of a radio-frequency (rf) magnetic field (hrf) and an rf spin current (jsp), the dynamic susceptibility of exchange-coupled vortices in response to hrf and jsp was obtained. It was found that the four eigenmodes expected for two vortices trapped in a magnetic elliptical disk were coupled to different components of hrf and jsp. As a consequence, orthogonal hrf and jsp (which are simultaneously generated by the application of an rf current to an elliptical disk) can excite two modes with different eigenfrequencies. This result suggests that a fieldlike nonadiabatic torque caused by an rf spin current can be spectroscopically distinguished from the one caused by the rf magnetic field.
Design and implementation of workflow engine for service-oriented architecture

NASA Astrophysics Data System (ADS)

Peng, Shuqing; Duan, Huining; Chen, Deyun

2009-04-01

As computer network is developed rapidly and in the situation of the appearance of distribution specialty in enterprise application, traditional workflow engine have some deficiencies, such as complex structure, bad stability, poor portability, little reusability and difficult maintenance. In this paper, in order to improve the stability, scalability and flexibility of workflow management system, a four-layer architecture structure of workflow engine based on SOA is put forward according to the XPDL standard of Workflow Management Coalition, the route control mechanism in control model is accomplished and the scheduling strategy of cyclic routing and acyclic routing is designed, and the workflow engine which adopts the technology such as XML, JSP, EJB and so on is implemented.
Summary of Aqua, Aura, and Terra High Interest Events

NASA Technical Reports Server (NTRS)

Newman, Lauri

2015-01-01

Single-obs tracking Sparsely tracked objects are an unfortunate reality of CARA operations Terra vs. 32081: new track with bad data was included in OD solution for secondary object and risk became high CARA and JSpOC discussed tracking and OSAs threw out the bad data. Event no longer presented high risk based on new OD Improvement: CARA now sends JSpOC a flag indicating when a single obs is included, so OSAs can evaluate if manual update to OD is required. Missing ASW OCMsAura vs. 87178, TCA: 317 at 08:04 UTC. Post-maneuver risk (conjunction was identified in OO results)CARA confirmed with JSpOC that ASW OCMs should have been received in addition to OO OCMsJSpOC corrected the manual error in their script that prevented the data from being delivered to CARAJSpOC QAd their other scripts to ensure this error did not exist in other places.
Sapphire: Canada's Answer to Space-Based Surveillance of Orbital Objects

NASA Astrophysics Data System (ADS)

Maskell, P.; Oram, L.

The Canadian Department of National Defence is in the process of developing the Canadian Space Surveillance System (CSSS) as the main focus of the Surveillance of Space (SofS) Project. The CSSS consists of two major elements: the Sapphire System and the Sensor System Operations Centre (SSOC). The space segment of the Sapphire System is comprised of the Sapphire Satellite - an autonomous spacecraft with an electro-optical payload which will act as a contributing sensor to the United States (US) Space Surveillance Network (SSN). It will operate in a circular, sunsynchronous orbit at an altitude of approximately 750 kilometers and image a minimum of 360 space objects daily in orbits ranging from 6,000 to 40,000 kilometers in altitude. The ground segment of the Sapphire System is composed of a Spacecraft Control Center (SCC), a Satellite Processing and Scheduling Facility (SPSF), and the Sapphire Simulator. The SPSF will be responsible for data transmission, reception, and processing while the SCC will serve to control and monitor the Sapphire Satellite. Surveillance data will be received from Sapphire through two ground stations. Following processing by the SPSF, the surveillance data will then be forwarded to the SSOC. The SSOC will function as the interface between the Sapphire System and the US Joint Space Operations Center (JSpOC). The JSpOC coordinates input from various sensors around the world, all of which are a part of the SSN. The SSOC will task the Sapphire System daily and provide surveillance data to the JSpOC for correlation with data from other SSN sensors. This will include orbital parameters required to predict future positions of objects to be tracked. The SSOC receives daily tasking instructions from the JSpOC to determine which objects the Sapphire spacecraft is required to observe. The advantage of this space-based sensor over ground-based telescopes is that weather and time of day are not factors affecting observation. Thus, space-based optical surveillance does not suffer outage periods of surveillance as is the case with ground-based optical sensors. This allows a space-based sensor to obtain more data and to collect it from a more flexible vantage point. The Sapphire launch is planned for July 2011. The Sapphire spacecraft is designed to operate for a minimum of five years. It will contribute considerably to establishing a significant space capability for Canada. This and other current Canadian space initiatives, will have wide-ranging benefits in the area of National Defence.
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Structural characterization and immunomodulatory activity of a new polysaccharide from jellyfish.

PubMed

Li, Qiang-Ming; Wang, Jing-Fei; Zha, Xue-Qiang; Pan, Li-Hua; Zhang, Hai-Lin; Luo, Jian-Ping

2017-03-01

A new polysaccharide (JSP-11) with a molecular weight of 1.25×10 6 Da was extracted and purified from jellyfish. Monosaccharide analysis showed that JSP-11 was composed of mannose, galactose and glucuronic acid with a molar ratio of 2.18:1.00:1.94. According to the analysis of fourier transform-infrared spectroscopy, methylation analysis, and NMR spectroscopy, JSP-11 was determined to contain a linear backbone which consisted of (1→3,6)-linked β-d-Manp and (1→6)-linked β-d-Galp. The branch of (1→)-linked α-d-GlcpA was attached to the C-3 position of (1→3,6)-linked β-d-Manp in the backbone. The immunomodulatory assay exhibited that JSP-11 could significantly enhance the viability of RAW 264.7 macrophage cells, and promote the release of NO, TNF-α, and IL-1β via activating NF-κB, MAPKs and PI3K/Akt signal pathways. Copyright © 2016 Elsevier Ltd. All rights reserved.
Xanthan gum production using jackfruit-seed-powder-based medium: optimization and characterization.

PubMed

Felicia Katherine, R; Muthukumaran, C; Sharmila, G; Manoj Kumar, N; Tamilarasan, K; Jaiganesh, R

2017-08-01

Xanthan gum (XG) production by Xanthomonas campestris NCIM 2961 using jackfruit seed powder (JSP) as a novel substrate was reported. Central composite design (CCD) of response surface method (RSM) was used to evaluate the linear and interaction effects of five medium variables (JSP, peptone, citric acid, K 2 HPO 4 and KH 2 PO 4 ) for XG production. Maximum XG production (51.62 g/L) was observed at the optimum level of JSP (4 g/L), peptone (0.93 g/L), citric acid (0.26 g/L), K 2 HPO 4 (1.29 g/L) and KH 2 PO 4 (0.5 g/L). K 2 HPO 4 and KH 2 PO 4 were found as significant medium components, which served as buffering agents as well as nutrients for X. campestris growth. The obtained biopolymer was characterized as XG by XRD and FTIR analysis. Results of this study revealed that JSP was found to be a suitable low cost substrate for XG production.
JSpOC Cognitive Task Analysis

NASA Astrophysics Data System (ADS)

Aleva, D.; McCracken, J.

This paper will overview a Cognitive Task Analysis (CTA) of the tasks accomplished by space operators in the Combat Operations Division (COD) of the Joint Space Operations Center (JSpOC). The methodology used to collect data will be presented. The work was performed in support of the AFRL Space Situation Awareness Fusion Intelligent Research Environment (SAFIRE) effort. SAFIRE is a multi-directorate program led by Air Force Research Laboratory (AFRL), Space Vehicles Directorate (AFRL/RV) and supporting Future Long Term Challenge 2.6.5. It is designed to address research areas identified from completion of a Core Process 3 effort for Joint Space Operations Center (JSpOC). The report is intended to be a resource for those developing capability in support of SAFIRE, the Joint Functional Component Command (JFCC) Space Integrated Prototype (JSIP) User-Defined Operating Picture (UDOP), and other related projects. The report is under distribution restriction; our purpose here is to expose its existence to a wider audience so that qualified individuals may access it. The report contains descriptions of the organization, its most salient products, tools, and cognitive tasks. Tasks reported are derived from the data collected and presented at multiple levels of abstraction. Recommendations for leveraging the findings of the report are presented. The report contains a number of appendices that amplify the methodology, provide background or context support, and includes references in support of cognitive task methodology. In a broad sense, the CTA is intended to be the foundation for relevant, usable capability in support of space warfighters. It presents, at an unclassified level, introductory material to familiarize inquirers with the work of the COD; this is embedded in a description of the broader context of the other divisions of the JSpOC. It does NOT provide guidance for the development of Tactics, Techniques, and Procedures (TT&Ps) in the development of JSpOC processes. However, the TT&Ps are a part of the structure of work, and are, therefore, a factor in developing future capability. The authors gratefully acknowledge the cooperation and assistance from the warfighters at the JSpOC as well as the personnel of the JSpOC Capabilities Integration Office (JCIO). Their input to the process created the value of this effort.
[Effect of jingui shenqi pill on morphology of injured spinal cell apoptosis in rats caused by brachytherapy].

PubMed

Xiao, Lu-wei; Shen, Jin-wen; Wu, Cheng-liang

2006-07-01

To study the effect of Jingui Shenqi Pill (JSP) on morphology of spinal cell apoptosis in rats injured by 192Ir irradiation. One hundred and twenty rats were randomly divided into four groups: the model group, the JSP group, the prednisone group and the normal group. Corresponding pharmaceutics were given to rats once a day for 14 days respectively. Then except rats in the normal group, the others received 192Ir interstitial irradiation with the dosage of 22 Gy using back-fixing technology. The injured segments of spinal cord were taken out for HE staining, TUNEL examination and observation with electron microscope 8 hrs, 24 hrs and 4 weeks after irradiation. HE staining examination showed no obvious histological change in rats 8 and 24 hrs after irradiation, but pathological changes, as tissue rarefaction and hemorrhage did found in white matter of spinal cord shown by TUNEL 4 weeks later. Electron microscopic examination and TUNEL staining showed that as compared with the model group, the apoptotic index in the JSP and predinisone treated groups was significantly lower (P < 0.01) 8 hrs after radiation, but it showed insignificant difference between groups at the time points of 24 hrs and 4 weeks after radiation (P > 0.05). JSP could act against apoptosis of gliocyte in spinal cord of rats in early stage after brachytherapy, indicating that JSP possessing a prednisone-like action.
BMDS/SSA Integrated Sensing Demonstration (BISD)

NASA Astrophysics Data System (ADS)

Turner, T.; Springford, K.; Grimaldi, L.

2011-09-01

This demonstration is intended to provide a near-term prototype, leave-behind capability for integrating Ballistic Missile Defense System (BMDS) ground sensors for use in the Space Situational Awareness (SSA) mission. Closed-loop tasking and cueing capability will be implemented, and a demonstration of net-centric space data dissemination using the BMDS sensors will be undertaken using various SSA mission threads. The demonstration is designed to highlight the implications of modifying software and/or hardware at the BMDS command and control node so that cost, risk, and schedule for an operational implementation can be fully understood. Additionally, this demonstration is intended to assess the impacts to both mission areas as a multi-mission, non-traditional sensor capability is integrated into the SSA mission. A successful demonstration will have many leave-behind capabilities and first-of-its-kind achievements to include: a) an extensible SSA operational prototype configuration for BMDS X-Band radars such as AN/TPY-2 and Sea-Based X-Band (SBX) b) a prototype SSA tasking and cueing capability between the Joint Functional Component Command for Space (JFCC Space) Joint Space Operations Center (JSpOC) and the Command, Control, Battle Management, and Communications (C2BMC) Experimental Laboratory (X-Lab), extensible to the Combatant Commands (COCOMS), and out to BMDS sensors c) a capability for a twoway, net-centric, interface for JSpOC space operations, to include translation from net-centric communications to legacy systems and d) processing of BMDS X-Band Radar tracks in the Space Defense Operations Center (SPADOC).
An Evaluation of Washington State's Job Skills Program.

ERIC Educational Resources Information Center

Washington State Workforce Training and Education Coordinating Board, Olympia.

The Job Skills Program (JSP) in Washington State provides job training customized to meet the needs of employers through partnerships of employers and training institutions. The JSP funds up to one-half the cost of training, with employers providing a match. Training can be provided for new employees, for upgrading employees receiving promotions,…

Preparation of 6-substituted quinoxaline JSP-1 inhibitors by microwave accelerated nucleophilic substitution.

PubMed

Zhang, Li; Qiu, Beiying; Li, Xin; Wang, Xin; Li, Jingya; Zhang, Yongliang; Liu, Jian; Li, Jia; Shen, Jingkang

2006-12-21

A small library of 6-aminoquinoxalines has been prepared by nucleophilic substitution of 6-fluoroquinoxaline with amines and nitrogen-containing heterocycles under computer-controlled microwave irradiation. Some compounds were found to be potent inhibitors of JNK Stimulatory Phosphatase-1 (JSP-1) in an in vitro biological assay.
20 CFR 617.49 - Job Search Program.

Code of Federal Regulations, 2014 CFR

2014-04-01

... 20 Employees' Benefits 3 2014-04-01 2014-04-01 false Job Search Program. 617.49 Section 617.49... FOR WORKERS UNDER THE TRADE ACT OF 1974 Job Search Program § 617.49 Job Search Program. (a) Program... approved job search program (JSP), or have completed a JSP, as a condition for receiving TRA, except where...
20 CFR 617.49 - Job Search Program.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 20 Employees' Benefits 3 2010-04-01 2010-04-01 false Job Search Program. 617.49 Section 617.49... FOR WORKERS UNDER THE TRADE ACT OF 1974 Job Search Program § 617.49 Job Search Program. (a) Program... approved job search program (JSP), or have completed a JSP, as a condition for receiving TRA, except where...
20 CFR 617.49 - Job Search Program.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 20 Employees' Benefits 3 2011-04-01 2011-04-01 false Job Search Program. 617.49 Section 617.49... FOR WORKERS UNDER THE TRADE ACT OF 1974 Job Search Program § 617.49 Job Search Program. (a) Program... approved job search program (JSP), or have completed a JSP, as a condition for receiving TRA, except where...
20 CFR 617.49 - Job Search Program.

Code of Federal Regulations, 2012 CFR

2012-04-01

... 20 Employees' Benefits 3 2012-04-01 2012-04-01 false Job Search Program. 617.49 Section 617.49... FOR WORKERS UNDER THE TRADE ACT OF 1974 Job Search Program § 617.49 Job Search Program. (a) Program... approved job search program (JSP), or have completed a JSP, as a condition for receiving TRA, except where...
20 CFR 617.49 - Job Search Program.

Code of Federal Regulations, 2013 CFR

2013-04-01

... 20 Employees' Benefits 3 2013-04-01 2013-04-01 false Job Search Program. 617.49 Section 617.49... FOR WORKERS UNDER THE TRADE ACT OF 1974 Job Search Program § 617.49 Job Search Program. (a) Program... approved job search program (JSP), or have completed a JSP, as a condition for receiving TRA, except where...
Activation of defence in sweet pepper, Capsicum annum, by cis-jasmone, and its impact on aphid and aphid parasitoid behaviour.

PubMed

Dewhirst, Sarah Y; Birkett, Michael A; Loza-Reyes, Elisa; Martin, Janet L; Pye, Barry J; Smart, Lesley E; Hardie, Jim; Pickett, John A

2012-10-01

Two important pests of the sweet pepper, Capsicum annuum, are the peach potato aphid, Myzus persicae, and the glasshouse potato aphid, Aulacorthum solani. Current aphid control measures include the use of biological control agents, i.e., parasitic wasps, but with varying levels of success. One option to increase parasitoid efficiency is to activate plant defence. Therefore, sweet pepper plants were treated with the naturally occurring plant defence activator cis-jasmone, and its impact upon the behaviour and development of aphids and aphid parasitoids was investigated. Growth rate studies revealed that the intrinsic rate of population increase of A. solani and M. persicae on sweet pepper plants treated with cis-jasmone (cJSP) was not affected compared with untreated plants (UnSP), but the positive behavioural response of alate M. persicae towards the volatile organic compounds (VOCs) from UnSP was eliminated by cis-jasmone treatment 48 h previously (cJSP48). In addition, the aphid parasitoid Aphidius ervi preferred VOCs from cJSP48 compared with UnSP, and a significant increase in foraging time was also observed on cJSP. Analysis of VOCs collected from cJSP48 revealed differences compared with UnSP. There is evidence that treatment with cis-jasmone has the potential to improve protection of sweet pepper against insect pests. © Crown copyright 2012. Reproduced with permission of Her Majesty's Stationery Office. Published by John Wiley & Sons, Ltd.
Rhodanine derivatives as inhibitors of JSP-1.

PubMed

Cutshall, Neil S; O'Day, Christine; Prezhdo, Marina

2005-07-15

Dual-specificity phosphatases (DSPs) are a subclass within the protein tyrosine phosphatase family (PTPs). A series of rhodanine-based inhibitors was synthesized and shown to be novel, potent, and selective inhibitors against the DSP family member JNK-stimulating phosphatase-1 (JSP-1). Compounds of this class may be useful for the treatment of inflammatory and proliferative disorders.
76 FR 32975 - Information Collection Available for Public Comments and Recommendations

Federal Register 2010, 2011, 2012, 2013, 2014

2011-06-07

... Administrative Waiver of the Jones Act 46 U.S.C. 12121, 46 CFR 388. Expiration Date of Approval: Three years from... by electronic means via the Internet at http://www.regulations.gov/search/index.jsp . Specifically... the World Wide Web at http://www.regulations.gov/search/index.jsp . Privacy Act: Anyone is able to...
Unscented Sampling Techniques For Evolutionary Computation With Applications To Astrodynamic Optimization

DTIC Science & Technology

2016-09-01

to both genetic algorithms and evolution strategies to achieve these goals. The results of this research offer a promising new set of modified ...abs_all.jsp?arnumber=203904 [163] Z. Michalewicz, C. Z. Janikow, and J. B. Krawczyk, “A modified genetic algo- rithm for optimal control problems...Available: http://arc.aiaa.org/doi/abs/10.2514/ 2.7053 375 [166] N. Yokoyama and S. Suzuki, “ Modified genetic algorithm for constrained trajectory
[Acceleration of Jingui Shenqi Pill on the testis telomerase activity in mice of Shen-yang deficiency].

PubMed

Xu, Cui-Ping; Zhu, Qing-Jun; Song, Jie; Li, Zhen; Zhang, Dan

2013-02-01

To explore the effects of Jingui Shenqi Pill (JSP) on the testis telomerase activity in mice of Shen-yang deficiency syndrome (SYDS). The SYDS model was prepared in 30 mice by over-fatigue and sexual overstrain. They were randomly divided into the model group and the JSP group, 15 in each group. Another 15 normal male mice were selected as the normal group. Mice in the normal group were fed routinely, with distilled water administered intragastrically at the daily dose of 0.1 mL/10 g. Mice in the model group were also administered intragastrically with distilled water at the daily dose of 0.1 mL/10 g while modeling establishment. Mice in the treatment group were administered intragastrically with JSP suspension at 0.1 mL/10 g (the concentration was 0.241 g/mL). The intervention lasted for 4 weeks. Four weeks later, the testis telomerase activity was detected in the three groups by ELISA. The SYDS model was replicated successfully by over-fatigue and sexual overstrain. JSP could improve the signs of mice of SYDS. Compared with the normal group, the activity of testis telomerase decreased in the model group (P < 0.01). Compared with the model group, the testis telomerase activity markedly increased in the treatment group (P < 0.01). The testis telomerase activity in mice of SYDS caused by over-fatigue and sexual overstrain obviously decreased, when compared with that in mice of the normal group. JSP could recover its activity.
The COROT Archive at LAEFF

NASA Astrophysics Data System (ADS)

Velasco, Almudena; Gutiérrez, Raúl; Solano, Enrique; García-Torres, Miguel; López, Mauro; Sarro, Luis Manuel

We describe here the main capabilities of the COROT archive. The archive (http://sdc.laeff.inta.es/corotfa/jsp/searchform.jsp), managed at LAEFF in the framework of the Spanish Virtual Observatory (http://svo.laeff.inta.es), has been developed following the standards and requirements defined by IVOA (http://www.ivoa.net). The COROT archive at LAEFF will be publicly available by the end of 2008.
75 FR 30105 - Solicitation of Applications for Fiscal Year (FY) 2010 Motor Carrier Safety Assistance Program...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-05-28

... on the grants.gov Web site ( http://www.grants.gov ). DATES: FMCSA will initially consider funding... register, go to http://www.grants.gov/applicants/get_registered.jsp . The applicant must download the grant... package. This can be done on the Internet at http://www.grants.gov/applicants/apply_for_grants.jsp . The...
Metabolomics and proteomics technologies to explore the herbal preparation affecting metabolic disorders using high resolution mass spectrometry.

PubMed

Zhang, Aihua; Zhou, Xiaohang; Zhao, Hongwei; Zou, Shiyu; Ma, Chung Wah; Liu, Qi; Sun, Hui; Liu, Liang; Wang, Xijun

2017-01-31

An integrative metabolomics and proteomics approach can provide novel insights in the understanding of biological systems. We have integrated proteome and metabolome data sets for a holistic view of the molecular mechanisms in disease. Using quantitative iTRAQ-LC-MS/MS proteomics coupled with UPLC-Q-TOF-HDMS based metabolomics, we determined the protein and metabolite expression changes in the kidney-yang deficiency syndrome (KYDS) rat model and further investigated the intervention effects of the Jinkui Shenqi Pill (JSP). The VIP-plot of the orthogonal PLS-DA (OPLS-DA) was used for discovering the potential biomarkers to clarify the therapeutic mechanisms of JSP in treating KYDS. The results showed that JSP can alleviate the kidney impairment induced by KYDS. Sixty potential biomarkers, including 5-l-glutamyl-taurine, phenylacetaldehyde, 4,6-dihydroxyquinoline, and xanthurenic acid etc., were definitely up- or down-regulated. The regulatory effect of JSP on the disturbed metabolic pathways was proved by the established metabonomic method. Using pathway analyses, we identified the disturbed metabolic pathways such as taurine and hypotaurine metabolism, pyrimidine metabolism, tyrosine metabolism, tryptophan metabolism, histidine metabolism, steroid hormone biosynthesis, etc. Furthermore, using iTRAQ-based quantitative proteomics analysis, seventeen differential proteins were identified and significantly altered by the JSP treatment. These proteins appear to be involved in Wnt, chemokine, PPAR, and MAPK signaling pathways, etc. Functional pathway analysis revealed that most of the proteins were found to play a key role in the regulation of metabolism pathways. Bioinformatics analysis with the IPA software found that these differentially-expressed moleculars had a strong correlation with the α-adrenergic signaling, FGF signaling, etc. Our data indicate that high-throughput metabolomics and proteomics can provide an insight on the herbal preparations affecting the metabolic disorders using high resolution mass spectrometry.
Utilizing Novel Non-traditional Sensor Tasking Approaches to Enhance the Space Situational Awareness Picture Maintained by the Space Surveillance Network

NASA Astrophysics Data System (ADS)

Herz, A.; Herz, E.; Center, K.; George, P.; Axelrad, P.; Mutschler, S.; Jones, B.

2016-09-01

The Space Surveillance Network (SSN) is tasked with the increasingly difficult mission of detecting, tracking, cataloging and identifying artificial objects orbiting the Earth, including active and inactive satellites, spent rocket bodies, and fragmented debris. Much of the architecture and operations of the SSN are limited and outdated. Efforts are underway to modernize some elements of the systems. Even so, the ability to maintain the best current Space Situational Awareness (SSA) picture and identify emerging events in a timely fashion could be significantly improved by leveraging non-traditional sensor sites. Orbit Logic, the University of Colorado and the University of Texas at Austin are developing an innovative architecture and operations concept to coordinate the tasking and observation information processing of non - traditional assets based on information-theoretic approaches. These confirmed tasking schedules and the resulting data can then be used to "inform" the SSN tasking process. The 'Heimdall Web' system is comprised of core tasking optimization components and accompanying Web interfaces within a secure, split architecture that will for the first time allow non-traditional sensors to support SSA and improve SSN tasking. Heimdall Web application components appropriately score/prioritize space catalog objects based on covariance, priority, observability, expected information gain, and probability of detect - then coordinate an efficient sensor observation schedule for non-SSN sensors contributing to the overall SSA picture maintained by the Joint Space Operations Center (JSpOC). The Heimdall Web Ops concept supports sensor participation levels of "Scheduled", "Tasked" and "Contributing". Scheduled and Tasked sensors are provided optimized observation schedules or object tracking lists from central algorithms, while Contributing sensors review and select from a list of "desired track objects". All sensors are "Web Enabled" for tasking and feedback, supplying observation schedules, confirmed observations and related data back to Heimdall Web to complete the feedback loop for the next scheduling iteration.
Seismic Observations and Interpretation in NE China, Infrasound Observations and Interpretation in Utah

DTIC Science & Technology

2010-07-30

from Xu et al., 2005). (b) Map of SMU-IGPCEA Huailai Seismic Network and seismicity ( open circles) for the time period of January 01, 2002 through...the Beijing-Huailai-Fengzhen (H20) refraction/ wide angle reflection profile (Zhu et al., 1997). Open circles are locations of two historical...historycatalog_query.jsp) and the China Seismograph Network ( CSN ) Catalog (http://210.72.96.165/wdcd/csn_catalog_p001.jsp) list a total of 323 earthquakes with magnitude
Exchange interactions in CdMnTe/CdMgTe quantum wells under high magnetic fields

NASA Astrophysics Data System (ADS)

Yasuhira, T.; Uchida, K.; Matsuda, Y. H.; Miura, N.; Kuroda, S.; Takita, K.

2002-03-01

The sp-d exchange interaction Jsp-d and the exchange interaction between the nearest neighbor Mn ions JNN were studied by magneto-photoluminescence spectra of excitons in CdMnTe/CdMgTe quantum wells in pulsed high magnetic fields up to 45 T. The magnitude of Jsp-d estimated from the observed Zeeman splitting was found to decrease as the quantum well width was decreased. The decrease is partly due to the penetration of the electron and the hole wave functions into the non-magnetic CdMgTe barrier layers, and partly due to the k-dependence of the exchange interaction. It was found that the latter effect is much larger than theoretically predicted. The observed features are well explained by a model assuming the interface disorder within some thickness near the interface. In contrast to Jsp-d, the nearest neighbor interaction JNN estimated from the steps in the photoluminescence peak was found to be independent of the well width.
Collision Avoidance Short Course Part I: Theory

NASA Technical Reports Server (NTRS)

Hejduk, Matthew D.

2017-01-01

Satellite conjunction assessment is perhaps the fastest-growing area in space situational awareness and protection, with military, civil, and commercial satellite owner operators embracing more and more sophisticated processes to avoid the avoidable namely collisions between high-value space assets and orbital debris. NASA and CNES have collaborated to offer an introductory short course on all the major aspects of the conjunction assessment problem. This half-day course will cover satellite conjunction dynamics and theory, JSpOC conjunction data products, major risk assessment parameters and plots, conjunction remediation decision support, and present and future challenges. This briefing represents the NASA portion of the course.
The Joint Space Operations Center (JSpOC) Mission System (JMS) and the Advanced Research, Collaboration, and Application Development Environment (ARCADE)

NASA Astrophysics Data System (ADS)

Johnson, K.; Kim, R.; Echeverry, J.

The Joint Space Operations Center (JSpOC) is a command and control center focused on executing the Space Control mission of the Joint Functional Component Command for Space (JFCC-SPACE) to ensure freedom of action of United States (US) space assets, while preventing adversary use of space against the US. To accomplish this, the JSpOC tasks a network of space surveillance sensors to collect Space Situational Awareness (SSA) data on resident space objects (RSOs) in near earth and deep space orbits. SSA involves the ingestion of data sources and use of algorithms and tools to build, maintain, and disseminate situational awareness of RSOs in space. On the heels of emergent and complex threats to space assets, the JSpOC's capabilities are limited by legacy systems and CONOPs. The JSpOC Mission System (JMS) aims to consolidate SSA efforts across US agencies, international partners, and commercial partners. The JMS program is intended to deliver a modern service-oriented architecture (SOA) based infrastructure with increased process automation and improved tools to remove the current barriers to JSpOC operations. JMS has been partitioned into several developmental increments. Increment 1, completed and operational in early 2013, and Increment 2, which is expected to be completed in 2016, will replace the legacy Space Defense Operations Center (SPADOC) and Astrodynamics Support Workstation (ASW) capabilities. In 2017 JMS Increment 3 will continue to provide additional SSA and C2 capabilities that will require development of new applications and procedures as well as the exploitation of new data sources. Most importantly, Increment 3 is uniquely postured to evolve the JSpOC into the centralized and authoritative source for all Space Control applications by using its SOA to aggregate information and capabilities from across the community. To achieve this goal, Scitor Corporation has supported the JMS Program Office as it has entered into a partnership with AFRL/RD (Directed Energy) and AFRL/RV (Space Vehicles) to create the Advanced Research, Collaboration, and Application Development Environment (ARCADE). The ARCADE formalizes capability development processes that hitherto have been ad hoc, slow to address the evolving space threat environment, and not easily repeatable. Therefore, the purpose of the ARCADE is to: (1) serve as a centralized testbed for all research and development (R&D) activities related to JMS applications, including algorithm development, data source exposure, service orchestration, and software services, and provide developers reciprocal access to relevant tools and data to accelerate technology development, (2) allow the JMS program to communicate user capability priorities and requirements to developers, (3) facilitate collaboration among developers who otherwise would not collaborate due to organizational, policy, or geographical barriers, and (4) support market research efforts by identifying outstanding performers that are available to shepherd into the formal transition process. Over the last several years Scitor Corporation has provided systems engineering support to the JMS Increment 3 Program Office, and has worked with AFRL/RV and AFRL/RD to create a high performance computing environment and SOA at both unclassified and classified levels that together allow developers to develop applications in an environment similar to the version of JMS currently in use by the JSpOC operators. Currently the ARCADE is operational in an unclassified environment via the High Performance Computing Modernization Program (HPCMP) Portal on DREN. The ARCADE also exists on SECRET and TOP SECRET environments on multiple networks. This presentation will cover the following topics: (1) Scitors role in shaping the ARCADE into its current form, (2) ARCADEs value proposition for potential technology developers, and (3) ARCADEs value proposition for the Government. These topics will be discussed by way of several case studies: a JMS Prototype activity, integration of the Search and Determine Integrated Environment (SADIE) system into the ARCADE, and developer challenge opportunities using the ARCADE. The contents of this presentation will be UNCLASSIFIED.
The GIS portal based on JSR168 portlet technology and WSRP

NASA Astrophysics Data System (ADS)

Wu, Defu; Chen, Nengcheng; Zhu, Xinyan; Gong, Jianya

2005-10-01

A portal is a powerful Web site that gives users a single point of access to applications and information in a unified interface. A portal lets users view each application or web page in its own window, called a portlet, and a single browser window can contain multiple portlets. The portlet based on JSP168&WSRP is a new technology for interactive, user-facing web services that plug and play with portals. Thanks to the development of Portal&Web GIS, the GIS Poratl is focused on more and more by the researcheres. This paper studies the GIS Portal defined by ESRI and analyzes the development's status, compares with the commercial Portal and points out the great shortage of the ESRI GIS Portal: lack in Personal content and UI. Therefor this paper goes into depth on the discussion of design and implementation scheme of real GIS Portal, and proposes the new idea of developing customized, plug and play GIS Portal Module based on JSP168 Portlet technology and WSRP standard. This way can resolve the difficult problem of the GIS Portal on lacking of content and customization function. According to this idea, this paper plans to use the JaveBeans provided by GeoSurf to develop visual portlet which have basic operating fuction of GIS. Finally deploys the GIS Portal uing the WebLogic Portal.

Ambient Particulate Matter Induces Oxidative Dna Damage in Lung Epithelial Cells.

PubMed

Knaapen, A M; Schins, R P; Steinfartz, Y; Doris, H; Dunemann, L; Borm, P J

2000-01-01

Although epidemiological studies have established a correlation between PMIO levels and acute cardiovascular and respiratory complications, hardly any data is available on possible chronic effects such as cancer. The purpose of this study was to investigate the production of free radicals by ambient particulate matter (TSP) and to link these data to oxidative DNA damage in lung epithelial cells. In line with previous findings on PMIO, supercoiled plasmid DNA was depleted by JSP as well as JSP supernatant (p < .001), and this effect was reduced in the presence of mannitol (5 mM). Using electron spin resonance (ESR) and the spin trap dimethyl-1-pyrroline N-oxide (DMPO) we were able to show that hydroxy/radicals ('OH) are formed from both JSP and JSP supernatant. The DMPO-OH signal was completely abrogated when TSP was preincubated with deferoxamine (5 mM), showing the importance of iron and other soluble metals in this process. Atomic absorption spectroscopy (AAS) analysis of the TSP supernatant showed the presence of soluble Fe, V, and Ni (respectively 253.0, 14.7, and 76.0 µ/g insoluble TSP). To investigate the biological significance of OH formation by TSP, 8-hydroxydeoxyguanosine (8-oxodC) was measured in a rat type II cell line by immunocytochemistry. The formation of this hydroxyl-radical-specific DNA adduct was increased twofold (p < .01) after incubation with TSP supernatants, and this effect was inhibited by deferoxamine (p < .01). In summary, our results provide direct evidence that ambient particulate matter generates hydroxyI radicals in acellular systems. Furthermore, we showed that these particulates induce the hydroxyl-radical-specific DNA lesion 8-oxodC in lung target cells via an iron-mediated mechanism.
Thermodesulfobacterium hveragerdense sp. nov., and Thermodesulfovibrio islandicus sp. nov., two thermophilic sulfate reducing bacteria isolated from a Icelandic hot spring.

PubMed

Sonne-Hansen, J; Ahring, B K

1999-12-01

Two thermophilic non-sporeforming sulfate-reducing bacteria (SRB) were isolated from microbial mats collected from an Icelandic hot spring. Strain JSP was a gram negative rod, with an average cell size of 2.8 x 0.5 microm. No flagella were found. Growth occurred between 55 and 74 degrees C with an optimum between 70 and 74 degrees C at pH 7.0. The G+C content was 40 mol%. Strain R1Ha3 was a gram negative vibrio-shaped rod with an average cell size of 1.7 x 0.4 microm. Motility was observed mediated by one polar flagellum. The growth optimum at pH 7.0 was 65 degrees C, and growth occurred between 45 and 70 degrees C. The G+C content was 38 mol%. In the presence of sulfate, both strains used lactate, pyruvate and H2 as electron donors. In addition, strain R1Ha3 used formate. Pyruvate was the only substrate supporting fermentative growth of both strains. Growth occurred with sulfate as well as thiosulfate as electron acceptors. Furthermore, strain R1Ha3 reduced nitrate and strain JSP reduced sulfite. Neither of the strains were able to oxidize lactate completely to CO2 and neither of the strains contained desulfoviridin. 16S rDNA sequencing placed strain JSP in the genus Thermodesulfobacterium and strain R1Ha3 in the genus Thermodesulfovibrio. Based on the DNA-DNA hybridization studies and differences in morphology and physiology to their closest relatives the two new isolates were considered as new species. Strain JSP is named Thermodesulfobacterium hveragerdense and strain R1Ha3 Thermodesulfovibrio islandicus.
ASAS definition for sacroiliitis on MRI in SpA: applicable to children?

PubMed

Herregods, Nele; Dehoorne, Joke; Van den Bosch, Filip; Jaremko, Jacob Lester; Van Vlaenderen, Joke; Joos, Rik; Baraliakos, Xenofon; Varkas, Gaëlle; Verstraete, Koenraad; Elewaut, Dirk; Jans, Lennart

2017-04-11

The Assessment of Spondyloarthritis International Society (ASAS) definition for a 'positive' Magnetic Resonance Imaging (MRI) for sacroiliitis is well studied and validated in adults, but studies about the value of this definition in children are lacking. The aim of this study is to evaluate whether the adult ASAS definition of a positive MRI of the sacroiliac joints can be applied to children with a clinical suspicion of Juvenile Spondyloarthritis (JSpA). Two pediatric musculoskeletal radiologists blinded to clinical data independently retrospectively reviewed sacroiliac (SI) joint MRI in 109 children suspected of sacroiliitis. They recorded global impression (sacroiliitis yes/no) and whether the adult ASAS definition for sacroiliitis was met at each joint. This was compared to gold-standard clinical diagnosis of JSpA. Additionally, MRI were scored according to'adapted' ASAS definitions including other features of sacroiliitis on MRI. JSpA was diagnosed clinically in 47/109 (43%) patients. On MRI, sacroiliitis was diagnosed by global assessment in 30/109 patients, of whom 14 also fulfilled ASAS criteria. No patients with negative global assessment for sacroiliitis fulfilled ASAS criteria. Sensitivity (SN) for JSpA was higher for global assessment (SN = 49%) than for ASAS definition (SN = 26%), but the ASAS definition was more specific (SP = 97% vs. 89%). Modifying adult ASAS criteria to allow bone marrow edema (BME) lesions seen on only one slice, synovitis or capsulitis, increased SN to 36%, 32% and 32% respectively, only slightly lowering SP. Including structural lesions increased SN to 28%, but lowered specificity to 95%. The adult ASAS definition for sacroiliitis has low sensitivity in children. A pediatric-specific definition of MRI-positive sacroiliitis including BME lesions visible on one slice only, synovitis and/or capsulitis may improve diagnostic utility, and increase relevance of MRI in pediatric rheumatology practice.
Collision Avoidance "Short Course" Part III: CA Role in Changing Space Flight Environment

NASA Technical Reports Server (NTRS)

Newman, Lauri

2017-01-01

Satellite conjunction assessment is perhaps the fastest-growing area in space situational awareness and protection, with military, civil, and commercial satellite owner operators embracing more and more sophisticated processes to avoid the avoidable namely collisions between high-value space assets and orbital debris. NASA and CNES have collaborated to offer an introductory short course on all the major aspects of the conjunction assessment problem. This half-day course will cover satellite conjunction dynamics and theory, JSpOC conjunction data products, major risk assessment parameters and plots, conjunction remediation decision support, and present and future challenges. This briefing represents the NASA portion of the course.
[Effects of jingui shenqi pill combined prednisone on expression of glucocorticoid receptor and its clinical effect in treating bullous pemphigoid patients].

PubMed

Liu, Bao-guo; Li, Zhi-ying; Du, Ming

2006-10-01

To investigate the effect of Jingui Shenqi Pill (JSP) on the expression of glucocorticoid receptor (GR) in the skin lesion and its clinical effect in treating bullous pemphigoid (BP) patients. Thirty BP patients were randomly divided into the treatment group (n=15) treated with JSP plus prednisone and the prednisone group (n=15) with prednisone alone both for 4 weeks. And a normal control group was set up also. Expressions of GR-alpha and GR-beta in the skin lesion of BP patients and the normal skin of the normal control were detected by immunohistochemical assay. Results The total effective rate was 93.33% in the treatment group, significantly higher than that in the prednisone group which was 73.33% (P < 0.05); GR-alpha expression was higher in the treatment group than that in other two groups (P < 0.01), while GR-beta expression in the treatment group was lower than that in the prednisone group (P < 0.01). JSP could increase GR-alpha expression and decrease GR-beta expression in the skin lesion of BP patients, so as to improve sensitivity of skin to glucocorticoid.
In vitro translation with [34S]-labeled methionine, selenomethionine, and telluromethionine.

PubMed

Ogra, Yasumitsu; Kitaguchi, Takashi; Suzuki, Noriyuki; Suzuki, Kazuo T

2008-01-01

Heteroisotope and heteroatom tagging with [(34)S]-enriched methionine (Met), selenomethionine (SeMet), and telluromethionine (TeMet) was applied to in vitro translation. Green fluorescent protein (GFP) and JNK stimulatory phosphatase-1 (JSP-1) genes were translated with wheat germ extract (WGE) in the presence of Met derivatives. GFPs containing Met derivatives were subjected to HPLC coupled with treble detection, i.e., a photodiode array detector, a fluorescence detector, and an inductively coupled plasma mass spectrometer (ICP-MS). The activities of JSP-1-containing Met derivatives were also measured. GFP and JSP-1 containing [(34)S]-Met and SeMet showed comparable fluorescence intensities and enzyme activities to those containing naturally occurring Met. TeMet was unstable and decomposed in WGE, whereas SeMet was stable throughout the experimental period. Thus, although Te was the most sensitive to ICP-MS detection among S, Se, and Te, TeMet was less incorporated into the proteins than Met and SeMet. Finally, the potential of heteroisotope and heteroatom tagging of desired proteins in in vitro translation followed by ICP-MS detection was discussed. [figure: see text] TeMet was less incorporated into GFP than Met and SeMet due to its instability in WGE.
Activation of the Jnk signaling pathway by a dual-specificity phosphatase, JSP-1.

PubMed

Shen, Y; Luche, R; Wei, B; Gordon, M L; Diltz, C D; Tonks, N K

2001-11-20

The mitogen-activated protein kinases (MAPKs) are integral to the mechanisms by which cells respond to physiological stimuli, such as growth factors, hormones, and cytokines, and to a wide variety of environmental stresses. The MAPKs, which are stimulated by phosphorylation of a TXY motif in their activation loop, are components of signal transduction cascades in which sequential activation of protein kinases culminates in their activation and their subsequent phosphorylation of various effector proteins that mediate the physiological response. MAPKs are also subject to dephosphorylation and inactivation, both by enzymes that recognize the residues of the TXY motif independently and by dual specificity phosphatases, which dephosphroylate both Tyr and Ser/Thr residues. We report the identification and characterization of a novel dual specificity phosphatase. Contrary to expectation, this broadly expressed enzyme did not inactivate MAPKs in transient cotransfection assays but instead displayed the capacity to function as a selective activator of the MAPK Jnk, hence the name, Jnk Stimulatory Phosphatase-1 (JSP-1). This study illustrates a new aspect of the regulation of MAPK-dependent signal transduction and raises the possibility that JSP-1 may offer a different perspective to the study of various inflammatory and proliferative disorders associated with dysfunctional Jnk signaling.
The Joint Space Operations Center Mission System and the Advanced Research, Collaboration, and Application Development Environment Status Update 2016

NASA Astrophysics Data System (ADS)

Murray-Krezan, Jeremy; Howard, Samantha; Sabol, Chris; Kim, Richard; Echeverry, Juan

2016-05-01

The Joint Space Operations Center (JSpOC) Mission System (JMS) is a service-oriented architecture (SOA) infrastructure with increased process automation and improved tools to enhance Space Situational Awareness (SSA) performed at the US-led JSpOC. The Advanced Research, Collaboration, and Application Development Environment (ARCADE) is a test-bed maintained and operated by the Air Force to (1) serve as a centralized test-bed for all research and development activities related to JMS applications, including algorithm development, data source exposure, service orchestration, and software services, and provide developers reciprocal access to relevant tools and data to accelerate technology development, (2) allow the JMS program to communicate user capability priorities and requirements to developers, (3) provide the JMS program with access to state-of-the-art research, development, and computing capabilities, and (4) support JMS Program Office-led market research efforts by identifying outstanding performers that are available to shepherd into the formal transition process. In this paper we will share with the international remote sensing community some of the recent JMS and ARCADE developments that may contribute to greater SSA at the JSpOC in the future, and share technical areas still in great need.
Activation of the Jnk signaling pathway by a dual-specificity phosphatase, JSP-1

PubMed Central

Shen, Yu; Luche, Ralf; Wei, Bo; Gordon, Marcia L.; Diltz, Curtis D.; Tonks, Nicholas K.

2001-01-01

The mitogen-activated protein kinases (MAPKs) are integral to the mechanisms by which cells respond to physiological stimuli, such as growth factors, hormones, and cytokines, and to a wide variety of environmental stresses. The MAPKs, which are stimulated by phosphorylation of a TXY motif in their activation loop, are components of signal transduction cascades in which sequential activation of protein kinases culminates in their activation and their subsequent phosphorylation of various effector proteins that mediate the physiological response. MAPKs are also subject to dephosphorylation and inactivation, both by enzymes that recognize the residues of the TXY motif independently and by dual specificity phosphatases, which dephosphroylate both Tyr and Ser/Thr residues. We report the identification and characterization of a novel dual specificity phosphatase. Contrary to expectation, this broadly expressed enzyme did not inactivate MAPKs in transient cotransfection assays but instead displayed the capacity to function as a selective activator of the MAPK Jnk, hence the name, Jnk Stimulatory Phosphatase-1 (JSP-1). This study illustrates a new aspect of the regulation of MAPK-dependent signal transduction and raises the possibility that JSP-1 may offer a different perspective to the study of various inflammatory and proliferative disorders associated with dysfunctional Jnk signaling. PMID:11717427
Constraint-based integration of planning and scheduling for space-based observatory management

NASA Technical Reports Server (NTRS)

Muscettola, Nicola; Smith, Steven F.

1994-01-01

Progress toward the development of effective, practical solutions to space-based observatory scheduling problems within the HSTS scheduling framework is reported. HSTS was developed and originally applied in the context of the Hubble Space Telescope (HST) short-term observation scheduling problem. The work was motivated by the limitations of the current solution and, more generally, by the insufficiency of classical planning and scheduling approaches in this problem context. HSTS has subsequently been used to develop improved heuristic solution techniques in related scheduling domains and is currently being applied to develop a scheduling tool for the upcoming Submillimeter Wave Astronomy Satellite (SWAS) mission. The salient architectural characteristics of HSTS and their relationship to previous scheduling and AI planning research are summarized. Then, some key problem decomposition techniques underlying the integrated planning and scheduling approach to the HST problem are described; research results indicate that these techniques provide leverage in solving space-based observatory scheduling problems. Finally, more recently developed constraint-posting scheduling procedures and the current SWAS application focus are summarized.
A meta-heuristic method for solving scheduling problem: crow search algorithm

NASA Astrophysics Data System (ADS)

Adhi, Antono; Santosa, Budi; Siswanto, Nurhadi

2018-04-01

Scheduling is one of the most important processes in an industry both in manufacturingand services. The scheduling process is the process of selecting resources to perform an operation on tasks. Resources can be machines, peoples, tasks, jobs or operations.. The selection of optimum sequence of jobs from a permutation is an essential issue in every research in scheduling problem. Optimum sequence becomes optimum solution to resolve scheduling problem. Scheduling problem becomes NP-hard problem since the number of job in the sequence is more than normal number can be processed by exact algorithm. In order to obtain optimum results, it needs a method with capability to solve complex scheduling problems in an acceptable time. Meta-heuristic is a method usually used to solve scheduling problem. The recently published method called Crow Search Algorithm (CSA) is adopted in this research to solve scheduling problem. CSA is an evolutionary meta-heuristic method which is based on the behavior in flocks of crow. The calculation result of CSA for solving scheduling problem is compared with other algorithms. From the comparison, it is found that CSA has better performance in term of optimum solution and time calculation than other algorithms.
Balancing antagonistic time and resource utilization constraints in over-subscribed scheduling problems

NASA Technical Reports Server (NTRS)

Smith, Stephen F.; Pathak, Dhiraj K.

1991-01-01

In this paper, we report work aimed at applying concepts of constraint-based problem structuring and multi-perspective scheduling to an over-subscribed scheduling problem. Previous research has demonstrated the utility of these concepts as a means for effectively balancing conflicting objectives in constraint-relaxable scheduling problems, and our goal here is to provide evidence of their similar potential in the context of HST observation scheduling. To this end, we define and experimentally assess the performance of two time-bounded heuristic scheduling strategies in balancing the tradeoff between resource setup time minimization and satisfaction of absolute time constraints. The first strategy considered is motivated by dispatch-based manufacturing scheduling research, and employs a problem decomposition that concentrates local search on minimizing resource idle time due to setup activities. The second is motivated by research in opportunistic scheduling and advocates a problem decomposition that focuses attention on the goal activities that have the tightest temporal constraints. Analysis of experimental results gives evidence of differential superiority on the part of each strategy in different problem solving circumstances. A composite strategy based on recognition of characteristics of the current problem solving state is then defined and tested to illustrate the potential benefits of constraint-based problem structuring and multi-perspective scheduling in over-subscribe scheduling problems.
Decomposability and scalability in space-based observatory scheduling

NASA Technical Reports Server (NTRS)

Muscettola, Nicola; Smith, Stephen F.

1992-01-01

In this paper, we discuss issues of problem and model decomposition within the HSTS scheduling framework. HSTS was developed and originally applied in the context of the Hubble Space Telescope (HST) scheduling problem, motivated by the limitations of the current solution and, more generally, the insufficiency of classical planning and scheduling approaches in this problem context. We first summarize the salient architectural characteristics of HSTS and their relationship to previous scheduling and AI planning research. Then, we describe some key problem decomposition techniques supported by HSTS and underlying our integrated planning and scheduling approach, and we discuss the leverage they provide in solving space-based observatory scheduling problems.
Interactive system for geomagnetic data analysis

NASA Astrophysics Data System (ADS)

Solovev, Igor

2017-10-01

The paper suggests the methods for analyzing geomagnetic field variations, which are implemented in "Aurora" software system for complex analysis of geophysical parameters. The software system allows one to perform a detailed magnetic data analysis. The methods allow one to estimate the intensity of geomagnetic perturbations and to allocate increased geomagnetic activity periods. The software system is publicly available (http://aurorasa.ikir.ru:8580, http://www.ikir.ru:8280/lsaserver/MagneticPage.jsp). This research was supported by the Russian Science Foundation (Project No. 14-11-00194).
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).
SOFIA's Choice: Automating the Scheduling of Airborne Observations

NASA Technical Reports Server (NTRS)

Frank, Jeremy; Norvig, Peter (Technical Monitor)

1999-01-01

This paper describes the problem of scheduling observations for an airborne telescope. Given a set of prioritized observations to choose from, and a wide range of complex constraints governing legitimate choices and orderings, how can we efficiently and effectively create a valid flight plan which supports high priority observations? This problem is quite different from scheduling problems which are routinely solved automatically in industry. For instance, the problem requires making choices which lead to other choices later, and contains many interacting complex constraints over both discrete and continuous variables. Furthermore, new types of constraints may be added as the fundamental problem changes. As a result of these features, this problem cannot be solved by traditional scheduling techniques. The problem resembles other problems in NASA and industry, from observation scheduling for rovers and other science instruments to vehicle routing. The remainder of the paper is organized as follows. In 2 we describe the observatory in order to provide some background. In 3 we describe the problem of scheduling a single flight. In 4 we compare flight planning and other scheduling problems and argue that traditional techniques are not sufficient to solve this problem. We also mention similar complex scheduling problems which may benefit from efforts to solve this problem. In 5 we describe an approach for solving this problem based on research into a similar problem, that of scheduling observations for a space-borne probe. In 6 we discuss extensions of the flight planning problem as well as other problems which are similar to flight planning. In 7 we conclude and discuss future work.
Oracle Applications Patch Administration Tool (PAT) Beta Version

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

2002-01-04

PAT is a Patch Administration Tool that provides analysis, tracking, and management of Oracle Application patches. This includes capabilities as outlined below: Patch Analysis & Management Tool Outline of capabilities: Administration Patch Data Maintenance -- track Oracle Application patches applied to what database instance & machine Patch Analysis capture text files (readme.txt and driver files) form comparison detail report comparison detail PL/SQL package comparison detail SQL scripts detail JSP module comparison detail Parse and load the current applptch.txt (10.7) or load patch data from Oracle Application database patch tables (11i) Display Analysis -- Compare patch to be applied with currentmore » Oracle Application installed Appl_top code versions Patch Detail Module comparison detail Analyze and display one Oracle Application module patch. Patch Management -- automatic queue and execution of patches Administration Parameter maintenance -- setting for directory structure of Oracle Application appl_top Validation data maintenance -- machine names and instances to patch Operation Patch Data Maintenance Schedule a patch (queue for later execution) Run a patch (queue for immediate execution) Review the patch logs Patch Management Reports« less
Noncontingent reinforcement without extinction plus differential reinforcement of alternative behavior during treatment of problem behavior.

PubMed

Fritz, Jennifer N; Jackson, Lynsey M; Stiefler, Nicole A; Wimberly, Barbara S; Richardson, Amy R

2017-07-01

The effects of noncontingent reinforcement (NCR) without extinction during treatment of problem behavior maintained by social positive reinforcement were evaluated for five individuals diagnosed with autism spectrum disorder. A continuous NCR schedule was gradually thinned to a fixed-time 5-min schedule. If problem behavior increased during NCR schedule thinning, a continuous NCR schedule was reinstated and NCR schedule thinning was repeated with differential reinforcement of alternative behavior (DRA) included. Results showed an immediate decrease in all participants' problem behavior during continuous NCR, and problem behavior maintained at low levels during NCR schedule thinning for three participants. Problem behavior increased and maintained at higher rates during NCR schedule thinning for two other participants; however, the addition of DRA to the intervention resulted in decreased problem behavior and increased mands. © 2017 Society for the Experimental Analysis of Behavior.
Job shop scheduling problem with late work criterion

NASA Astrophysics Data System (ADS)

Piroozfard, Hamed; Wong, Kuan Yew

2015-05-01

Scheduling is considered as a key task in many industries, such as project based scheduling, crew scheduling, flight scheduling, machine scheduling, etc. In the machine scheduling area, the job shop scheduling problems are considered to be important and highly complex, in which they are characterized as NP-hard. The job shop scheduling problems with late work criterion and non-preemptive jobs are addressed in this paper. Late work criterion is a fairly new objective function. It is a qualitative measure and concerns with late parts of the jobs, unlike classical objective functions that are quantitative measures. In this work, simulated annealing was presented to solve the scheduling problem. In addition, operation based representation was used to encode the solution, and a neighbourhood search structure was employed to search for the new solutions. The case studies are Lawrence instances that were taken from the Operations Research Library. Computational results of this probabilistic meta-heuristic algorithm were compared with a conventional genetic algorithm, and a conclusion was made based on the algorithm and problem.
An algorithm for a single machine scheduling problem with sequence dependent setup times and scheduling windows

NASA Technical Reports Server (NTRS)

Moore, J. E.

1975-01-01

An enumeration algorithm is presented for solving a scheduling problem similar to the single machine job shop problem with sequence dependent setup times. The scheduling problem differs from the job shop problem in two ways. First, its objective is to select an optimum subset of the available tasks to be performed during a fixed period of time. Secondly, each task scheduled is constrained to occur within its particular scheduling window. The algorithm is currently being used to develop typical observational timelines for a telescope that will be operated in earth orbit. Computational times associated with timeline development are presented.

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

NASA Astrophysics Data System (ADS)

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

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

PubMed

Markiewicz, Tomasz

2011-03-30

The Matlab software is a one of the most advanced development tool for application in engineering practice. From our point of view the most important is the image processing toolbox, offering many built-in functions, including mathematical morphology, and implementation of a many artificial neural networks as AI. It is very popular platform for creation of the specialized program for image analysis, also in pathology. Based on the latest version of Matlab Builder Java toolbox, it is possible to create the software, serving as a remote system for image analysis in pathology via internet communication. The internet platform can be realized based on Java Servlet Pages with Tomcat server as servlet container. In presented software implementation we propose remote image analysis realized by Matlab algorithms. These algorithms can be compiled to executable jar file with the help of Matlab Builder Java toolbox. The Matlab function must be declared with the set of input data, output structure with numerical results and Matlab web figure. Any function prepared in that manner can be used as a Java function in Java Servlet Pages (JSP). The graphical user interface providing the input data and displaying the results (also in graphical form) must be implemented in JSP. Additionally the data storage to database can be implemented within algorithm written in Matlab with the help of Matlab Database Toolbox directly with the image processing. The complete JSP page can be run by Tomcat server. The proposed tool for remote image analysis was tested on the Computerized Analysis of Medical Images (CAMI) software developed by author. The user provides image and case information (diagnosis, staining, image parameter etc.). When analysis is initialized, input data with image are sent to servlet on Tomcat. When analysis is done, client obtains the graphical results as an image with marked recognized cells and also the quantitative output. Additionally, the results are stored in a server database. The internet platform was tested on PC Intel Core2 Duo T9600 2.8 GHz 4 GB RAM server with 768x576 pixel size, 1.28 Mb tiff format images reffering to meningioma tumour (x400, Ki-67/MIB-1). The time consumption was as following: at analysis by CAMI, locally on a server - 3.5 seconds, at remote analysis - 26 seconds, from which 22 seconds were used for data transfer via internet connection. At jpg format image (102 Kb) the consumption time was reduced to 14 seconds. The results have confirmed that designed remote platform can be useful for pathology image analysis. The time consumption is depended mainly on the image size and speed of the internet connections. The presented implementation can be used for many types of analysis at different staining, tissue, morphometry approaches, etc. The significant problem is the implementation of the JSP page in the multithread form, that can be used parallelly by many users. The presented platform for image analysis in pathology can be especially useful for small laboratory without its own image analysis system.
Using MATLAB software with Tomcat server and Java platform for remote image analysis in pathology

PubMed Central

2011-01-01

Background The Matlab software is a one of the most advanced development tool for application in engineering practice. From our point of view the most important is the image processing toolbox, offering many built-in functions, including mathematical morphology, and implementation of a many artificial neural networks as AI. It is very popular platform for creation of the specialized program for image analysis, also in pathology. Based on the latest version of Matlab Builder Java toolbox, it is possible to create the software, serving as a remote system for image analysis in pathology via internet communication. The internet platform can be realized based on Java Servlet Pages with Tomcat server as servlet container. Methods In presented software implementation we propose remote image analysis realized by Matlab algorithms. These algorithms can be compiled to executable jar file with the help of Matlab Builder Java toolbox. The Matlab function must be declared with the set of input data, output structure with numerical results and Matlab web figure. Any function prepared in that manner can be used as a Java function in Java Servlet Pages (JSP). The graphical user interface providing the input data and displaying the results (also in graphical form) must be implemented in JSP. Additionally the data storage to database can be implemented within algorithm written in Matlab with the help of Matlab Database Toolbox directly with the image processing. The complete JSP page can be run by Tomcat server. Results The proposed tool for remote image analysis was tested on the Computerized Analysis of Medical Images (CAMI) software developed by author. The user provides image and case information (diagnosis, staining, image parameter etc.). When analysis is initialized, input data with image are sent to servlet on Tomcat. When analysis is done, client obtains the graphical results as an image with marked recognized cells and also the quantitative output. Additionally, the results are stored in a server database. The internet platform was tested on PC Intel Core2 Duo T9600 2.8GHz 4GB RAM server with 768x576 pixel size, 1.28Mb tiff format images reffering to meningioma tumour (x400, Ki-67/MIB-1). The time consumption was as following: at analysis by CAMI, locally on a server – 3.5 seconds, at remote analysis – 26 seconds, from which 22 seconds were used for data transfer via internet connection. At jpg format image (102 Kb) the consumption time was reduced to 14 seconds. Conclusions The results have confirmed that designed remote platform can be useful for pathology image analysis. The time consumption is depended mainly on the image size and speed of the internet connections. The presented implementation can be used for many types of analysis at different staining, tissue, morphometry approaches, etc. The significant problem is the implementation of the JSP page in the multithread form, that can be used parallelly by many users. The presented platform for image analysis in pathology can be especially useful for small laboratory without its own image analysis system. PMID:21489188
Electrolytes Test

MedlinePlus

... online at http://www.merck.com/mrkshared/mm_geriatrics/sec8/ch59.jsp. (1995-2004). Acid-Base Metabolism. The Merck Manual of Diagnosis and Therapy, Section 2. Endocrine And Metabolic Disorders, Chapter 12. ...
Blood Clots

MedlinePlus

... sitting for long periods. If you travel by airplane, walk the aisle periodically. For long car trips, ... Your-Risk-for-Excessive-Blood-Clotting_UCM_448771_Article.jsp. Accessed April 18, 2016. What causes excessive ...
Completable scheduling: An integrated approach to planning and scheduling

NASA Technical Reports Server (NTRS)

Gervasio, Melinda T.; Dejong, Gerald F.

1992-01-01

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

PubMed

Cheng, Zhi-An; Han, Ling; Wei, Jian-An; Sun, Jing; Duan, Xiao-Dong

2013-02-01

To study the effects of Chinese medical recipes for invigorating Shen on rat bone marrow mesenchymal stem cells (BMSCs)-derived preadipocytes' differentiation to osteoblasts. The BMSCs were cultured using whole bone marrow adherence wall method. The BMSCs were induced to preadipocytes by classic chemical method. The osteogenic differentiation process of preadipocytes was intervened by Liuwei Dihuang Pill (LDP), Jingui Shenqi Pill (JSP), or Jiangu Erxian Pill (JEP)-containing serums (with the concentRation of 10%, on behalf of tonifying Shen yin, tonifying Shen yang, and tonifying Shen essence). Reverse transcription-real time fluorescent quantitative-PCR (RT real time qPCR) was used to detect RUNX2, ALP, BGP, BMP2, BMP4, SPP1, and IGF1 mRNA expressions of osteogenic differentiation-related genes, mRNA expressions of LPL, FABP4, and PPARgamma of adipogenic differentiation-related genes on the 6th, the 12th, and the 18th day. As for the osteogenic differentiation-related gene, when compared with the control group, there was no statistical difference in the gene expression level in the experimental groups on the 6th day (2.0 > Ratio > 0.5). On the 12th day, the mRNA expressions of IGF1 and Runx2 increased more significantly in the JSP group, with their relative quantification (Ratio) being 2.97 and 1.81 respectively. On the 18th day the IGF1 mRNA expression significantly increased, being the Ratio value of 3.74, 12.60, and 8.35, respectively, in the LDP group, the JSP group, and the JEP group. The SPP1 mRNA expression also significantly increased, with the Ratio value of 2.94, 3.18, and 2.62, respectively, in the LDP group, the JSP group, and the JEP group. As for adipogenic differentiation-related genes, on the 6th day, when compared with the control group, FABP4 mRNA expression significantly decreased in the LDP group and the JSP group (with the Ratio value of 0.47 and 0.40 respectively). The expression levels of other genes were all down-regulated, but not significantly. On the 12th day and 18th day, there was no statistical change in the adipogenic differentiation-related genes expressions (2.0 > Ratio > 0.5). Up-regulation of osteogenic differentiation-related genes expression occurred in later time, while down-regulation of adipogenic differentiation-related genes expression occurred in earlier time after treatment by Chinese medical recipes for invigorating Shen. In general, above data indicated that tonifying Shen yang was more effective in promoting osteogenic differentiation and inhibiting adipogenic differentiation of BMSCs.
Dynamic scheduling and planning parallel observations on large Radio Telescope Arrays with the Square Kilometre Array in mind

NASA Astrophysics Data System (ADS)

Buchner, Johannes

2011-12-01

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

DTIC Science & Technology

1986-03-01

problems is the National Basketball Association ( NBA -) schedul- ing problems developed by Bean (1980), as discussed in detail in the Appendix. These...fY! X F L- %n~ P ’ % -C-10 K7 K: K7 -L- -7".i - W. , W V APPENDIX The NBA Scheduling Problem §A.1 Formulation The National Basketball Association...16 2.2 4.9 40.2 15.14 §6.2.3 NBA Scheduling Problem The last set of testing problems involves the NBA scheduling problem. A detailed description of
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.
77 FR 15997 - National Medal of Technology and Innovation Nomination Evaluation Committee Charter Renewal

Federal Register 2010, 2011, 2012, 2013, 2014

2012-03-19

... States Patent and Trademark Office, Commerce. ACTION: Notice. SUMMARY: The Chief Financial Officer and.../nmti/index.jsp . SUPPLEMENTARY INFORMATION: The Chief Financial Officer and Assistant Secretary of...
DoD Agile Adoption: Necessary Considerations, Concerns, and Changes

DTIC Science & Technology

2012-01-01

a large, highly visible display used by software development teams to track progress. The term was first coined by Alistar Cockburn. See <http://www.atlassian.com/ wallboards /information-radiators.jsp>
Creating Simple Windchill Admin Tools Using Info*Engine

NASA Technical Reports Server (NTRS)

Jones, Corey; Kapatos, Dennis; Skradski, Cory

2012-01-01

Being a Windchill administrator often requires performing simple yet repetitive tasks on large sets of objects. These can include renaming, deleting, checking in, undoing checkout, and much more. This is especially true during a migration. Fortunately, PTC has provided a simple way to dynamically interact with Windchill using Info*Engine. This presentation will describe how to create simple Info*Engine tasks capable of saving Windchill 10.0 administrators hours of tedious work. It will also show how these tasks can be combined and displayed on a simple JSP page that acts as a "Windchill Administrator Dashboard/Toolbox". The attendee will learn some valuable tasks Info*Engine capable of performing. The attendee will gain a basic understanding of how to perform and implement Info*Engine tasks. The attendee will learn what's involved in creating a JSP page that displays Info*Engine tasks
Peak Pc Prediction in Conjunction Analysis: Conjunction Assessment Risk Analysis. Pc Behavior Prediction Models

NASA Technical Reports Server (NTRS)

Vallejo, J.J.; Hejduk, M.D.; Stamey, J. D.

2015-01-01

Satellite conjunction risk typically evaluated through the probability of collision (Pc). Considers both conjunction geometry and uncertainties in both state estimates. Conjunction events initially discovered through Joint Space Operations Center (JSpOC) screenings, usually seven days before Time of Closest Approach (TCA). However, JSpOC continues to track objects and issue conjunction updates. Changes in state estimate and reduced propagation time cause Pc to change as event develops. These changes a combination of potentially predictable development and unpredictable changes in state estimate covariance. Operationally useful datum: the peak Pc. If it can reasonably be inferred that the peak Pc value has passed, then risk assessment can be conducted against this peak value. If this value is below remediation level, then event intensity can be relaxed. Can the peak Pc location be reasonably predicted?
Effect of a metal primer on the bond strength of the resin-metal interface.

PubMed

Freitas, Anderson Pinheiro de; Francisconi, Paulo Afonso Silveira

2004-06-01

To evaluate the effect of different surface treatments on shear bond strength between a metallic alloy (Co-Cr-Mo - Remanium CD) and a resin cement (Rely X TM) and to evaluate the mode of fracture after testing, forty couples of metallic-alloy disks were melted, regularized, polished, submitted to four thermal cycles (Vacuum, 960ºC, 8 minutes) and randomly separated into four groups. Each group received a different type of treatment: Group PSP: Polished with sandpaper 600; Group PCP: Polished with sandpaper 600 and application of the metal primer Alloy Primer (Kuraray); Group JSP: Sandblasted with 100µm aluminum oxide; Group JCP: Sandblasted with 100mm aluminum oxide and treated with a metal Primer. The groups were cemented and stored in distilled water at 37ºC for 36 hours and submitted to the shear bond strength test. The mean and standard deviation (in Kgf/cm²) obtained for each group was: PSP 4.0/0.4; PCP 88.9/33.6; JSP 163.2/27.6; JCP 144.5/54.0. After the statistical analysis the authors concluded that: the highest values were obtained for the sandblasted groups (JSP, JCP), regardless of the primer application; the Alloy Primer increased the retention between the Rely X cement and the polished surface of the Co-Cr-Mo alloy, yet its bond strength was not greater than that obtained with sandblasting; all specimens showed adhesive failures in the tested interface.
Compiling Planning into Scheduling: A Sketch

NASA Technical Reports Server (NTRS)

Bedrax-Weiss, Tania; Crawford, James M.; Smith, David E.

2004-01-01

Although there are many approaches for compiling a planning problem into a static CSP or a scheduling problem, current approaches essentially preserve the structure of the planning problem in the encoding. In this pape: we present a fundamentally different encoding that more accurately resembles a scheduling problem. We sketch the approach and argue, based on an example, that it is possible to automate the generation of such an encoding for problems with certain properties and thus produce a compiler of planning into scheduling problems. Furthermore we argue that many NASA problems exhibit these properties and that such a compiler would provide benefits to both theory and practice.
Bridging the Gap Between Planning and Scheduling

NASA Technical Reports Server (NTRS)

Smith, David E.; Frank, Jeremy; Jonsson, Ari K.; Norvig, Peter (Technical Monitor)

2000-01-01

Planning research in Artificial Intelligence (AI) has often focused on problems where there are cascading levels of action choice and complex interactions between actions. In contrast. Scheduling research has focused on much larger problems where there is little action choice, but the resulting ordering problem is hard. In this paper, we give an overview of M planning and scheduling techniques, focusing on their similarities, differences, and limitations. We also argue that many difficult practical problems lie somewhere between planning and scheduling, and that neither area has the right set of tools for solving these vexing problems.
Interactive computer aided shift scheduling.

PubMed

Gaertner, J

2001-12-01

This paper starts with a discussion of computer aided shift scheduling. After a brief review of earlier approaches, two conceptualizations of this field are introduced: First, shift scheduling as a field that ranges from extremely stable rosters at one pole to rather market-like approaches on the other pole. Unfortunately, already small alterations of a scheduling problem (e.g., the number of groups, the number of shifts) may call for rather different approaches and tools. Second, their environment shapes scheduling problems and scheduling has to be done within idiosyncratic organizational settings. This calls for the amalgamation of scheduling with other tasks (e.g., accounting) and for reflections whether better solutions might become possible by changes in the problem definition (e.g., other service levels, organizational changes). Therefore shift scheduling should be understood as a highly connected problem. Building upon these two conceptualizations, a few examples of software that ease scheduling in some areas of this field are given and future research questions are outlined.
77 FR 7136 - Caribbean Fishery Management Council; Public Meetings

Federal Register 2010, 2011, 2012, 2013, 2014

2012-02-10

.../Sedar_Workshops.jsp?WorkshopNum=26 ) 5. Discussion of options paper on parrotfish size and trip limits 6... meetings are open to the public, and will be conducted in English. Simultaneous interpretation (English...

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.
Integrated scheduling and resource management. [for Space Station Information System

NASA Technical Reports Server (NTRS)

Ward, M. T.

1987-01-01

This paper examines the problem of integrated scheduling during the Space Station era. Scheduling for Space Station entails coordinating the support of many distributed users who are sharing common resources and pursuing individual and sometimes conflicting objectives. This paper compares the scheduling integration problems of current missions with those anticipated for the Space Station era. It examines the facilities and the proposed operations environment for Space Station. It concludes that the pattern of interdependecies among the users and facilities, which are the source of the integration problem is well structured, allowing a dividing of the larger problem into smaller problems. It proposes an architecture to support integrated scheduling by scheduling efficiently at local facilities as a function of dependencies with other facilities of the program. A prototype is described that is being developed to demonstrate this integration concept.
Applications of dynamic scheduling technique to space related problems: Some case studies

NASA Astrophysics Data System (ADS)

Nakasuka, Shinichi; Ninomiya, Tetsujiro

1994-10-01

The paper discusses the applications of 'Dynamic Scheduling' technique, which has been invented for the scheduling of Flexible Manufacturing System, to two space related scheduling problems: operation scheduling of a future space transportation system, and resource allocation in a space system with limited resources such as space station or space shuttle.
Solving a real-world problem using an evolving heuristically driven schedule builder.

PubMed

Hart, E; Ross, P; Nelson, J

1998-01-01

This work addresses the real-life scheduling problem of a Scottish company that must produce daily schedules for the catching and transportation of large numbers of live chickens. The problem is complex and highly constrained. We show that it can be successfully solved by division into two subproblems and solving each using a separate genetic algorithm (GA). We address the problem of whether this produces locally optimal solutions and how to overcome this. We extend the traditional approach of evolving a "permutation + schedule builder" by concentrating on evolving the schedule builder itself. This results in a unique schedule builder being built for each daily scheduling problem, each individually tailored to deal with the particular features of that problem. This results in a robust, fast, and flexible system that can cope with most of the circumstances imaginable at the factory. We also compare the performance of a GA approach to several other evolutionary methods and show that population-based methods are superior to both hill-climbing and simulated annealing in the quality of solutions produced. Population-based methods also have the distinct advantage of producing multiple, equally fit solutions, which is of particular importance when considering the practical aspects of the problem.
Testing Task Schedulers on Linux System

NASA Astrophysics Data System (ADS)

Jelenković, Leonardo; Groš, Stjepan; Jakobović, Domagoj

Testing task schedulers on Linux operating system proves to be a challenging task. There are two main problems. The first one is to identify which properties of the scheduler to test. The second problem is how to perform it, e.g., which API to use that is sufficiently precise and in the same time supported on most platforms. This paper discusses the problems in realizing test framework for testing task schedulers and presents one potential solution. Observed behavior of the scheduler is the one used for “normal” task scheduling (SCHED_OTHER), unlike one used for real-time tasks (SCHED_FIFO, SCHED_RR).
Discrete Bat Algorithm for Optimal Problem of Permutation Flow Shop Scheduling

PubMed Central

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.

PubMed

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.
CSIRT Requirements for Situational Awareness

DTIC Science & Technology

2014-01-25

deepsight-products http://www.symantec.com/security_response/publications/threatreport.jsp Verizon Verizon produces an annual data breach report...impact studies to the differences between malicious versus non-malicious data breaches . Ponemon also offers con- sulting services. Ponemon also
Middle Man Concept for In-Orbit Collision Risks Mitigation, CAESAR and CARA Examples

NASA Technical Reports Server (NTRS)

Moury, Monique; Newman, Lauri K.; Laporte, Francois

2014-01-01

This paper describes the conjunction analysis which has to be performed using data provided by JSpOC. This description not only demonstrates that Collision Avoidance is a 2- step process (close approach detection followed by risk evaluation for collision avoidance decision) but also leads to the conclusion that there is a need for a Middle Man role. After describing the Middle Man concept, this paper introduces two examples with their similarities and particularities: the American civil space effort delivered by the NASA CARA team (Conjunction Assessment Risk Analysis) and the French response CAESAR (Conjunction Assessment and Evaluation Service: Alerts and Recommendations). For both, statistics are presented and feedbacks discussed. All together, around 80 satellites are served by CARA and/or CAESAR. Both processes regularly evolve in order either to follow JSpOC upgrades or to improve analysis according to experience acquired during the past years.
Foundation and progress of Japanese society of toxicologic pathology*.

PubMed

Konishi, Yoichi; Enomoto, Makoto; Hayashi, Yuzo

2011-03-01

The Japanese Society of Toxicologic Pathology (JSTP) has a differing conceptual framework from the Japanese Society of Pathology (JSP) and Japanese Society of Toxicology (JST) and was founded in 1985 by the leadership of late Dr. Yasukazu Nishiyama with the cooperation of several founding members and the support of JSP. The aim of the JSTP is to improve the human and animal health using an interdisciplinary scientific approach based on pathology and toxicology. In its development as a professional society, the JSTP has established society rules and activities. The JSTP has grown in terms of membership and financial aspects and is now recognized not only domestically but also internationally as a well-organized scientific society. To maintain the high professional standard and visibility of JSTP, we here provide the historical background of the society as a basis for current members to contribute to the continued improvement of our scientific organization.
Development of the Subaru-Mitaka-Okayama-Kiso Archive System

NASA Astrophysics Data System (ADS)

Baba, Hajime; Yasuda, Naoki; Ichikawa, Shin-Ichi; Yagi, Masafumi; Iwamoto, Nobuyuki; Takata, Tadafumi; Horaguchi, Toshihiro; Taga, Masatoshi; Watanabe, Masaru; Ozawa, Tomohiko; Hamabe, Masaru

We have developed the Subaru-Mitaka-Okayama-Kiso-Archive (SMOKA) public science archive system which provides access to the data of the Subaru Telescope, the 188 cm telescope at Okayama Astrophysical Observatory, and the 105 cm Schmidt telescope at Kiso Observatory/University of Tokyo. SMOKA is the successor of the MOKA3 system. The user can browse the Quick-Look Images, Header Information (HDI) and the ASCII Table Extension (ATE) of each frame from the search result table. A request for data can be submitted in a simple manner. The system is developed with Java Servlet for the back-end, and Java Server Pages (JSP) for content display. The advantage of JSP's is the separation of the front-end presentation from the middle- and back-end tiers which led to an efficient development of the system. The SMOKA homepage is available at SMOKA
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.
A Comparison of Techniques for Scheduling Fleets of Earth-Observing Satellites

NASA Technical Reports Server (NTRS)

Globus, Al; Crawford, James; Lohn, Jason; Pryor, Anna

2003-01-01

Earth observing satellite (EOS) scheduling is a complex real-world domain representative of a broad class of over-subscription scheduling problems. Over-subscription problems are those where requests for a facility exceed its capacity. These problems arise in a wide variety of NASA and terrestrial domains and are .XI important class of scheduling problems because such facilities often represent large capital investments. We have run experiments comparing multiple variants of the genetic algorithm, hill climbing, simulated annealing, squeaky wheel optimization and iterated sampling on two variants of a realistically-sized model of the EOS scheduling problem. These are implemented as permutation-based methods; methods that search in the space of priority orderings of observation requests and evaluate each permutation by using it to drive a greedy scheduler. Simulated annealing performs best and random mutation operators outperform our squeaky (more intelligent) operator. Furthermore, taking smaller steps towards the end of the search improves performance.
Aspects of job scheduling

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.
User requirements for a patient scheduling system

NASA Technical Reports Server (NTRS)

Zimmerman, W.

1979-01-01

A rehabilitation institute's needs and wants from a scheduling system were established by (1) studying the existing scheduling system and the variables that affect patient scheduling, (2) conducting a human-factors study to establish the human interfaces that affect patients' meeting prescribed therapy schedules, and (3) developing and administering a questionnaire to the staff which pertains to the various interface problems in order to identify staff requirements to minimize scheduling problems and other factors that may limit the effectiveness of any new scheduling system.
Evaluation of scheduling techniques for payload activity planning

NASA Technical Reports Server (NTRS)

Bullington, Stanley F.

1991-01-01

Two tasks related to payload activity planning and scheduling were performed. The first task involved making a comparison of space mission activity scheduling problems with production scheduling problems. The second task consisted of a statistical analysis of the output of runs of the Experiment Scheduling Program (ESP). Details of the work which was performed on these two tasks are presented.
Artificial intelligence approaches to astronomical observation scheduling

NASA Technical Reports Server (NTRS)

Johnston, Mark D.; Miller, Glenn

1988-01-01

Automated scheduling will play an increasing role in future ground- and space-based observatory operations. Due to the complexity of the problem, artificial intelligence technology currently offers the greatest potential for the development of scheduling tools with sufficient power and flexibility to handle realistic scheduling situations. Summarized here are the main features of the observatory scheduling problem, how artificial intelligence (AI) techniques can be applied, and recent progress in AI scheduling for Hubble Space Telescope.
The comparison of predictive scheduling algorithms for different sizes of job shop scheduling problems

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.
32 CFR 158.7 - Guidance for contractor medical and dental fitness.

Code of Federal Regulations, 2014 CFR

2014-07-01

... “shot record,” available for purchase at http://bookstore.gpo.gov/collections/vaccination.jsp). (g... employee with one of the conditions listed in paragraphs (j)(2)(i) through (j)(2)(xxx) of this section can...
32 CFR 158.7 - Guidance for contractor medical and dental fitness.

Code of Federal Regulations, 2013 CFR

2013-07-01

... “shot record,” available for purchase at http://bookstore.gpo.gov/collections/vaccination.jsp). (g... employee with one of the conditions listed in paragraphs (j)(2)(i) through (j)(2)(xxx) of this section can...

32 CFR 158.7 - Guidance for contractor medical and dental fitness.

Code of Federal Regulations, 2012 CFR

2012-07-01

... “shot record,” available for purchase at http://bookstore.gpo.gov/collections/vaccination.jsp). (g... employee with one of the conditions listed in paragraphs (j)(2)(i) through (j)(2)(xxx) of this section can...
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.
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

DTIC Science & Technology

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
Improving Resource Selection and Scheduling Using Predictions. Chapter 1

NASA Technical Reports Server (NTRS)

Smith, Warren

2003-01-01

The introduction of computational grids has resulted in several new problems in the area of scheduling that can be addressed using predictions. The first problem is selecting where to run an application on the many resources available in a grid. Our approach to help address this problem is to provide predictions of when an application would start to execute if submitted to specific scheduled computer systems. The second problem is gaining simultaneous access to multiple computer systems so that distributed applications can be executed. We help address this problem by investigating how to support advance reservations in local scheduling systems. Our approaches to both of these problems are based on predictions for the execution time of applications on space- shared parallel computers. As a side effect of this work, we also discuss how predictions of application run times can be used to improve scheduling performance.
Experiments with a decision-theoretic scheduler

NASA Technical Reports Server (NTRS)

Hansson, Othar; Holt, Gerhard; Mayer, Andrew

1992-01-01

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

NASA Technical Reports Server (NTRS)

Chien, S.; Gratch, J.

1994-01-01

One drawback to using constraint-propagation in planning and scheduling systems is that when a problem has an unsatisfiable set of constraints such algorithms typically only show that no solution exists. While, technically correct, in practical situations, it is desirable in these cases to produce a satisficing solution that satisfies the most important constraints (typically defined in terms of maximizing a utility function). This paper describes an iterative constraint relaxation approach in which the scheduler uses heuristics to progressively relax problem constraints until the problem becomes satisfiable. We present empirical results of applying these techniques to the problem of scheduling spacecraft communications for JPL/NASA antenna resources.
A New Lagrangian Relaxation Method Considering Previous Hour Scheduling for Unit Commitment Problem

NASA Astrophysics Data System (ADS)

Khorasani, H.; Rashidinejad, M.; Purakbari-Kasmaie, M.; Abdollahi, A.

2009-08-01

Generation scheduling is a crucial challenge in power systems especially under new environment of liberalization of electricity industry. A new Lagrangian relaxation method for unit commitment (UC) has been presented for solving generation scheduling problem. This paper focuses on the economical aspect of UC problem, while the previous hour scheduling as a very important issue is studied. In this paper generation scheduling of present hour has been conducted by considering the previous hour scheduling. The impacts of hot/cold start-up cost have been taken in to account in this paper. Case studies and numerical analysis presents significant outcomes while it demonstrates the effectiveness of the proposed method.
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.
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.
78 FR 17234 - Advisory Committee for Mathematical Sciences and Physical Sciences #66; Notice of Meeting

Federal Register 2010, 2011, 2012, 2013, 2014

2013-03-20

... Officer at the above address or the Web site at http://www.nsf.gov/mps/advisory.jsp . Purpose of Meeting... Opportunities in Science and Engineering, and the Advisory Committee for International Science and Engineering...
Coordinating space telescope operations in an integrated planning and scheduling architecture

NASA Technical Reports Server (NTRS)

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

1992-01-01

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

NASA Astrophysics Data System (ADS)

Chou, Hui-Yu; Yang, Jyh-Bin

2017-10-01

The problem of schedule delay commonly occurs in construction projects. The quality of delay analysis depends on the availability of schedule-related information and delay evidence. More information used in delay analysis usually produces more accurate and fair analytical results. How to use innovative techniques to improve the quality of schedule delay analysis results have received much attention recently. As Building Information Modeling (BIM) technique has been quickly developed, using BIM and 4D simulation techniques have been proposed and implemented. Obvious benefits have been achieved especially in identifying and solving construction consequence problems in advance of construction. This study preforms an intensive literature review to discuss the problems encountered in schedule delay analysis and the possibility of using BIM as a tool in developing a BIM-based approach for schedule delay analysis. This study believes that most of the identified problems can be dealt with by BIM technique. Research results could be a fundamental of developing new approaches for resolving schedule delay disputes.
Further Evaluation of the Use of Multiple Schedules for Behavior Maintained by Negative Reinforcement.

PubMed

Campos, Claudia; Leon, Yanerys; Sleiman, Andressa; Urcuyo, Beatriz

2017-03-01

One potential limitation of functional communication training (FCT) is that after the functional communication response (FCR) is taught, the response may be emitted at high rates or inappropriate times. Thus, schedule thinning is often necessary. Previous research has demonstrated that multiple schedules can facilitate schedule thinning by establishing discriminative control of the communication response while maintaining low rates of problem behavior. To date, most applied research evaluating the clinical utility of multiple schedules has done so in the context of behavior maintained by positive reinforcement (e.g., attention or tangible items). This study examined the use of a multiple schedule with alternating Fixed Ratio (FR 1)/extinction (EXT) components for two individuals with developmental disabilities who emitted escape-maintained problem behavior. Although problem behavior remained low during all FCT and multiple schedule phases, the use of the multiple schedule alone did not result in discriminated manding.
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.
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.
An investigation of the use of temporal decomposition in space mission scheduling

NASA Technical Reports Server (NTRS)

Bullington, Stanley E.; Narayanan, Venkat

1994-01-01

This research involves an examination of techniques for solving scheduling problems in long-duration space missions. The mission timeline is broken up into several time segments, which are then scheduled incrementally. Three methods are presented for identifying the activities that are to be attempted within these segments. The first method is a mathematical model, which is presented primarily to illustrate the structure of the temporal decomposition problem. Since the mathematical model is bound to be computationally prohibitive for realistic problems, two heuristic assignment procedures are also presented. The first heuristic method is based on dispatching rules for activity selection, and the second heuristic assigns performances of a model evenly over timeline segments. These heuristics are tested using a sample Space Station mission and a Spacelab mission. The results are compared with those obtained by scheduling the missions without any problem decomposition. The applicability of this approach to large-scale mission scheduling problems is also discussed.
Analysis of Issues for Project Scheduling by Multiple, Dispersed Schedulers (distributed Scheduling) and Requirements for Manual Protocols and Computer-based Support

NASA Technical Reports Server (NTRS)

Richards, Stephen F.

1991-01-01

Although computerized operations have significant gains realized in many areas, one area, scheduling, has enjoyed few benefits from automation. The traditional methods of industrial engineering and operations research have not proven robust enough to handle the complexities associated with the scheduling of realistic problems. To address this need, NASA has developed the computer-aided scheduling system (COMPASS), a sophisticated, interactive scheduling tool that is in wide-spread use within NASA and the contractor community. Therefore, COMPASS provides no explicit support for the large class of problems in which several people, perhaps at various locations, build separate schedules that share a common pool of resources. This research examines the issue of distributing scheduling, as applied to application domains characterized by the partial ordering of tasks, limited resources, and time restrictions. The focus of this research is on identifying issues related to distributed scheduling, locating applicable problem domains within NASA, and suggesting areas for ongoing research. The issues that this research identifies are goals, rescheduling requirements, database support, the need for communication and coordination among individual schedulers, the potential for expert system support for scheduling, and the possibility of integrating artificially intelligent schedulers into a network of human schedulers.
Automated telescope scheduling

NASA Technical Reports Server (NTRS)

Johnston, Mark D.

1988-01-01

With the ever increasing level of automation of astronomical telescopes the benefits and feasibility of automated planning and scheduling are becoming more apparent. Improved efficiency and increased overall telescope utilization are the most obvious goals. Automated scheduling at some level has been done for several satellite observatories, but the requirements on these systems were much less stringent than on modern ground or satellite observatories. The scheduling problem is particularly acute for Hubble Space Telescope: virtually all observations must be planned in excruciating detail weeks to months in advance. Space Telescope Science Institute has recently made significant progress on the scheduling problem by exploiting state-of-the-art artificial intelligence software technology. What is especially interesting is that this effort has already yielded software that is well suited to scheduling groundbased telescopes, including the problem of optimizing the coordinated scheduling of more than one telescope.
Finland’s Security Solution in the Future

DTIC Science & Technology

2013-03-01

important for foreign and security policies. This part of the world is becoming increasingly important for transport, natural resources and tourism . The...julkaisu/fi.jsp?oid=373066 (accessed December 22, 2012, only in Finnish). 6 Finnish Goverment Communication Department, “Government Security and

Reinforcement learning in scheduling

NASA Technical Reports Server (NTRS)

Dietterich, Tom G.; Ok, Dokyeong; Zhang, Wei; Tadepalli, Prasad

1994-01-01

The goal of this research is to apply reinforcement learning methods to real-world problems like scheduling. In this preliminary paper, we show that learning to solve scheduling problems such as the Space Shuttle Payload Processing and the Automatic Guided Vehicle (AGV) scheduling can be usefully studied in the reinforcement learning framework. We discuss some of the special challenges posed by the scheduling domain to these methods and propose some possible solutions we plan to implement.
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.
Application of decentralized cooperative problem solving in dynamic flexible scheduling

NASA Astrophysics Data System (ADS)

Guan, Zai-Lin; Lei, Ming; Wu, Bo; Wu, Ya; Yang, Shuzi

1995-08-01

The object of this study is to discuss an intelligent solution to the problem of task-allocation in shop floor scheduling. For this purpose, the technique of distributed artificial intelligence (DAI) is applied. Intelligent agents (IAs) are used to realize decentralized cooperation, and negotiation is realized by using message passing based on the contract net model. Multiple agents, such as manager agents, workcell agents, and workstation agents, make game-like decisions based on multiple criteria evaluations. This procedure of decentralized cooperative problem solving makes local scheduling possible. And by integrating such multiple local schedules, dynamic flexible scheduling for the whole shop floor production can be realized.
Predicting Space Weather Effects on Close Approach Events

NASA Technical Reports Server (NTRS)

Hejduk, Matthew D.; Newman, Lauri K.; Besser, Rebecca L.; Pachura, Daniel A.

2015-01-01

The NASA Robotic Conjunction Assessment Risk Analysis (CARA) team sends ephemeris data to the Joint Space Operations Center (JSpOC) for conjunction assessment screening against the JSpOC high accuracy catalog and then assesses risk posed to protected assets from predicted close approaches. Since most spacecraft supported by the CARA team are located in LEO orbits, atmospheric drag is the primary source of state estimate uncertainty. Drag magnitude and uncertainty is directly governed by atmospheric density and thus space weather. At present the actual effect of space weather on atmospheric density cannot be accurately predicted because most atmospheric density models are empirical in nature, which do not perform well in prediction. The Jacchia-Bowman-HASDM 2009 (JBH09) atmospheric density model used at the JSpOC employs a solar storm active compensation feature that predicts storm sizes and arrival times and thus the resulting neutral density alterations. With this feature, estimation errors can occur in either direction (i.e., over- or under-estimation of density and thus drag). Although the exact effect of a solar storm on atmospheric drag cannot be determined, one can explore the effects of JBH09 model error on conjuncting objects' trajectories to determine if a conjunction is likely to become riskier, less risky, or pass unaffected. The CARA team has constructed a Space Weather Trade-Space tool that systematically alters the drag situation for the conjuncting objects and recalculates the probability of collision for each case to determine the range of possible effects on the collision risk. In addition to a review of the theory and the particulars of the tool, the different types of observed output will be explained, along with statistics of their frequency.
Resting metabolic rate of Indian Junior Soccer players: Testing agreement between measured versus selected predictive equations.

PubMed

Cherian, Keren Susan; Shahkar, Faaiza; Sainoji, Ashok; Balakrishna, Nagalla; Yagnambhatt, Venkata Ramana

2018-01-01

Owing to a dearth of research related to Resting Metabolic Rate (RMR) among adolescent athletes in India, our study aimed to document RMR among junior soccer players (JSP) and to identify suitable RMR predictive models for JSP from nine existing equations. Forty Indian JSP (Boys = 21, Girls = 19) representing the under-12 and under-16 age categories were assessed for body composition (skinfold technique) and RMR (oxycon mobile). Two-way ANOVA and ANCOVA were used to examine the differences across age and sex. Bland-Altman plot was used to test agreement between measured vs. predicted RMR using the equations of Cunningham (, The American Journal of Clinical Nutrition, 33), Soares et al. (, European Journal of Clinical Nutrition, 47; 1998, British Journal of Nutrition, 79), Henry (, Public Health Nutrition, 8), and Patil and Bharadwaj (, Journal of Postgraduate Medicine, 59) for non-athletic populations and the equations of De Lorenzo et al. (, The Journal of Sports Medicine and Physical Fitness, 39), Wong et al. (, Singapore Medical Journal, 53), and ten Haaf & Weijs (, PloS One, 9) for adult athletes. RMR showed significant (P < .01) sex differences (Boys: 1343 ± 297.1; Girls: 1135 ± 116.7 kcal·day -1 ). While RMR values adjusted for fat-free mass (FFM) were similar across age and sex. The equation of Soares et al. (, British Journal of Nutrition, 79) for girls and Wong et al. (, Singapore Medical Journal, 53) for boys showed better RMR predictability. FFM explained variation in RMR across age and sex. The FFM-based Soares et al. (, British Journal of Nutrition, 79) equation for girls and body weight-based Wong et al. (, Singapore Medical Journal, 53) equation for boys are best suited for predicting RMR. © 2017 Wiley Periodicals, Inc.
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.
Decision-theoretic control of EUVE telescope scheduling

NASA Technical Reports Server (NTRS)

Hansson, Othar; Mayer, Andrew

1993-01-01

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

NASA Technical Reports Server (NTRS)

Jones, Robert L., III

1995-01-01

A graph-theoretic design process and software tool is defined for selecting a multiprocessing 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. Graph-search algorithms and analysis techniques are introduced and shown to effectively determine performance bounds, scheduling constraints, and resource requirements. The software tool applies the design process to a given problem and includes performance optimization through the inclusion of additional precedence constraints among the schedulable tasks.
The European Medicines Agency experience with biomarker qualification.

PubMed

Manolis, Efthymios; Koch, Armin; Deforce, Dieter; Vamvakas, Spiros

2015-01-01

Since the launch of the qualification process in 2009, the CHMP reviewed/is reviewing 48 requests for qualification advice or opinion (as of Sept 2013) related to biomarkers (BM) or other novel drug development tools (e.g. patient reported outcome measures, modeling, and statistical methods). The qualification opinions are available on the EMA website (Qualification of novel methodologies for medicine development, http://www.ema.europa.eu/ema/index.jsp?curl=pages/regulation/document_listing/document_listing_000319.jsp&mid=WC0b01ac0580022bb0#section2 , 2013). Also there is a trend of increasing numbers of qualification requests to CHMP, indicative of the pace that targeted drug development and personalized medicine is gaining and the need to bring the new tools from research to drug development and clinical use. This chapter will focus on the regulatory experience gained so far from the CHMP qualification procedure. Basic qualification principles will be presented. Through qualification examples, we will elaborate on common grounds and divergences between the different stakeholders.
Designing a fuzzy scheduler for hard real-time systems

NASA Technical Reports Server (NTRS)

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

1992-01-01

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

PubMed

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

2015-01-01

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

PubMed

Wang, Zhaocai; Ji, Zuwen; Wang, Xiaoming; Wu, Tunhua; Huang, Wei

2017-12-01

As a promising approach to solve the computationally intractable problem, the method based on DNA computing is an emerging research area including mathematics, computer science and molecular biology. The task scheduling problem, as a well-known NP-complete problem, arranges n jobs to m individuals and finds the minimum execution time of last finished individual. In this paper, we use a biologically inspired computational model and describe a new parallel algorithm to solve the task scheduling problem by basic DNA molecular operations. In turn, we skillfully design flexible length DNA strands to represent elements of the allocation matrix, take appropriate biological experiment operations and get solutions of the task scheduling problem in proper length range with less than O(n 2 ) time complexity. Copyright © 2017. Published by Elsevier B.V.
A hybrid online scheduling mechanism with revision and progressive techniques for autonomous Earth observation satellite

NASA Astrophysics Data System (ADS)

Li, Guoliang; Xing, Lining; Chen, Yingwu

2017-11-01

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

NASA Astrophysics Data System (ADS)

Wu, Zhigang; Li, Zhihong; Yang, Ding; Zhang, Guozhen

With the development of modern information technology, the traditional teaching mode becomes more deficient for the requirement of modern education. Plant Quarantine has been accepted as the common course for the universities of agriculture in China after the entry of WTO. But the teaching resources of this course are not enough especially for most universities with lack base. The characteristic of e-learning is regarded as one way to solve the problem of short teaching resource. PQRTS (Plant Quarantine Remote Teaching System) was designed and developed with JSP (Java Sever Pages), MySQL and Tomcat in this study. The system included many kinds of plant quarantine teaching resources, such as international glossary, regulations and standards, multimedia information of quarantine process and pests, ppt files of teaching, and training exercise. The system prototype implemented the functions of remote learning, querying, management, examination and remote discussion. It could be a tool for teaching, teaching assistance and learning online.
Discrete harmony search algorithm for scheduling and rescheduling the reprocessing problems in remanufacturing: a case study

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.
Solving multi-objective job shop scheduling problems using a non-dominated sorting genetic algorithm

NASA Astrophysics Data System (ADS)

Piroozfard, Hamed; Wong, Kuan Yew

2015-05-01

The efforts of finding optimal schedules for the job shop scheduling problems are highly important for many real-world industrial applications. In this paper, a multi-objective based job shop scheduling problem by simultaneously minimizing makespan and tardiness is taken into account. The problem is considered to be more complex due to the multiple business criteria that must be satisfied. To solve the problem more efficiently and to obtain a set of non-dominated solutions, a meta-heuristic based non-dominated sorting genetic algorithm is presented. In addition, task based representation is used for solution encoding, and tournament selection that is based on rank and crowding distance is applied for offspring selection. Swapping and insertion mutations are employed to increase diversity of population and to perform intensive search. To evaluate the modified non-dominated sorting genetic algorithm, a set of modified benchmarking job shop problems obtained from the OR-Library is used, and the results are considered based on the number of non-dominated solutions and quality of schedules obtained by the algorithm.
78 FR 60256 - Initial Patent Applications

Federal Register 2010, 2011, 2012, 2013, 2014

2013-10-01

... patent statutes and regulations to be issued as a patent. Most applications for patent, including new.../process/fiie/efs/guidance/New legal framework.jsp, provides a listing of patent applications and documents... declaration forms that were created to comply with the changes resulting from the Leahy-Smith America Invents...
Investigations into Generalization of Constraint-Based Scheduling Theories with Applications to Space Telescope Observation Scheduling

NASA Technical Reports Server (NTRS)

Muscettola, Nicola; Smith, Steven S.

1996-01-01

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

NASA Technical Reports Server (NTRS)

Johnston, Mark; Miller, Glenn; Sponsler, Jeff; Vick, Shon; Jackson, Robert

1990-01-01

Efficient utilization of spacecraft resources is essential, but the accompanying scheduling problems are often computationally intractable and are difficult to approximate because of the presence of numerous interacting constraints. Artificial intelligence techniques were applied to the scheduling of the NASA/ESA Hubble Space Telescope (HST). This presents a particularly challenging problem since a yearlong observing program can contain some tens of thousands of exposures which are subject to a large number of scientific, operational, spacecraft, and environmental constraints. New techniques were developed for machine reasoning about scheduling constraints and goals, especially in cases where uncertainty is an important scheduling consideration and where resolving conflicts among conflicting preferences is essential. These technique were utilized in a set of workstation based scheduling tools (Spike) for HST. Graphical displays of activities, constraints, and schedules are an important feature of the system. High level scheduling strategies using both rule based and neural network approaches were developed. While the specific constraints implemented are those most relevant to HST, the framework developed is far more general and could easily handle other kinds of scheduling problems. The concept and implementation of the Spike system are described along with some experiments in adapting Spike to other spacecraft scheduling domains.

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.
What work schedule characteristics constitute a problem to the individual? A representative study of Swedish shift workers.

PubMed

Åkerstedt, Torbjörn; Kecklund, Göran

2017-03-01

The purpose was to investigate which detailed characteristics of shift schedules that are seen as problems to those exposed. A representative national sample of non-day workers (N = 2031) in Sweden was asked whether they had each of a number of particular work schedule characteristics and, if yes, to what extent this constituted a "big problem in life". It was also inquired whether the individual's work schedules had negative consequences for fatigue, sleep and social life. The characteristic with the highest percentage reporting a big problem was "short notice (<1 month) of a new work schedule" (30.5%), <11 h off between shifts (27.8%), and split duty (>1.5 h break at mid-shift, 27.2%). Overtime (>10 h/week), night work, morning work, day/night shifts showed lower prevalences of being a "big problem". Women indicated more problems in general. Short notice was mainly related to negative social effects, while <11 h off between shifts was related to disturbed sleep, fatigue and social difficulties. It was concluded that schedules involving unpredictable working hours (short notice), short daily rest between shifts, and split duty shifts constitute big problems. The results challenge current views of what aspects of shift work need improvement, and negative social consequences seem more important than those related to health. Copyright Â© 2016 Elsevier Ltd. All rights reserved.
Service-Oriented Node Scheduling Scheme for Wireless Sensor Networks Using Markov Random Field Model

PubMed Central

Cheng, Hongju; Su, Zhihuang; Lloret, Jaime; Chen, Guolong

2014-01-01

Future wireless sensor networks are expected to provide various sensing services and energy efficiency is one of the most important criterions. The node scheduling strategy aims to increase network lifetime by selecting a set of sensor nodes to provide the required sensing services in a periodic manner. In this paper, we are concerned with the service-oriented node scheduling problem to provide multiple sensing services while maximizing the network lifetime. We firstly introduce how to model the data correlation for different services by using Markov Random Field (MRF) model. Secondly, we formulate the service-oriented node scheduling issue into three different problems, namely, the multi-service data denoising problem which aims at minimizing the noise level of sensed data, the representative node selection problem concerning with selecting a number of active nodes while determining the services they provide, and the multi-service node scheduling problem which aims at maximizing the network lifetime. Thirdly, we propose a Multi-service Data Denoising (MDD) algorithm, a novel multi-service Representative node Selection and service Determination (RSD) algorithm, and a novel MRF-based Multi-service Node Scheduling (MMNS) scheme to solve the above three problems respectively. Finally, extensive experiments demonstrate that the proposed scheme efficiently extends the network lifetime. PMID:25384005
A bicriteria heuristic for an elective surgery scheduling problem.

PubMed

Marques, Inês; Captivo, M Eugénia; Vaz Pato, Margarida

2015-09-01

Resource rationalization and reduction of waiting lists for surgery are two main guidelines for hospital units outlined in the Portuguese National Health Plan. This work is dedicated to an elective surgery scheduling problem arising in a Lisbon public hospital. In order to increase the surgical suite's efficiency and to reduce the waiting lists for surgery, two objectives are considered: maximize surgical suite occupation and maximize the number of surgeries scheduled. This elective surgery scheduling problem consists of assigning an intervention date, an operating room and a starting time for elective surgeries selected from the hospital waiting list. Accordingly, a bicriteria surgery scheduling problem arising in the hospital under study is presented. To search for efficient solutions of the bicriteria optimization problem, the minimization of a weighted Chebyshev distance to a reference point is used. A constructive and improvement heuristic procedure specially designed to address the objectives of the problem is developed and results of computational experiments obtained with empirical data from the hospital are presented. This study shows that by using the bicriteria approach presented here it is possible to build surgical plans with very good performance levels. This method can be used within an interactive approach with the decision maker. It can also be easily adapted to other hospitals with similar scheduling conditions.
Automatic Generation of Heuristics for Scheduling

NASA Technical Reports Server (NTRS)

Morris, Robert A.; Bresina, John L.; Rodgers, Stuart M.

1997-01-01

This paper presents a technique, called GenH, that automatically generates search heuristics for scheduling problems. The impetus for developing this technique is the growing consensus that heuristics encode advice that is, at best, useful in solving most, or typical, problem instances, and, at worst, useful in solving only a narrowly defined set of instances. In either case, heuristic problem solvers, to be broadly applicable, should have a means of automatically adjusting to the idiosyncrasies of each problem instance. GenH generates a search heuristic for a given problem instance by hill-climbing in the space of possible multi-attribute heuristics, where the evaluation of a candidate heuristic is based on the quality of the solution found under its guidance. We present empirical results obtained by applying GenH to the real world problem of telescope observation scheduling. These results demonstrate that GenH is a simple and effective way of improving the performance of an heuristic scheduler.
Optimizing an F-16 Squadron Weekly Pilot Schedule for the Turkish Air Force

DTIC Science & Technology

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
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.
Scheduling language and algorithm development study. Volume 1, phase 2: Design considerations for a scheduling and resource allocation system

NASA Technical Reports Server (NTRS)

Morrell, R. A.; Odoherty, R. J.; Ramsey, H. R.; Reynolds, C. C.; Willoughby, J. K.; Working, R. D.

1975-01-01

Data and analyses related to a variety of algorithms for solving typical large-scale scheduling and resource allocation problems are presented. The capabilities and deficiencies of various alternative problem solving strategies are discussed from the viewpoint of computer system design.
A Genetic Algorithm for Flow Shop Scheduling with Assembly Operations to Minimize Makespan

NASA Astrophysics Data System (ADS)

Bhongade, A. S.; Khodke, P. M.

2014-04-01

Manufacturing systems, in which, several parts are processed through machining workstations and later assembled to form final products, is common. Though scheduling of such problems are solved using heuristics, available solution approaches can provide solution for only moderate sized problems due to large computation time required. In this work, scheduling approach is developed for such flow-shop manufacturing system having machining workstations followed by assembly workstations. The initial schedule is generated using Disjunctive method and genetic algorithm (GA) is applied further for generating schedule for large sized problems. GA is found to give near optimal solution based on the deviation of makespan from lower bound. The lower bound of makespan of such problem is estimated and percent deviation of makespan from lower bounds is used as a performance measure to evaluate the schedules. Computational experiments are conducted on problems developed using fractional factorial orthogonal array, varying the number of parts per product, number of products, and number of workstations (ranging upto 1,520 number of operations). A statistical analysis indicated the significance of all the three factors considered. It is concluded that GA method can obtain optimal makespan.
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.
Hybrid Pareto artificial bee colony algorithm for multi-objective single machine group scheduling problem with sequence-dependent setup times and learning effects.

PubMed

Yue, Lei; Guan, Zailin; Saif, Ullah; Zhang, Fei; Wang, Hao

2016-01-01

Group scheduling is significant for efficient and cost effective production system. However, there exist setup times between the groups, which require to decrease it by sequencing groups in an efficient way. Current research is focused on a sequence dependent group scheduling problem with an aim to minimize the makespan in addition to minimize the total weighted tardiness simultaneously. In most of the production scheduling problems, the processing time of jobs is assumed as fixed. However, the actual processing time of jobs may be reduced due to "learning effect". The integration of sequence dependent group scheduling problem with learning effects has been rarely considered in literature. Therefore, current research considers a single machine group scheduling problem with sequence dependent setup times and learning effects simultaneously. A novel hybrid Pareto artificial bee colony algorithm (HPABC) with some steps of genetic algorithm is proposed for current problem to get Pareto solutions. Furthermore, five different sizes of test problems (small, small medium, medium, large medium, large) are tested using proposed HPABC. Taguchi method is used to tune the effective parameters of the proposed HPABC for each problem category. The performance of HPABC is compared with three famous multi objective optimization algorithms, improved strength Pareto evolutionary algorithm (SPEA2), non-dominated sorting genetic algorithm II (NSGAII) and particle swarm optimization algorithm (PSO). Results indicate that HPABC outperforms SPEA2, NSGAII and PSO and gives better Pareto optimal solutions in terms of diversity and quality for almost all the instances of the different sizes of problems.
Integrated resource scheduling in a distributed scheduling environment

NASA Technical Reports Server (NTRS)

Zoch, David; Hall, Gardiner

1988-01-01

The Space Station era presents a highly-complex multi-mission planning and scheduling environment exercised over a highly distributed system. In order to automate the scheduling process, customers require a mechanism for communicating their scheduling requirements to NASA. A request language that a remotely-located customer can use to specify his scheduling requirements to a NASA scheduler, thus automating the customer-scheduler interface, is described. This notation, Flexible Envelope-Request Notation (FERN), allows the user to completely specify his scheduling requirements such as resource usage, temporal constraints, and scheduling preferences and options. The FERN also contains mechanisms for representing schedule and resource availability information, which are used in the inter-scheduler inconsistency resolution process. Additionally, a scheduler is described that can accept these requests, process them, generate schedules, and return schedule and resource availability information to the requester. The Request-Oriented Scheduling Engine (ROSE) was designed to function either as an independent scheduler or as a scheduling element in a network of schedulers. When used in a network of schedulers, each ROSE communicates schedule and resource usage information to other schedulers via the FERN notation, enabling inconsistencies to be resolved between schedulers. Individual ROSE schedules are created by viewing the problem as a constraint satisfaction problem with a heuristically guided search strategy.
Decomposition of timed automata for solving scheduling problems

NASA Astrophysics Data System (ADS)

Nishi, Tatsushi; Wakatake, Masato

2014-03-01

A decomposition algorithm for scheduling problems based on timed automata (TA) model is proposed. The problem is represented as an optimal state transition problem for TA. The model comprises of the parallel composition of submodels such as jobs and resources. The procedure of the proposed methodology can be divided into two steps. The first step is to decompose the TA model into several submodels by using decomposable condition. The second step is to combine individual solution of subproblems for the decomposed submodels by the penalty function method. A feasible solution for the entire model is derived through the iterated computation of solving the subproblem for each submodel. The proposed methodology is applied to solve flowshop and jobshop scheduling problems. Computational experiments demonstrate the effectiveness of the proposed algorithm compared with a conventional TA scheduling algorithm without decomposition.
A controlled genetic algorithm by fuzzy logic and belief functions for job-shop scheduling.

PubMed

Hajri, S; Liouane, N; Hammadi, S; Borne, P

2000-01-01

Most scheduling problems are highly complex combinatorial problems. However, stochastic methods such as genetic algorithm yield good solutions. In this paper, we present a controlled genetic algorithm (CGA) based on fuzzy logic and belief functions to solve job-shop scheduling problems. For better performance, we propose an efficient representational scheme, heuristic rules for creating the initial population, and a new methodology for mixing and computing genetic operator probabilities.
Scheduling in the Face of Uncertain Resource Consumption and Utility

NASA Technical Reports Server (NTRS)

Frank, Jeremy; Dearden, Richard

2003-01-01

We discuss the problem of scheduling tasks that consume uncertain amounts of a resource with known capacity and where the tasks have uncertain utility. In these circumstances, we would like to find schedules that exceed a lower bound on the expected utility when executed. We show that the problems are NP- complete, and present some results that characterize the behavior of some simple heuristics over a variety of problem classes.
Scheduling Earth Observing Fleets Using Evolutionary Algorithms: Problem Description and Approach

NASA Technical Reports Server (NTRS)

Globus, Al; Crawford, James; Lohn, Jason; Morris, Robert; Clancy, Daniel (Technical Monitor)

2002-01-01

We describe work in progress concerning multi-instrument, multi-satellite scheduling. Most, although not all, Earth observing instruments currently in orbit are unique. In the relatively near future, however, we expect to see fleets of Earth observing spacecraft, many carrying nearly identical instruments. This presents a substantially new scheduling challenge. Inspired by successful commercial applications of evolutionary algorithms in scheduling domains, this paper presents work in progress regarding the use of evolutionary algorithms to solve a set of Earth observing related model problems. Both the model problems and the software are described. Since the larger problems will require substantial computation and evolutionary algorithms are embarrassingly parallel, we discuss our parallelization techniques using dedicated and cycle-scavenged workstations.
The "Journal of School Psychology's" First Twenty Years: Contributions and Contributors.

ERIC Educational Resources Information Center

Oakland, Thomas

1984-01-01

Examined the 74 issues that comprise volumes 1-20 of the "Journal of School Psychology" (JSP) to determine the number of articles (N=709), the name and number of authors and coauthors (N=910), and the number of separate references (N=6,722) that appeared. (LLL)
Integrating Space into an Air Expeditionary Force

DTIC Science & Technology

1999-04-01

National Guard in space. Further thanks go out to Col Andersson, Col Hoapili, CAPT Huffine, LTC Glen Collins, USA, LTC Bill Bayles, USA, Maj Brian Creelman ...should be the senior space professional in theater, regardless of service. The main questions regarding a JSpOTF pertain to this task force’s physical
76 FR 6162 - Public Availability of the National Science Foundation FY 2010 Service Contract Inventory

Federal Register 2010, 2011, 2012, 2013, 2014

2011-02-03

... National Science Foundation homepage at the following link: http://www.nsf.gov/publications/pub_summ.jsp... NATIONAL SCIENCE FOUNDATION Public Availability of the National Science Foundation FY 2010 Service Contract Inventory AGENCY: National Science Foundation. ACTION: Notice of Public Availability of FY 2010...
77 FR 40341 - Proposed Information Collection; Comment Request; Application for Appointment in the NOAA...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-07-09

... recommendation, and official transcripts. A personal interview must also be conducted. Eligibility requirements.../erecruit/login.jsp ) and then submit paper forms via mail. An in-person interview is also required. III... of Respondents: 1,800. Estimated Time per Response: written applications, 2 hours; interviews, 5...

File System Virtual Appliances

DTIC Science & Technology

2010-05-01

Technical Conference. USENIX Association, Berkeley, CA, 24–24. [31] Eisler , M., Corbett, P., Kazar, M., Nydick, D. S., and Wagner, C. 2007. Data ONTAP GX...and Operations Market Through 2012. http://www.gartner.com/it/page.jsp?id=638207. [37] Gingell, R. A., Moran, J. P., and Shannon, W. A. 1987 . Virtual
Contingency rescheduling of spacecraft operations

NASA Technical Reports Server (NTRS)

Britt, Daniel L.; Geoffroy, Amy L.; Gohring, John R.

1988-01-01

Spacecraft activity scheduling was a focus of attention in artificial intelligence recently. Several scheduling systems were devised which more-or-less successfully address various aspects of the activity scheduling problem, though most of these are not yet mature, with the notable expection of NASA's ESP. Few current scheduling systems, however, make any attempt to deal fully with the problem of modifying a schedule in near-real-time in the event of contingencies which may arise during schedule execution. These contingencies can include resources becoming unavailable unpredictably, a change in spacecraft conditions or environment, or the need to perform an activity not scheduled. In these cases it becomes necessary to repair an existing schedule, disrupting ongoing operations as little as possible. Normal scheduling is just a part of that which must be accomplished during contingency rescheduling. A prototype system named MAESTRO was developed for spacecraft activity scheduling. MAESTRO is briefly described with a focus on recent work in the area of real-time contingency handling. Included is a discussion of some of the complexities of the scheduling problem and how they affect contingency rescheduling, such as temporal constraints between activities, activities which may be interrupted and continued in any of several ways, and different ways to choose a resource complement which will allow continuation of an activity. Various heuristics used in MAESTRO for contingency rescheduling is discussed, as are operational concerns such as interaction of the scheduler with spacecraft subsystems controllers.
Using Multiple Schedules During Functional Communication Training to Promote Rapid Transfer of Treatment Effects

PubMed Central

Fisher, Wayne W.; Greer, Brian D.; Fuhrman, Ashley M.; Querim, Angie C.

2016-01-01

Multiple schedules with signaled periods of reinforcement and extinction have been used to thin reinforcement schedules during functional communication training (FCT) to make the intervention more practical for parents and teachers. We evaluated whether these signals would also facilitate rapid transfer of treatment effects from one setting to the next and from one therapist to the next. With two children, we conducted FCT in the context of mixed (baseline) and multiple (treatment) schedules introduced across settings or therapists using a multiple baseline design. Results indicated that when the multiple schedules were introduced, the functional communication response came under rapid discriminative control, and problem behavior remained at near-zero rates. We extended these findings with another individual by using a more traditional baseline in which problem behavior produced reinforcement. Results replicated those of the previous participants and showed rapid reductions in problem behavior when multiple schedules were implemented across settings. PMID:26384141
A Simulation Based Approach to Optimize Berth Throughput Under Uncertainty at Marine Container Terminals

NASA Technical Reports Server (NTRS)

Golias, Mihalis M.

2011-01-01

Berth scheduling is a critical function at marine container terminals and determining the best berth schedule depends on several factors including the type and function of the port, size of the port, location, nearby competition, and type of contractual agreement between the terminal and the carriers. In this paper we formulate the berth scheduling problem as a bi-objective mixed-integer problem with the objective to maximize customer satisfaction and reliability of the berth schedule under the assumption that vessel handling times are stochastic parameters following a discrete and known probability distribution. A combination of an exact algorithm, a Genetic Algorithms based heuristic and a simulation post-Pareto analysis is proposed as the solution approach to the resulting problem. Based on a number of experiments it is concluded that the proposed berth scheduling policy outperforms the berth scheduling policy where reliability is not considered.
Using multiple schedules during functional communication training to promote rapid transfer of treatment effects.

PubMed

Fisher, Wayne W; Greer, Brian D; Fuhrman, Ashley M; Querim, Angie C

2015-12-01

Multiple schedules with signaled periods of reinforcement and extinction have been used to thin reinforcement schedules during functional communication training (FCT) to make the intervention more practical for parents and teachers. We evaluated whether these signals would also facilitate rapid transfer of treatment effects across settings and therapists. With 2 children, we conducted FCT in the context of mixed (baseline) and multiple (treatment) schedules introduced across settings or therapists using a multiple baseline design. Results indicated that when the multiple schedules were introduced, the functional communication response came under rapid discriminative control, and problem behavior remained at near-zero rates. We extended these findings with another individual by using a more traditional baseline in which problem behavior produced reinforcement. Results replicated those of the previous participants and showed rapid reductions in problem behavior when multiple schedules were implemented across settings. © Society for the Experimental Analysis of Behavior.
Overview of Human-Centric Space Situational Awareness (SSA) Science and Technology (S&T)

NASA Astrophysics Data System (ADS)

Ianni, J.; Aleva, D.; Ellis, S.

2012-09-01

A number of organizations, within the government, industry, and academia, are researching ways to help humans understand and react to events in space. The problem is both helped and complicated by the fact that there are numerous data sources that need to be planned (i.e., tasked), collected, processed, analyzed, and disseminated. A large part of the research is in support of the Joint Space Operational Center (JSpOC), National Air and Space Intelligence Center (NASIC), and similar organizations. Much recent research has been specifically targeting the JSpOC Mission System (JMS) which has provided a unifying software architecture. This paper will first outline areas of science and technology (S&T) related to human-centric space situational awareness (SSA) and space command and control (C2) including: 1. Object visualization - especially data fused from disparate sources. Also satellite catalog visualizations that convey the physical relationships between space objects. 2. Data visualization - improve data trend analysis as in visual analytics and interactive visualization; e.g., satellite anomaly trends over time, space weather visualization, dynamic visualizations 3. Workflow support - human-computer interfaces that encapsulate multiple computer services (i.e., algorithms, programs, applications) into a 4. Command and control - e.g., tools that support course of action (COA) development and selection, tasking for satellites and sensors, etc. 5. Collaboration - improve individuals or teams ability to work with others; e.g., video teleconferencing, shared virtual spaces, file sharing, virtual white-boards, chat, and knowledge search. 6. Hardware/facilities - e.g., optimal layouts for operations centers, ergonomic workstations, immersive displays, interaction technologies, and mobile computing. Secondly we will provide a survey of organizations working these areas and suggest where more attention may be needed. Although no detailed master plan exists for human-centric SSA and C2, we see little redundancy among the groups supporting SSA human factors at this point.
Capability of the Maximax&Maximin selection operator in the evolutionary algorithm for a nurse scheduling problem

NASA Astrophysics Data System (ADS)

Ramli, Razamin; Tein, Lim Huai

2016-08-01

A good work schedule can improve hospital operations by providing better coverage with appropriate staffing levels in managing nurse personnel. Hence, constructing the best nurse work schedule is the appropriate effort. In doing so, an improved selection operator in the Evolutionary Algorithm (EA) strategy for a nurse scheduling problem (NSP) is proposed. The smart and efficient scheduling procedures were considered. Computation of the performance of each potential solution or schedule was done through fitness evaluation. The best so far solution was obtained via special Maximax&Maximin (MM) parent selection operator embedded in the EA, which fulfilled all constraints considered in the NSP.
Scheduling multirobot operations in manufacturing by truncated Petri nets

NASA Astrophysics Data System (ADS)

Chen, Qin; Luh, J. Y.

1995-08-01

Scheduling of operational sequences in manufacturing processes is one of the important problems in automation. Methods of applying Petri nets to model and analyze the problem with constraints on precedence relations, multiple resources allocation, etc. have been available in literature. Searching for an optimum schedule can be implemented by combining the branch-and-bound technique with the execution of the timed Petri net. The process usually produces a large Petri net which is practically not manageable. This disadvantage, however, can be handled by a truncation technique which divides the original large Petri net into several smaller size subnets. The complexity involved in the analysis of each subnet individually is greatly reduced. However, when the locally optimum schedules of the resulting subnets are combined together, it may not yield an overall optimum schedule for the original Petri net. To circumvent this problem, algorithms are developed based on the concepts of Petri net execution and modified branch-and-bound process. The developed technique is applied to a multi-robot task scheduling problem of the manufacturing work cell.
Scheduling in the Face of Uncertain Resource Consumption and Utility

NASA Technical Reports Server (NTRS)

Koga, Dennis (Technical Monitor); Frank, Jeremy; Dearden, Richard

2003-01-01

We discuss the problem of scheduling tasks that consume a resource with known capacity and where the tasks have varying utility. We consider problems in which the resource consumption and utility of each activity is described by probability distributions. In these circumstances, we would like to find schedules that exceed a lower bound on the expected utility when executed. We first show that while some of these problems are NP-complete, others are only NP-Hard. We then describe various heuristic search algorithms to solve these problems and their drawbacks. Finally, we present empirical results that characterize the behavior of these heuristics over a variety of problem classes.
A novel discrete PSO algorithm for solving job shop scheduling problem to minimize makespan

NASA Astrophysics Data System (ADS)

Rameshkumar, K.; Rajendran, C.

2018-02-01

In this work, a discrete version of PSO algorithm is proposed to minimize the makespan of a job-shop. A novel schedule builder has been utilized to generate active schedules. The discrete PSO is tested using well known benchmark problems available in the literature. The solution produced by the proposed algorithms is compared with best known solution published in the literature and also compared with hybrid particle swarm algorithm and variable neighborhood search PSO algorithm. The solution construction methodology adopted in this study is found to be effective in producing good quality solutions for the various benchmark job-shop scheduling problems.
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.
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.
Empirical results on scheduling and dynamic backtracking

NASA Technical Reports Server (NTRS)

Boddy, Mark S.; Goldman, Robert P.

1994-01-01

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

PubMed

Reed, Derek D; Martens, Brian K

2008-01-01

We conducted an experimental analysis of children's relative problem-completion rates across two workstations under conditions of equal (Experiment 1) and unequal (Experiment 2) problem difficulty. Results were described using the generalized matching equation and were evaluated for degree of schedule versus stimulus control. Experiment 1 involved a symmetrical choice arrangement in which the children could earn points exchangeable for rewards contingent on correct math problem completion. Points were delivered according to signaled variable-interval schedules at each workstation. For 2 children, relative rates of problem completion appeared to have been controlled by the schedule requirements in effect and matched relative rates of reinforcement, with sensitivity values near 1 and bias values near 0. Experiment 2 involved increasing the difficulty of math problems at one of the workstations. Sensitivity values for all 3 participants were near 1, but a substantial increase in bias toward the easier math problems was observed. This bias was possibly associated with responding at the more difficult workstation coming under stimulus control rather than schedule control.
Analysis of Feeder Bus Network Design and Scheduling Problems

PubMed Central

Almasi, Mohammad Hadi; Karim, Mohamed Rehan

2014-01-01

A growing concern for public transit is its inability to shift passenger's mode from private to public transport. In order to overcome this problem, a more developed feeder bus network and matched schedules will play important roles. The present paper aims to review some of the studies performed on Feeder Bus Network Design and Scheduling Problem (FNDSP) based on three distinctive parts of the FNDSP setup, namely, problem description, problem characteristics, and solution approaches. The problems consist of different subproblems including data preparation, feeder bus network design, route generation, and feeder bus scheduling. Subsequently, descriptive analysis and classification of previous works are presented to highlight the main characteristics and solution methods. Finally, some of the issues and trends for future research are identified. This paper is targeted at dealing with the FNDSP to exhibit strategic and tactical goals and also contributes to the unification of the field which might be a useful complement to the few existing reviews. PMID:24526890
A genetic algorithm-based approach to flexible flow-line scheduling with variable lot sizes.

PubMed

Lee, I; Sikora, R; Shaw, M J

1997-01-01

Genetic algorithms (GAs) have been used widely for such combinatorial optimization problems as the traveling salesman problem (TSP), the quadratic assignment problem (QAP), and job shop scheduling. In all of these problems there is usually a well defined representation which GA's use to solve the problem. We present a novel approach for solving two related problems-lot sizing and sequencing-concurrently using GAs. The essence of our approach lies in the concept of using a unified representation for the information about both the lot sizes and the sequence and enabling GAs to evolve the chromosome by replacing primitive genes with good building blocks. In addition, a simulated annealing procedure is incorporated to further improve the performance. We evaluate the performance of applying the above approach to flexible flow line scheduling with variable lot sizes for an actual manufacturing facility, comparing it to such alternative approaches as pair wise exchange improvement, tabu search, and simulated annealing procedures. The results show the efficacy of this approach for flexible flow line scheduling.
Optimization of multi-objective integrated process planning and scheduling problem using a priority based optimization algorithm

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.
An Integrated Constraint Programming Approach to Scheduling Sports Leagues with Divisional and Round-robin Tournaments

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

Carlsson, Mats; Johansson, Mikael; Larson, Jeffrey

Previous approaches for scheduling a league with round-robin and divisional tournaments involved decomposing the problem into easier subproblems. This approach, used to schedule the top Swedish handball league Elitserien, reduces the problem complexity but can result in suboptimal schedules. This paper presents an integrated constraint programming model that allows to perform the scheduling in a single step. Particular attention is given to identifying implied and symmetry-breaking constraints that reduce the computational complexity significantly. The experimental evaluation of the integrated approach takes considerably less computational effort than the previous approach.
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).

Multi-Objective Scheduling for the Cluster II Constellation

NASA Technical Reports Server (NTRS)

Johnston, Mark D.; Giuliano, Mark

2011-01-01

This paper describes the application of the MUSE multiobjecctive scheduling framework to the Cluster II WBD scheduling domain. Cluster II is an ESA four-spacecraft constellation designed to study the plasma environment of the Earth and it's magnetosphere. One of the instruments on each of the four spacecraft is the Wide Band Data (WBD) plasma wave experiment. We have applied the MUSE evolutionary algorithm to the scheduling problem represented by this instrument, and the result has been adopted and utilized by the WBD schedulers for nearly a year. This paper describes the WBD scheduling problem, its representation in MUSE, and some of the visualization elements that provide insight into objective value tradeoffs.
23 CFR 630.1110 - Maintenance of temporary traffic control devices.

Code of Federal Regulations, 2010 CFR

2010-04-01

... available for purchase from ATSSA through the following URL: http://www.atssa.com/store/bc_item_detail.jsp... http://dot.state.il.us/workzone/wztcd2004r.pdf. The Minnesota Department of Transportation “Quality... Unacceptable” is available online at http://www.dot.state.mn.us/trafficeng/otepubl/fieldmanual2007/FM-2007...
The Arizona Journey Schools Program: A Strategy for Change. Final Report.

ERIC Educational Resources Information Center

Laughran, Laura J.; Shaw, Jerome M.

The Arizona Journey Schools Program (JSP) was a two-year professional development experience whose stated purpose was to build the leadership capacity of school/community teams and establish a network of professionals to support teams as they bring about systemic change in mathematics and science teaching, learning, and assessment. This report…
Job Skills Program Biennial Report 1985-1987.

ERIC Educational Resources Information Center

Washington State Board for Vocational Education, Olympia.

The Washington State Job Skills Program (JSP) was established by the legislature in 1983 as an economic development incentive to provide customized, quick-start training to meet the employment needs of new or expanding businesses in the state. Funds are granted to public and private educational institutions to train people for new jobs, prepare…
Architecture for Cyber Defense Simulator in Military Applications

DTIC Science & Technology

2013-06-01

ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5977648&isnumber=5977431 [18] Goodall , J.R.; D’Amico, A.; Kopylec, J.K.; , "Camus: Automatically mapping...isnumber=5977431 • [18] Goodall , J.R.; D’Amico, A.; Kopylec, J.K.; , "Camus: Automatically mapping Cyber Assets to Missions and Users," Military
Influencing the Behavior of General Chang Wanquan to Protect United States Space Assets

DTIC Science & Technology

2009-04-01

story_generic.jsp?channel= awst &id=news/CH I01177.xml. Feng, Huiyun. Chinese Strategic Culture and Foreign Policy Decision-Making: Confucianism...Donates Frw350 Million.” The New Times, 22 May 2007. As collected by AllAfrica, Inc. Samovar, Larry A., Richard E. Porter, and Edwin R . McDaniel
Strategic Implications of U.S. Fighter Force Reductions: Air-to-Air Combat Modeling Using Lanchester Equations

DTIC Science & Technology

2011-06-01

Retrieved from http://www.aviationweek.com/aw/generic/channel_awst.jsp?channel= awst on multiple occasions. Baron, Kevin. “Retiring Air Force...Defense. January 2011a. -----. “The Evolution of PRC Air Power.” Second Line of Defense. January 2011b. 70 Drew, Donald R . and others
Comparison of response times of a mobile-web EHRs system using PHP and JSP languages.

PubMed

De la Torre-Díez, Isabel; Antón-Rodríguez, Míriam; Díaz-Pernas, Francisco Javier; Perozo-Rondón, Freddy José

2012-12-01

Performance evaluation is highly important in the Electronic Health Records (EHRs) system implementation. Response time's measurement can be considered as one manner to make that evaluation. In the e-health field, after the creation of EHRs available through different platforms such as Web and/or mobile, a performance evaluation is necessary. The operation of the system in the right way is essential. In this paper, a comparison of the response times for the MEHRmobile system is presented. The first version uses PHP language with a MySQL database and the second one employs JSP with an eXist database. Both versions have got the same functionalities. In addition to the technological aspects, a significant difference is the way the information is stored. The main goal of this paper is choosing the version which offers better response times. We have created a new benchmark to calculate the response times. Better results have been obtained for the PHP version. Nowadays, this version is being used for specialists from Fundación Intras, Spain.
Exact and Metaheuristic Approaches for a Bi-Objective School Bus Scheduling Problem.

PubMed

Chen, Xiaopan; Kong, Yunfeng; Dang, Lanxue; Hou, Yane; Ye, Xinyue

2015-01-01

As a class of hard combinatorial optimization problems, the school bus routing problem has received considerable attention in the last decades. For a multi-school system, given the bus trips for each school, the school bus scheduling problem aims at optimizing bus schedules to serve all the trips within the school time windows. In this paper, we propose two approaches for solving the bi-objective school bus scheduling problem: an exact method of mixed integer programming (MIP) and a metaheuristic method which combines simulated annealing with local search. We develop MIP formulations for homogenous and heterogeneous fleet problems respectively and solve the models by MIP solver CPLEX. The bus type-based formulation for heterogeneous fleet problem reduces the model complexity in terms of the number of decision variables and constraints. The metaheuristic method is a two-stage framework for minimizing the number of buses to be used as well as the total travel distance of buses. We evaluate the proposed MIP and the metaheuristic method on two benchmark datasets, showing that on both instances, our metaheuristic method significantly outperforms the respective state-of-the-art methods.
The application of artificial intelligence to astronomical scheduling problems

NASA Technical Reports Server (NTRS)

Johnston, Mark D.

1992-01-01

Efficient utilization of expensive space- and ground-based observatories is an important goal for the astronomical community; the cost of modern observing facilities is enormous, and the available observing time is much less than the demand from astronomers around the world. The complexity and variety of scheduling constraints and goals has led several groups to investigate how artificial intelligence (AI) techniques might help solve these kinds of problems. The earliest and most successful of these projects was started at Space Telescope Science Institute in 1987 and has led to the development of the Spike scheduling system to support the scheduling of Hubble Space Telescope (HST). The aim of Spike at STScI is to allocate observations to timescales of days to a week observing all scheduling constraints and maximizing preferences that help ensure that observations are made at optimal times. Spike has been in use operationally for HST since shortly after the observatory was launched in Apr. 1990. Although developed specifically for HST scheduling, Spike was carefully designed to provide a general framework for similar (activity-based) scheduling problems. In particular, the tasks to be scheduled are defined in the system in general terms, and no assumptions about the scheduling timescale are built in. The mechanisms for describing, combining, and propagating temporal and other constraints and preferences are quite general. The success of this approach has been demonstrated by the application of Spike to the scheduling of other satellite observatories: changes to the system are required only in the specific constraints that apply, and not in the framework itself. In particular, the Spike framework is sufficiently flexible to handle both long-term and short-term scheduling, on timescales of years down to minutes or less. This talk will discuss recent progress made in scheduling search techniques, the lessons learned from early HST operations, the application of Spike to other problem domains, and plans for the future evolution of the system.
Non-Evolutionary Algorithms for Scheduling Dependent Tasks in Distributed Heterogeneous Computing Environments

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

Wayne F. Boyer; Gurdeep S. Hura

2005-09-01

The Problem of obtaining an optimal matching and scheduling of interdependent tasks in distributed heterogeneous computing (DHC) environments is well known to be an NP-hard problem. In a DHC system, task execution time is dependent on the machine to which it is assigned and task precedence constraints are represented by a directed acyclic graph. Recent research in evolutionary techniques has shown that genetic algorithms usually obtain more efficient schedules that other known algorithms. We propose a non-evolutionary random scheduling (RS) algorithm for efficient matching and scheduling of inter-dependent tasks in a DHC system. RS is a succession of randomized taskmore » orderings and a heuristic mapping from task order to schedule. Randomized task ordering is effectively a topological sort where the outcome may be any possible task order for which the task precedent constraints are maintained. A detailed comparison to existing evolutionary techniques (GA and PSGA) shows the proposed algorithm is less complex than evolutionary techniques, computes schedules in less time, requires less memory and fewer tuning parameters. Simulation results show that the average schedules produced by RS are approximately as efficient as PSGA schedules for all cases studied and clearly more efficient than PSGA for certain cases. The standard formulation for the scheduling problem addressed in this paper is Rm|prec|Cmax.,« less
Scheduling Future Water Supply Investments Under Uncertainty

NASA Astrophysics Data System (ADS)

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

2014-12-01

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

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.
Constraint-based scheduling

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.
Constraint-based scheduling

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.
Blood Glucose Levels and Problem Behavior

ERIC Educational Resources Information Center

Valdovinos, Maria G.; Weyand, David

2006-01-01

The relationship between varying blood glucose levels and problem behavior during daily scheduled activities was examined. The effects that varying blood glucose levels had on problem behavior during daily scheduled activities were examined. Prior research has shown that differing blood glucose levels can affect behavior and mood. Results of this…
JSpOC Mission System Application Development Environment

NASA Astrophysics Data System (ADS)

Luce, R.; Reele, P.; Sabol, C.; Zetocha, P.; Echeverry, J.; Kim, R.; Golf, B.

2012-09-01

The Joint Space Operations Center (JSpOC) Mission System (JMS) is the program of record tasked with replacing the legacy Space Defense Operations Center (SPADOC) and Astrodynamics Support Workstation (ASW) capabilities by the end of FY2015 as well as providing additional Space Situational Awareness (SSA) and Command and Control (C2) capabilities post-FY2015. To meet the legacy replacement goal, the JMS program is maturing a government Service Oriented Architecture (SOA) infrastructure that supports the integration of mission applications while acquiring mature industry and government mission applications. Future capabilities required by the JSpOC after 2015 will require development of new applications and procedures as well as the exploitation of new SSA data sources. To support the post FY2015 efforts, the JMS program is partnering with the Air Force Research Laboratory (AFRL) to build a JMS application development environment. The purpose of this environment is to: 1) empower the research & development community, through access to relevant tools and data, to accelerate technology development, 2) allow the JMS program to communicate user capability priorities and requirements to the developer community, 3) provide the JMS program with access to state-of-the-art research, development, and computing capabilities, and 4) support market research efforts by identifying outstanding performers that are available to shepherd into the formal transition process. The application development environment will consist of both unclassified and classified environments that can be accessed over common networks (including the Internet) to provide software developers, scientists, and engineers everything they need (e.g., building block JMS services, modeling and simulation tools, relevant test scenarios, documentation, data sources, user priorities/requirements, and SOA integration tools) to develop and test mission applications. The developed applications will be exercised in these relevant environments with representative data sets to help bridge the gap between development and integration into the operational JMS enterprise.
Planning as a Precursor to Scheduling for Space Station Payload Operations

NASA Technical Reports Server (NTRS)

Howell, Eric; Maxwell, Theresa

1995-01-01

Contemporary schedulers attempt to solve the problem of best fitting a set of activities into an available timeframe while still satisfying the necessary constraints. This approach produces results which are optimized for the region of time the scheduler is able to process, satisfying the near term goals of the operation. In general the scheduler is not able to reason about the activities which precede or follow the window into which it is inputs to scheduling so that the intermediate placing activities. This creates a problem for operations which are composed of many activities spanning long durations (which exceed the scheduler's reasoning horizon) such as the continuous operations environment for payload operations on the Space Station. Not only must the near term scheduling objectives be met, but somehow the results of near term scheduling must be made to support the attainment of long term goals.
Spike: AI scheduling for Hubble Space Telescope after 18 months of orbital operations

NASA Technical Reports Server (NTRS)

Johnston, Mark D.

1992-01-01

This paper is a progress report on the Spike scheduling system, developed by the Space Telescope Science Institute for long-term scheduling of Hubble Space Telescope (HST) observations. Spike is an activity-based scheduler which exploits artificial intelligence (AI) techniques for constraint representation and for scheduling search. The system has been in operational use since shortly after HST launch in April 1990. Spike was adopted for several other satellite scheduling problems; of particular interest was the demonstration that the Spike framework is sufficiently flexible to handle both long-term and short-term scheduling, on timescales of years down to minutes or less. We describe the recent progress made in scheduling search techniques, the lessons learned from early HST operations, and the application of Spike to other problem domains. We also describe plans for the future evolution of the system.
Solving the flexible job shop problem by hybrid metaheuristics-based multiagent model

NASA Astrophysics Data System (ADS)

Nouri, Houssem Eddine; Belkahla Driss, Olfa; Ghédira, Khaled

2018-03-01

The flexible job shop scheduling problem (FJSP) is a generalization of the classical job shop scheduling problem that allows to process operations on one machine out of a set of alternative machines. The FJSP is an NP-hard problem consisting of two sub-problems, which are the assignment and the scheduling problems. In this paper, we propose how to solve the FJSP by hybrid metaheuristics-based clustered holonic multiagent model. First, a neighborhood-based genetic algorithm (NGA) is applied by a scheduler agent for a global exploration of the search space. Second, a local search technique is used by a set of cluster agents to guide the research in promising regions of the search space and to improve the quality of the NGA final population. The efficiency of our approach is explained by the flexible selection of the promising parts of the search space by the clustering operator after the genetic algorithm process, and by applying the intensification technique of the tabu search allowing to restart the search from a set of elite solutions to attain new dominant scheduling solutions. Computational results are presented using four sets of well-known benchmark literature instances. New upper bounds are found, showing the effectiveness of the presented approach.

Periodic Heterogeneous Vehicle Routing Problem With Driver Scheduling

NASA Astrophysics Data System (ADS)

Mardiana Panggabean, Ellis; Mawengkang, Herman; Azis, Zainal; Filia Sari, Rina

2018-01-01

The paper develops a model for the optimal management of logistic delivery of a given commodity. The company has different type of vehicles with different capacity to deliver the commodity for customers. The problem is then called Periodic Heterogeneous Vehicle Routing Problem (PHVRP). The goal is to schedule the deliveries according to feasible combinations of delivery days and to determine the scheduling of fleet and driver and routing policies of the vehicles. The objective is to minimize the sum of the costs of all routes over the planning horizon. We propose a combined approach of heuristic algorithm and exact method to solve the problem.
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...
Estimates of the absolute error and a scheme for an approximate solution to scheduling problems

NASA Astrophysics Data System (ADS)

Lazarev, A. A.

2009-02-01

An approach is proposed for estimating absolute errors and finding approximate solutions to classical NP-hard scheduling problems of minimizing the maximum lateness for one or many machines and makespan is minimized. The concept of a metric (distance) between instances of the problem is introduced. The idea behind the approach is, given the problem instance, to construct another instance for which an optimal or approximate solution can be found at the minimum distance from the initial instance in the metric introduced. Instead of solving the original problem (instance), a set of approximating polynomially/pseudopolynomially solvable problems (instances) are considered, an instance at the minimum distance from the given one is chosen, and the resulting schedule is then applied to the original instance.
Working Notes from the 1992 AAAI Spring Symposium on Practical Approaches to Scheduling and Planning

NASA Technical Reports Server (NTRS)

Drummond, Mark; Fox, Mark; Tate, Austin; Zweben, Monte

1992-01-01

The symposium presented issues involved in the development of scheduling systems that can deal with resource and time limitations. To qualify, a system must be implemented and tested to some degree on non-trivial problems (ideally, on real-world problems). However, a system need not be fully deployed to qualify. Systems that schedule actions in terms of metric time constraints typically represent and reason about an external numeric clock or calendar and can be contrasted with those systems that represent time purely symbolically. The following topics are discussed: integrating planning and scheduling; integrating symbolic goals and numerical utilities; managing uncertainty; incremental rescheduling; managing limited computation time; anytime scheduling and planning algorithms, systems; dependency analysis and schedule reuse; management of schedule and plan execution; and incorporation of discrete event techniques.
Job Scheduling in a Heterogeneous Grid Environment

NASA Technical Reports Server (NTRS)

Shan, Hong-Zhang; Smith, Warren; Oliker, Leonid; Biswas, Rupak

2004-01-01

Computational grids have the potential for solving large-scale scientific problems using heterogeneous and geographically distributed resources. However, a number of major technical hurdles must be overcome before this potential can be realized. One problem that is critical to effective utilization of computational grids is the efficient scheduling of jobs. This work addresses this problem by describing and evaluating a grid scheduling architecture and three job migration algorithms. The architecture is scalable and does not assume control of local site resources. The job migration policies use the availability and performance of computer systems, the network bandwidth available between systems, and the volume of input and output data associated with each job. An extensive performance comparison is presented using real workloads from leading computational centers. The results, based on several key metrics, demonstrate that the performance of our distributed migration algorithms is significantly greater than that of a local scheduling framework and comparable to a non-scalable global scheduling approach.
Uncertainty management by relaxation of conflicting constraints in production process scheduling

NASA Technical Reports Server (NTRS)

Dorn, Juergen; Slany, Wolfgang; Stary, Christian

1992-01-01

Mathematical-analytical methods as used in Operations Research approaches are often insufficient for scheduling problems. This is due to three reasons: the combinatorial complexity of the search space, conflicting objectives for production optimization, and the uncertainty in the production process. Knowledge-based techniques, especially approximate reasoning and constraint relaxation, are promising ways to overcome these problems. A case study from an industrial CIM environment, namely high-grade steel production, is presented to demonstrate how knowledge-based scheduling with the desired capabilities could work. By using fuzzy set theory, the applied knowledge representation technique covers the uncertainty inherent in the problem domain. Based on this knowledge representation, a classification of jobs according to their importance is defined which is then used for the straightforward generation of a schedule. A control strategy which comprises organizational, spatial, temporal, and chemical constraints is introduced. The strategy supports the dynamic relaxation of conflicting constraints in order to improve tentative schedules.
Simulated annealing with probabilistic analysis for solving traveling salesman problems

NASA Astrophysics Data System (ADS)

Hong, Pei-Yee; Lim, Yai-Fung; Ramli, Razamin; Khalid, Ruzelan

2013-09-01

Simulated Annealing (SA) is a widely used meta-heuristic that was inspired from the annealing process of recrystallization of metals. Therefore, the efficiency of SA is highly affected by the annealing schedule. As a result, in this paper, we presented an empirical work to provide a comparable annealing schedule to solve symmetric traveling salesman problems (TSP). Randomized complete block design is also used in this study. The results show that different parameters do affect the efficiency of SA and thus, we propose the best found annealing schedule based on the Post Hoc test. SA was tested on seven selected benchmarked problems of symmetric TSP with the proposed annealing schedule. The performance of SA was evaluated empirically alongside with benchmark solutions and simple analysis to validate the quality of solutions. Computational results show that the proposed annealing schedule provides a good quality of solution.
Guidance and Control Software,

DTIC Science & Technology

1980-05-01

commitments of function, cost, and schedule . The phrase "software engineering" was intended to contrast with the phrase "computer science" the latter aims...the software problems of cost, delivery schedule , and quality were gradually being recognized at the highest management levels. Thus, in a project... schedule dates. Although the analysis of software problems indicated that the entire software development process (figure 1) needed new methods, only
High performance techniques for space mission scheduling

NASA Technical Reports Server (NTRS)

Smith, Stephen F.

1994-01-01

In this paper, we summarize current research at Carnegie Mellon University aimed at development of high performance techniques and tools for space mission scheduling. Similar to prior research in opportunistic scheduling, our approach assumes the use of dynamic analysis of problem constraints as a basis for heuristic focusing of problem solving search. This methodology, however, is grounded in representational assumptions more akin to those adopted in recent temporal planning research, and in a problem solving framework which similarly emphasizes constraint posting in an explicitly maintained solution constraint network. These more general representational assumptions are necessitated by the predominance of state-dependent constraints in space mission planning domains, and the consequent need to integrate resource allocation and plan synthesis processes. First, we review the space mission problems we have considered to date and indicate the results obtained in these application domains. Next, we summarize recent work in constraint posting scheduling procedures, which offer the promise of better future solutions to this class of problems.
A Novel Strategy Using Factor Graphs and the Sum-Product Algorithm for Satellite Broadcast Scheduling Problems

NASA Astrophysics Data System (ADS)

Chen, Jung-Chieh

This paper presents a low complexity algorithmic framework for finding a broadcasting schedule in a low-altitude satellite system, i. e., the satellite broadcast scheduling (SBS) problem, based on the recent modeling and computational methodology of factor graphs. Inspired by the huge success of the low density parity check (LDPC) codes in the field of error control coding, in this paper, we transform the SBS problem into an LDPC-like problem through a factor graph instead of using the conventional neural network approaches to solve the SBS problem. Based on a factor graph framework, the soft-information, describing the probability that each satellite will broadcast information to a terminal at a specific time slot, is exchanged among the local processing in the proposed framework via the sum-product algorithm to iteratively optimize the satellite broadcasting schedule. Numerical results show that the proposed approach not only can obtain optimal solution but also enjoys the low complexity suitable for integral-circuit implementation.
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.
The role of artificial intelligence techniques in scheduling systems

NASA Technical Reports Server (NTRS)

Geoffroy, Amy L.; Britt, Daniel L.; Gohring, John R.

1990-01-01

Artificial Intelligence (AI) techniques provide good solutions for many of the problems which are characteristic of scheduling applications. However, scheduling is a large, complex heterogeneous problem. Different applications will require different solutions. Any individual application will require the use of a variety of techniques, including both AI and conventional software methods. The operational context of the scheduling system will also play a large role in design considerations. The key is to identify those places where a specific AI technique is in fact the preferable solution, and to integrate that technique into the overall architecture.
A new distributed systems scheduling algorithm: a swarm intelligence approach

NASA Astrophysics Data System (ADS)

Haghi Kashani, Mostafa; Sarvizadeh, Raheleh; Jameii, Mahdi

2011-12-01

The scheduling problem in distributed systems is known as an NP-complete problem, and methods based on heuristic or metaheuristic search have been proposed to obtain optimal and suboptimal solutions. The task scheduling is a key factor for distributed systems to gain better performance. In this paper, an efficient method based on memetic algorithm is developed to solve the problem of distributed systems scheduling. With regard to load balancing efficiently, Artificial Bee Colony (ABC) has been applied as local search in the proposed memetic algorithm. The proposed method has been compared to existing memetic-Based approach in which Learning Automata method has been used as local search. The results demonstrated that the proposed method outperform the above mentioned method in terms of communication cost.
Solution and reasoning reuse in space planning and scheduling applications

NASA Technical Reports Server (NTRS)

Verfaillie, Gerard; Schiex, Thomas

1994-01-01

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

PubMed

Oddi, A; Cesta, A

2000-10-01

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

PubMed

Xie, Zhiqiang; Shao, Xia; Xin, Yu

2016-01-01

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

PubMed Central

Xie, Zhiqiang; Shao, Xia; Xin, Yu

2016-01-01

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

PubMed

Wu, Zuobao; Weng, Michael X

2005-04-01

Flexible job-shop scheduling problems are an important extension of the classical job-shop scheduling problems and present additional complexity. Such problems are mainly due to the existence of a considerable amount of overlapping capacities with modern machines. Classical scheduling methods are generally incapable of addressing such capacity overlapping. We propose a multiagent scheduling method with job earliness and tardiness objectives in a flexible job-shop environment. The earliness and tardiness objectives are consistent with the just-in-time production philosophy which has attracted significant attention in both industry and academic community. A new job-routing and sequencing mechanism is proposed. In this mechanism, two kinds of jobs are defined to distinguish jobs with one operation left from jobs with more than one operation left. Different criteria are proposed to route these two kinds of jobs. Job sequencing enables to hold a job that may be completed too early. Two heuristic algorithms for job sequencing are developed to deal with these two kinds of jobs. The computational experiments show that the proposed multiagent scheduling method significantly outperforms the existing scheduling methods in the literature. In addition, the proposed method is quite fast. In fact, the simulation time to find a complete schedule with over 2000 jobs on ten machines is less than 1.5 min.
Cactus: The Centres of a Triangle

ERIC Educational Resources Information Center

Hyde, Hartley

2009-01-01

This is the first of two articles which describe how to use "JavaSketchPad" to explore the centres of a triangle. This introductory exercise is suggested in the GSP "Workshop Guide". Students can use "JavaSketchPad Interactive Geometry" (JSP) at home at no cost. They are likely to impress their parents with their enthusiasm for geometry and all…
The phosphatase JKAP/DUSP22 inhibits t-cell receptor signalling and autoimmunity by inactivating Lck

USDA-ARS?s Scientific Manuscript database

JNK pathway-associated phosphatase (JKAP, also known as DUSP22 or JSP-1) is a JNK activator. The in vivo role of JKAP in immune regulation remains unclear. Here we report that JKAP directly inactivates Lck by dephosphorylating tyrosine-394 residue during T-cell receptor (TCR) signalling. JKAP-knocko...

(Investigations in guage theories, topological solitons and string theories)

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

Chang, L.N.; Tze, C.H.

1989-01-01

This report discusses the following topics: Phases and conservation laws in parametrized systems; Time reversal symmetry in 2 + 1 dimemsional systems; Chiral symmetry breaking in QCD at high temperatures; Solitons at Tev energies; Self-Duality, conformal symmetries and hypercomplex analyticity; Hopf phase entanglements, exotic membranes and division algebras; and Non-perturbative methods. 58 refs. (JSP)
75 FR 38097 - Agency Information Collection Activities; Proposed Collection; Comment Request

Federal Register 2010, 2011, 2012, 2013, 2014

2010-07-01

....jsp ), you may also file an electronic comment through that website. The Commission will consider all comments that regulations.gov forwards to it. You may also visit the FTC website at ( http://www.ftc.gov... will be available to the public on the FTC Website, to the extent practicable, at ( http://www.ftc.gov...
An Optimizing Space Data-Communications Scheduling Method and Algorithm with Interference Mitigation, Generalized for a Broad Class of Optimization Problems

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.
Discrete particle swarm optimization to solve multi-objective limited-wait hybrid flow shop scheduling problem

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
Exact and Metaheuristic Approaches for a Bi-Objective School Bus Scheduling Problem

PubMed Central

Chen, Xiaopan; Kong, Yunfeng; Dang, Lanxue; Hou, Yane; Ye, Xinyue

2015-01-01

As a class of hard combinatorial optimization problems, the school bus routing problem has received considerable attention in the last decades. For a multi-school system, given the bus trips for each school, the school bus scheduling problem aims at optimizing bus schedules to serve all the trips within the school time windows. In this paper, we propose two approaches for solving the bi-objective school bus scheduling problem: an exact method of mixed integer programming (MIP) and a metaheuristic method which combines simulated annealing with local search. We develop MIP formulations for homogenous and heterogeneous fleet problems respectively and solve the models by MIP solver CPLEX. The bus type-based formulation for heterogeneous fleet problem reduces the model complexity in terms of the number of decision variables and constraints. The metaheuristic method is a two-stage framework for minimizing the number of buses to be used as well as the total travel distance of buses. We evaluate the proposed MIP and the metaheuristic method on two benchmark datasets, showing that on both instances, our metaheuristic method significantly outperforms the respective state-of-the-art methods. PMID:26176764
A Genetic Algorithm Tool (splicer) for Complex Scheduling Problems and the Space Station Freedom Resupply Problem

NASA Technical Reports Server (NTRS)

Wang, Lui; Valenzuela-Rendon, Manuel

1993-01-01

The Space Station Freedom will require the supply of items in a regular fashion. A schedule for the delivery of these items is not easy to design due to the large span of time involved and the possibility of cancellations and changes in shuttle flights. This paper presents the basic concepts of a genetic algorithm model, and also presents the results of an effort to apply genetic algorithms to the design of propellant resupply schedules. As part of this effort, a simple simulator and an encoding by which a genetic algorithm can find near optimal schedules have been developed. Additionally, this paper proposes ways in which robust schedules, i.e., schedules that can tolerate small changes, can be found using genetic algorithms.
Learning Search Control Knowledge for Deep Space Network Scheduling

NASA Technical Reports Server (NTRS)

Gratch, Jonathan; Chien, Steve; DeJong, Gerald

1993-01-01

While the general class of most scheduling problems is NP-hard in worst-case complexity, in practice, for specific distributions of problems and constraints, domain-specific solutions have been shown to perform in much better than exponential time.
Vehicle and driver scheduling for public transit.

DOT National Transportation Integrated Search

2009-08-01

The problem of driver scheduling involves the construction of a legal set of shifts, including allowance : of overtime, which cover the blocks in a particular vehicle schedule. A shift is the work scheduled to be performed by : a driver in one day, w...
An Efficient Downlink Scheduling Strategy Using Normal Graphs for Multiuser MIMO Wireless Systems

NASA Astrophysics Data System (ADS)

Chen, Jung-Chieh; Wu, Cheng-Hsuan; Lee, Yao-Nan; Wen, Chao-Kai

Inspired by the success of the low-density parity-check (LDPC) codes in the field of error-control coding, in this paper we propose transforming the downlink multiuser multiple-input multiple-output scheduling problem into an LDPC-like problem using the normal graph. Based on the normal graph framework, soft information, which indicates the probability that each user will be scheduled to transmit packets at the access point through a specified angle-frequency sub-channel, is exchanged among the local processors to iteratively optimize the multiuser transmission schedule. Computer simulations show that the proposed algorithm can efficiently schedule simultaneous multiuser transmission which then increases the overall channel utilization and reduces the average packet delay.
Predit: A temporal predictive framework for scheduling systems

NASA Technical Reports Server (NTRS)

Paolucci, E.; Patriarca, E.; Sem, M.; Gini, G.

1992-01-01

Scheduling can be formalized as a Constraint Satisfaction Problem (CSP). Within this framework activities belonging to a plan are interconnected via temporal constraints that account for slack among them. Temporal representation must include methods for constraints propagation and provide a logic for symbolic and numerical deductions. In this paper we describe a support framework for opportunistic reasoning in constraint directed scheduling. In order to focus the attention of an incremental scheduler on critical problem aspects, some discrete temporal indexes are presented. They are also useful for the prediction of the degree of resources contention. The predictive method expressed through our indexes can be seen as a Knowledge Source for an opportunistic scheduler with a blackboard architecture.
Distributed Sleep Scheduling in Wireless Sensor Networks via Fractional Domatic Partitioning

NASA Astrophysics Data System (ADS)

Schumacher, André; Haanpää, Harri

We consider setting up sleep scheduling in sensor networks. We formulate the problem as an instance of the fractional domatic partition problem and obtain a distributed approximation algorithm by applying linear programming approximation techniques. Our algorithm is an application of the Garg-Könemann (GK) scheme that requires solving an instance of the minimum weight dominating set (MWDS) problem as a subroutine. Our two main contributions are a distributed implementation of the GK scheme for the sleep-scheduling problem and a novel asynchronous distributed algorithm for approximating MWDS based on a primal-dual analysis of Chvátal's set-cover algorithm. We evaluate our algorithm with ns2 simulations.
A Solution Method of Scheduling Problem with Worker Allocation by a Genetic Algorithm

NASA Astrophysics Data System (ADS)

Osawa, Akira; Ida, Kenichi

In a scheduling problem with worker allocation (SPWA) proposed by Iima et al, the worker's skill level to each machine is all the same. However, each worker has a different skill level for each machine in the real world. For that reason, we propose a new model of SPWA in which a worker has the different skill level to each machine. To solve the problem, we propose a new GA for SPWA consisting of the following new three procedures, shortening of idle time, modifying infeasible solution to feasible solution, and a new selection method for GA. The effectiveness of the proposed algorithm is clarified by numerical experiments using benchmark problems for job-shop scheduling.
Psychometric Properties of the Disability Assessment Schedule (DAS) for Behavior Problems: An Independent Investigation

ERIC Educational Resources Information Center

Tsakanikos, Elias; Underwood, Lisa; Sturmey, Peter; Bouras, Nick; McCarthy, Jane

2011-01-01

The present study employed the Disability Assessment Schedule (DAS) to assess problem behaviors in a large sample of adults with ID (N = 568) and evaluate the psychometric properties of this instrument. Although the DAS problem behaviors were found to be internally consistent (Cronbach's [alpha] = 0.87), item analysis revealed one weak item…
An Optimizing Space Data-Communications Scheduling Method and Algorithm with Interference Mitigation, Generalized for a Broad Class of Optimization Problems

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.
Scheduling: A guide for program managers

NASA Technical Reports Server (NTRS)

1994-01-01

The following topics are discussed concerning scheduling: (1) milestone scheduling; (2) network scheduling; (3) program evaluation and review technique; (4) critical path method; (5) developing a network; (6) converting an ugly duckling to a swan; (7) network scheduling problem; (8) (9) network scheduling when resources are limited; (10) multi-program considerations; (11) influence on program performance; (12) line-of-balance technique; (13) time management; (14) recapitulization; and (15) analysis.
Automated Scheduling Via Artificial Intelligence

NASA Technical Reports Server (NTRS)

Biefeld, Eric W.; Cooper, Lynne P.

1991-01-01

Artificial-intelligence software that automates scheduling developed in Operations Mission Planner (OMP) research project. Software used in both generation of new schedules and modification of existing schedules in view of changes in tasks and/or available resources. Approach based on iterative refinement. Although project focused upon scheduling of operations of scientific instruments and other equipment aboard spacecraft, also applicable to such terrestrial problems as scheduling production in factory.
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.
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.
Solving cyclical nurse scheduling problem using preemptive goal programming

NASA Astrophysics Data System (ADS)

Sundari, V. E.; Mardiyati, S.

2017-07-01

Nurse scheduling system in a hospital is being modeled as a preemptive goal programming problem that is solved by using LINGO software with the objective function to minimize deviation variable at each goal. The scheduling is done cyclically, so every nurse is treated fairly since they have the same work shift portion with the other nurses. By paying attention to the hospital's rules regarding nursing work shift cyclically, it can be obtained that numbers of nurse needed in every ward are 18 nurses and the numbers of scheduling periods are 18 periods where every period consists of 21 days.
Neighbourhood generation mechanism applied in simulated annealing to job shop scheduling problems

NASA Astrophysics Data System (ADS)

Cruz-Chávez, Marco Antonio

2015-11-01

This paper presents a neighbourhood generation mechanism for the job shop scheduling problems (JSSPs). In order to obtain a feasible neighbour with the generation mechanism, it is only necessary to generate a permutation of an adjacent pair of operations in a scheduling of the JSSP. If there is no slack time between the adjacent pair of operations that is permuted, then it is proven, through theory and experimentation, that the new neighbour (schedule) generated is feasible. It is demonstrated that the neighbourhood generation mechanism is very efficient and effective in a simulated annealing.

Block Scheduling in High Schools.

ERIC Educational Resources Information Center

Irmsher, Karen

1996-01-01

Block Scheduling has been considered a cure for a lengthy list of educational problems. This report reviews the literature on block schedules and describes some Oregon high schools that have integrated block scheduling. Major disadvantages included resistance to change and requirements that teachers change their teaching strategies. There is…
Deadlock-free genetic scheduling algorithm for automated manufacturing systems based on deadlock control policy.

PubMed

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.
Education and Social Equity: With a Special Focus on Scheduled Castes and Scheduled Tribes in Elementary Education. CREATE Pathways to Access. Research Monograph No. 19

ERIC Educational Resources Information Center

Sedwal, Mona; Kamat, Sangeeta

2008-01-01

The Scheduled Castes (SCs, also known as Dalits) and Scheduled Tribes (STs, also known as Adivasis) are among the most socially and educationally disadvantaged groups in India. This paper examines issues concerning school access and equity for Scheduled Caste and Scheduled Tribe communities and also highlights their unique problems, which may…
A modified genetic algorithm with fuzzy roulette wheel selection for job-shop scheduling problems

NASA Astrophysics Data System (ADS)

Thammano, Arit; Teekeng, Wannaporn

2015-05-01

The job-shop scheduling problem is one of the most difficult production planning problems. Since it is in the NP-hard class, a recent trend in solving the job-shop scheduling problem is shifting towards the use of heuristic and metaheuristic algorithms. This paper proposes a novel metaheuristic algorithm, which is a modification of the genetic algorithm. This proposed algorithm introduces two new concepts to the standard genetic algorithm: (1) fuzzy roulette wheel selection and (2) the mutation operation with tabu list. The proposed algorithm has been evaluated and compared with several state-of-the-art algorithms in the literature. The experimental results on 53 JSSPs show that the proposed algorithm is very effective in solving the combinatorial optimization problems. It outperforms all state-of-the-art algorithms on all benchmark problems in terms of the ability to achieve the optimal solution and the computational time.
Cost-efficient scheduling of FAST observations

NASA Astrophysics Data System (ADS)

Luo, Qi; Zhao, Laiping; Yu, Ce; Xiao, Jian; Sun, Jizhou; Zhu, Ming; Zhong, Yi

2018-03-01

A cost-efficient schedule for the Five-hundred-meter Aperture Spherical radio Telescope (FAST) requires to maximize the number of observable proposals and the overall scientific priority, and minimize the overall slew-cost generated by telescope shifting, while taking into account the constraints including the astronomical objects visibility, user-defined observable times, avoiding Radio Frequency Interference (RFI). In this contribution, first we solve the problem of maximizing the number of observable proposals and scientific priority by modeling it as a Minimum Cost Maximum Flow (MCMF) problem. The optimal schedule can be found by any MCMF solution algorithm. Then, for minimizing the slew-cost of the generated schedule, we devise a maximally-matchable edges detection-based method to reduce the problem size, and propose a backtracking algorithm to find the perfect matching with minimum slew-cost. Experiments on a real dataset from NASA/IPAC Extragalactic Database (NED) show that, the proposed scheduler can increase the usage of available times with high scientific priority and reduce the slew-cost significantly in a very short time.
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
Meta-RaPS Algorithm for the Aerial Refueling Scheduling Problem

NASA Technical Reports Server (NTRS)

Kaplan, Sezgin; Arin, Arif; Rabadi, Ghaith

2011-01-01

The Aerial Refueling Scheduling Problem (ARSP) can be defined as determining the refueling completion times for each fighter aircraft (job) on multiple tankers (machines). ARSP assumes that jobs have different release times and due dates, The total weighted tardiness is used to evaluate schedule's quality. Therefore, ARSP can be modeled as a parallel machine scheduling with release limes and due dates to minimize the total weighted tardiness. Since ARSP is NP-hard, it will be more appropriate to develop a pproimate or heuristic algorithm to obtain solutions in reasonable computation limes. In this paper, Meta-Raps-ATC algorithm is implemented to create high quality solutions. Meta-RaPS (Meta-heuristic for Randomized Priority Search) is a recent and promising meta heuristic that is applied by introducing randomness to a construction heuristic. The Apparent Tardiness Rule (ATC), which is a good rule for scheduling problems with tardiness objective, is used to construct initial solutions which are improved by an exchanging operation. Results are presented for generated instances.
EUROPA2: Plan Database Services for Planning and Scheduling Applications

NASA Technical Reports Server (NTRS)

Bedrax-Weiss, Tania; Frank, Jeremy; Jonsson, Ari; McGann, Conor

2004-01-01

NASA missions require solving a wide variety of planning and scheduling problems with temporal constraints; simple resources such as robotic arms, communications antennae and cameras; complex replenishable resources such as memory, power and fuel; and complex constraints on geometry, heat and lighting angles. Planners and schedulers that solve these problems are used in ground tools as well as onboard systems. The diversity of planning problems and applications of planners and schedulers precludes a one-size fits all solution. However, many of the underlying technologies are common across planning domains and applications. We describe CAPR, a formalism for planning that is general enough to cover a wide variety of planning and scheduling domains of interest to NASA. We then describe EUROPA(sub 2), a software framework implementing CAPR. EUROPA(sub 2) provides efficient, customizable Plan Database Services that enable the integration of CAPR into a wide variety of applications. We describe the design of EUROPA(sub 2) from the perspective of both modeling, customization and application integration to different classes of NASA missions.
75 FR 59718 - US Search, Inc. And US Search, LLC; Analysis of Proposed Consent Order to Aid Public Comment

Federal Register 2010, 2011, 2012, 2013, 2014

2010-09-28

... FEDERAL TRADE COMMISSION [File No. 102 3131] US Search, Inc. And US Search, LLC; Analysis of... written comments electronically or in paper form. Comments should refer to``US Search, Inc., File No. 101... this Notice appears at ( http://www.regulations.gov/search/index.jsp ), you may also file an electronic...
Implementation of the US EPA (United States Environmental Protection Agency) Regional Oxidant Modeling System

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

Novak, J.H.

1984-05-01

Model design, implementation and quality assurance procedures can have a significant impact on the effectiveness of long term utility of any modeling approach. The Regional Oxidant Modeling System (ROMS) is exceptionally complex because it treats all chemical and physical processes thought to affect ozone concentration on a regional scale. Thus, to effectively illustrate useful design and implementation techniques, this paper describes the general modeling framework which forms the basis of the ROMS. This framework is flexible enough to allow straightforward update or replacement of the chemical kinetics mechanism and/or any theoretical formulations of the physical processes. Use of the Jacksonmore » Structured Programming (JSP) method to implement this modeling framework has not only increased programmer productivity and quality of the resulting programs, but also has provided standardized program design, dynamic documentation, and easily maintainable and transportable code. A summary of the JSP method is presented to encourage modelers to pursue this technique in their own model development efforts. In addition, since data preparation is such an integral part of a successful modeling system, the ROMS processor network is described with emphasis on the internal quality control techniques.« less
A Web-based telemedicine system for diabetic retinopathy screening using digital fundus photography.

PubMed

Wei, Jack C; Valentino, Daniel J; Bell, Douglas S; Baker, Richard S

2006-02-01

The purpose was to design and implement a Web-based telemedicine system for diabetic retinopathy screening using digital fundus cameras and to make the software publicly available through Open Source release. The process of retinal imaging and case reviewing was modeled to optimize workflow and implement use of computer system. The Web-based system was built on Java Servlet and Java Server Pages (JSP) technologies. Apache Tomcat was chosen as the JSP engine, while MySQL was used as the main database and Laboratory of Neuro Imaging (LONI) Image Storage Architecture, from the LONI-UCLA, as the platform for image storage. For security, all data transmissions were carried over encrypted Internet connections such as Secure Socket Layer (SSL) and HyperText Transfer Protocol over SSL (HTTPS). User logins were required and access to patient data was logged for auditing. The system was deployed at Hubert H. Humphrey Comprehensive Health Center and Martin Luther King/Drew Medical Center of Los Angeles County Department of Health Services. Within 4 months, 1500 images of more than 650 patients were taken at Humphrey's Eye Clinic and successfully transferred to King/Drew's Department of Ophthalmology. This study demonstrates an effective architecture for remote diabetic retinopathy screening.
Hypertext-based design of a user interface for scheduling

NASA Technical Reports Server (NTRS)

Woerner, Irene W.; Biefeld, Eric

1993-01-01

Operations Mission Planner (OMP) is an ongoing research project at JPL that utilizes AI techniques to create an intelligent, automated planning and scheduling system. The information space reflects the complexity and diversity of tasks necessary in most real-world scheduling problems. Thus the problem of the user interface is to present as much information as possible at a given moment and allow the user to quickly navigate through the various types of displays. This paper describes a design which applies the hypertext model to solve these user interface problems. The general paradigm is to provide maps and search queries to allow the user to quickly find an interesting conflict or problem, and then allow the user to navigate through the displays in a hypertext fashion.
Scheduling the resident 80-hour work week: an operations research algorithm.

PubMed

Day, T Eugene; Napoli, Joseph T; Kuo, Paul C

2006-01-01

The resident 80-hour work week requires that programs now schedule duty hours. Typically, scheduling is performed in an empirical "trial-and-error" fashion. However, this is a classic "scheduling" problem from the field of operations research (OR). It is similar to scheduling issues that airlines must face with pilots and planes routing through various airports at various times. The authors hypothesized that an OR approach using iterative computer algorithms could provide a rational scheduling solution. Institution-specific constraints of the residency problem were formulated. A total of 56 residents are rotating through 4 hospitals. Additional constraints were dictated by the Residency Review Committee (RRC) rules or the specific surgical service. For example, at Hospital 1, during the weekday hours between 6 am and 6 pm, there will be a PGY4 or PGY5 and a PGY2 or PGY3 on-duty to cover Service "A." A series of equations and logic statements was generated to satisfy all constraints and requirements. These were restated in the Optimization Programming Language used by the ILOG software suite for solving mixed integer programming problems. An integer programming solution was generated to this resource-constrained assignment problem. A total of 30,900 variables and 12,443 constraints were required. A total of man-hours of programming were used; computer run-time was 25.9 hours. A weekly schedule was generated for each resident that satisfied the RRC regulations while fulfilling all stated surgical service requirements. Each required between 64 and 80 weekly resident duty hours. The authors conclude that OR is a viable approach to schedule resident work hours. This technique is sufficiently robust to accommodate changes in resident numbers, service requirements, and service and hospital rotations.
Energy-efficient approach to minimizing the energy consumption in an extended job-shop scheduling problem

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.
Integrated production and distribution scheduling problems related to fixed delivery departure dates and weights of late orders.

PubMed

Li, Shanlin; Li, Maoqin

2015-01-01

We consider an integrated production and distribution scheduling problem faced by a typical make-to-order manufacturer which relies on a third-party logistics (3PL) provider for finished product delivery to customers. In the beginning of a planning horizon, the manufacturer has received a set of orders to be processed on a single production line. Completed orders are delivered to customers by a finite number of vehicles provided by the 3PL company which follows a fixed daily or weekly shipping schedule such that the vehicles have fixed departure dates which are not part of the decisions. The problem is to find a feasible schedule that minimizes one of the following objective functions when processing times and weights are oppositely ordered: (1) the total weight of late orders and (2) the number of vehicles used subject to the condition that the total weight of late orders is minimum. We show that both problems are solvable in polynomial time.
Scheduling Non-Preemptible Jobs to Minimize Peak Demand

DOE PAGES

Yaw, Sean; Mumey, Brendan

2017-10-28

Our paper examines an important problem in smart grid energy scheduling; peaks in power demand are proportionally more expensive to generate and provision for. The issue is exacerbated in local microgrids that do not benefit from the aggregate smoothing experienced by large grids. Demand-side scheduling can reduce these peaks by taking advantage of the fact that there is often flexibility in job start times. We then focus attention on the case where the jobs are non-preemptible, meaning once started, they run to completion. The associated optimization problem is called the peak demand minimization problem, and has been previously shown tomore » be NP-hard. These results include an optimal fixed-parameter tractable algorithm, a polynomial-time approximation algorithm, as well as an effective heuristic that can also be used in an online setting of the problem. Simulation results show that these methods can reduce peak demand by up to 50% versus on-demand scheduling for household power jobs.« less
Integrated Production and Distribution Scheduling Problems Related to Fixed Delivery Departure Dates and Weights of Late Orders

PubMed Central

Li, Shanlin; Li, Maoqin

2015-01-01

We consider an integrated production and distribution scheduling problem faced by a typical make-to-order manufacturer which relies on a third-party logistics (3PL) provider for finished product delivery to customers. In the beginning of a planning horizon, the manufacturer has received a set of orders to be processed on a single production line. Completed orders are delivered to customers by a finite number of vehicles provided by the 3PL company which follows a fixed daily or weekly shipping schedule such that the vehicles have fixed departure dates which are not part of the decisions. The problem is to find a feasible schedule that minimizes one of the following objective functions when processing times and weights are oppositely ordered: (1) the total weight of late orders and (2) the number of vehicles used subject to the condition that the total weight of late orders is minimum. We show that both problems are solvable in polynomial time. PMID:25785285
Scheduling Non-Preemptible Jobs to Minimize Peak Demand

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

Yaw, Sean; Mumey, Brendan

Our paper examines an important problem in smart grid energy scheduling; peaks in power demand are proportionally more expensive to generate and provision for. The issue is exacerbated in local microgrids that do not benefit from the aggregate smoothing experienced by large grids. Demand-side scheduling can reduce these peaks by taking advantage of the fact that there is often flexibility in job start times. We then focus attention on the case where the jobs are non-preemptible, meaning once started, they run to completion. The associated optimization problem is called the peak demand minimization problem, and has been previously shown tomore » be NP-hard. These results include an optimal fixed-parameter tractable algorithm, a polynomial-time approximation algorithm, as well as an effective heuristic that can also be used in an online setting of the problem. Simulation results show that these methods can reduce peak demand by up to 50% versus on-demand scheduling for household power jobs.« less
A generalized network flow model for the multi-mode resource-constrained project scheduling problem with discounted cash flows

NASA Astrophysics Data System (ADS)

Chen, Miawjane; Yan, Shangyao; Wang, Sin-Siang; Liu, Chiu-Lan

2015-02-01

An effective project schedule is essential for enterprises to increase their efficiency of project execution, to maximize profit, and to minimize wastage of resources. Heuristic algorithms have been developed to efficiently solve the complicated multi-mode resource-constrained project scheduling problem with discounted cash flows (MRCPSPDCF) that characterize real problems. However, the solutions obtained in past studies have been approximate and are difficult to evaluate in terms of optimality. In this study, a generalized network flow model, embedded in a time-precedence network, is proposed to formulate the MRCPSPDCF with the payment at activity completion times. Mathematically, the model is formulated as an integer network flow problem with side constraints, which can be efficiently solved for optimality, using existing mathematical programming software. To evaluate the model performance, numerical tests are performed. The test results indicate that the model could be a useful planning tool for project scheduling in the real world.
A novel hybrid genetic algorithm to solve the make-to-order sequence-dependent flow-shop scheduling problem

NASA Astrophysics Data System (ADS)

Mirabi, Mohammad; Fatemi Ghomi, S. M. T.; Jolai, F.

2014-04-01

Flow-shop scheduling problem (FSP) deals with the scheduling of a set of n jobs that visit a set of m machines in the same order. As the FSP is NP-hard, there is no efficient algorithm to reach the optimal solution of the problem. To minimize the holding, delay and setup costs of large permutation flow-shop scheduling problems with sequence-dependent setup times on each machine, this paper develops a novel hybrid genetic algorithm (HGA) with three genetic operators. Proposed HGA applies a modified approach to generate a pool of initial solutions, and also uses an improved heuristic called the iterated swap procedure to improve the initial solutions. We consider the make-to-order production approach that some sequences between jobs are assumed as tabu based on maximum allowable setup cost. In addition, the results are compared to some recently developed heuristics and computational experimental results show that the proposed HGA performs very competitively with respect to accuracy and efficiency of solution.

PRACTICAL: Planning and Resource Allocation in C2-Domains With Time Critical Algorithms (PRACTICAL: Planning en Allocatie in C2-Domeinen Met Tijdkritische Algoritmen)

DTIC Science & Technology

1993-02-01

the (re)planning framework, incorporating the demonstrators CALIGULA and ALLOCATOR for resource allocation and scheduling respectively. In the Command...demonstrator CALIGULA for the problem of allocating frequencies to a radio link network. The problems in the domain of scheduling are dealt with. which has...demonstrating the (re)planning framework, incorporating the demonstrators CALIGULA and ALLOCATOR for resource allocation and scheduling respectively
Intercell scheduling: A negotiation approach using multi-agent coalitions

NASA Astrophysics Data System (ADS)

Tian, Yunna; Li, Dongni; Zheng, Dan; Jia, Yunde

2016-10-01

Intercell scheduling problems arise as a result of intercell transfers in cellular manufacturing systems. Flexible intercell routes are considered in this article, and a coalition-based scheduling (CBS) approach using distributed multi-agent negotiation is developed. Taking advantage of the extended vision of the coalition agents, the global optimization is improved and the communication cost is reduced. The objective of the addressed problem is to minimize mean tardiness. Computational results show that, compared with the widely used combinatorial rules, CBS provides better performance not only in minimizing the objective, i.e. mean tardiness, but also in minimizing auxiliary measures such as maximum completion time, mean flow time and the ratio of tardy parts. Moreover, CBS is better than the existing intercell scheduling approach for the same problem with respect to the solution quality and computational costs.
Effective Iterated Greedy Algorithm for Flow-Shop Scheduling Problems with Time lags

NASA Astrophysics Data System (ADS)

ZHAO, Ning; YE, Song; LI, Kaidian; CHEN, Siyu

2017-05-01

Flow shop scheduling problem with time lags is a practical scheduling problem and attracts many studies. Permutation problem(PFSP with time lags) is concentrated but non-permutation problem(non-PFSP with time lags) seems to be neglected. With the aim to minimize the makespan and satisfy time lag constraints, efficient algorithms corresponding to PFSP and non-PFSP problems are proposed, which consist of iterated greedy algorithm for permutation(IGTLP) and iterated greedy algorithm for non-permutation (IGTLNP). The proposed algorithms are verified using well-known simple and complex instances of permutation and non-permutation problems with various time lag ranges. The permutation results indicate that the proposed IGTLP can reach near optimal solution within nearly 11% computational time of traditional GA approach. The non-permutation results indicate that the proposed IG can reach nearly same solution within less than 1% computational time compared with traditional GA approach. The proposed research combines PFSP and non-PFSP together with minimal and maximal time lag consideration, which provides an interesting viewpoint for industrial implementation.
Application of a hybrid generation/utility assessment heuristic to a class of scheduling problems

NASA Technical Reports Server (NTRS)

Heyward, Ann O.

1989-01-01

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

PubMed Central

Kadima, Hubert; Granado, Bertrand

2013-01-01

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

PubMed

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

2013-01-01

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

NASA Technical Reports Server (NTRS)

Yu, Chee-Fen; Wah, Benjamin W.

1988-01-01

Dominance relations commonly are used to prune unnecessary nodes in search graphs, but they are problem-dependent and cannot be derived by a general procedure. The authors identify machine learning of dominance relations and the applicable learning mechanisms. A study of learning dominance relations using learning by experimentation is described. This system has been able to learn dominance relations for the 0/1-knapsack problem, an inventory problem, the reliability-by-replication problem, the two-machine flow shop problem, a number of single-machine scheduling problems, and a two-machine scheduling problem. It is considered that the same methodology can be extended to learn dominance relations in general.
Scheduling IT Staff at a Bank: A Mathematical Programming Approach

PubMed Central

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.

PubMed

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.
Systemic Sustainability in RtI Using Intervention-Based Scheduling Methodologies

ERIC Educational Resources Information Center

Dallas, William P.

2017-01-01

This study evaluated a scheduling methodology referred to as intervention-based scheduling to address the problem of practice regarding the fidelity of implementing Response to Intervention (RtI) in an existing school schedule design. Employing panel data, this study used fixed-effects regressions and first differences ordinary least squares (OLS)…
Scheduling Independent Partitions in Integrated Modular Avionics Systems

PubMed Central

Du, Chenglie; Han, Pengcheng

2016-01-01

Recently the integrated modular avionics (IMA) architecture has been widely adopted by the avionics industry due to its strong partition mechanism. Although the IMA architecture can achieve effective cost reduction and reliability enhancement in the development of avionics systems, it results in a complex allocation and scheduling problem. All partitions in an IMA system should be integrated together according to a proper schedule such that their deadlines will be met even under the worst case situations. In order to help provide a proper scheduling table for all partitions in IMA systems, we study the schedulability of independent partitions on a multiprocessor platform in this paper. We firstly present an exact formulation to calculate the maximum scaling factor and determine whether all partitions are schedulable on a limited number of processors. Then with a Game Theory analogy, we design an approximation algorithm to solve the scheduling problem of partitions, by allowing each partition to optimize its own schedule according to the allocations of the others. Finally, simulation experiments are conducted to show the efficiency and reliability of the approach proposed in terms of time consumption and acceptance ratio. PMID:27942013
A future Outlook: Web based Simulation of Hydrodynamic models

NASA Astrophysics Data System (ADS)

Islam, A. S.; Piasecki, M.

2003-12-01

Despite recent advances to present simulation results as 3D graphs or animation contours, the modeling user community still faces some shortcomings when trying to move around and analyze data. Typical problems include the lack of common platforms with standard vocabulary to exchange simulation results from different numerical models, insufficient descriptions about data (metadata), lack of robust search and retrieval tools for data, and difficulties to reuse simulation domain knowledge. This research demonstrates how to create a shared simulation domain in the WWW and run a number of models through multi-user interfaces. Firstly, meta-datasets have been developed to describe hydrodynamic model data based on geographic metadata standard (ISO 19115) that has been extended to satisfy the need of the hydrodynamic modeling community. The Extended Markup Language (XML) is used to publish this metadata by the Resource Description Framework (RDF). Specific domain ontology for Web Based Simulation (WBS) has been developed to explicitly define vocabulary for the knowledge based simulation system. Subsequently, this knowledge based system is converted into an object model using Meta Object Family (MOF). The knowledge based system acts as a Meta model for the object oriented system, which aids in reusing the domain knowledge. Specific simulation software has been developed based on the object oriented model. Finally, all model data is stored in an object relational database. Database back-ends help store, retrieve and query information efficiently. This research uses open source software and technology such as Java Servlet and JSP, Apache web server, Tomcat Servlet Engine, PostgresSQL databases, Protégé ontology editor, RDQL and RQL for querying RDF in semantic level, Jena Java API for RDF. Also, we use international standards such as the ISO 19115 metadata standard, and specifications such as XML, RDF, OWL, XMI, and UML. The final web based simulation product is deployed as Web Archive (WAR) files which is platform and OS independent and can be used by Windows, UNIX, or Linux. Keywords: Apache, ISO 19115, Java Servlet, Jena, JSP, Metadata, MOF, Linux, Ontology, OWL, PostgresSQL, Protégé, RDF, RDQL, RQL, Tomcat, UML, UNIX, Windows, WAR, XML
Temporal planning for transportation planning and scheduling

NASA Technical Reports Server (NTRS)

Frederking, Robert E.; Muscettola, Nicola

1992-01-01

In this paper we describe preliminary work done in the CORTES project, applying the Heuristic Scheduling Testbed System (HSTS) to a transportation planning and scheduling domain. First, we describe in more detail the transportation problems that we are addressing. We then describe the fundamental characteristics of HSTS and we concentrate on the representation of multiple capacity resources. We continue with a more detailed description of the transportation planning problem that we have initially addressed in HSTS and of its solution. Finally we describe future directions for our research.
Graph Coloring Used to Model Traffic Lights.

ERIC Educational Resources Information Center

Williams, John

1992-01-01

Two scheduling problems, one involving setting up an examination schedule and the other describing traffic light problems, are modeled as colorings of graphs consisting of a set of vertices and edges. The chromatic number, the least number of colors necessary for coloring a graph, is employed in the solutions. (MDH)
Concurrent Reinforcement Schedules for Problem Behavior and Appropriate Behavior: Experimental Applications of the Matching Law

ERIC Educational Resources Information Center

Borrero, Carrie S. W.; Vollmer, Timothy R.; Borrero, John C.; Bourret, Jason C.; Sloman, Kimberly N.; Samaha, Andrew L.; Dallery, Jesse

2010-01-01

This study evaluated how children who exhibited functionally equivalent problem and appropriate behavior allocate responding to experimentally arranged reinforcer rates. Relative reinforcer rates were arranged on concurrent variable-interval schedules and effects on relative response rates were interpreted using the generalized matching equation.…
Shiftwork Scheduling for the 1990s.

ERIC Educational Resources Information Center

Coleman, Richard M.

1989-01-01

The author discusses the problems of scheduling shift work, touching on such topics as employee desires, health requirements, and business needs. He presents a method for developing shift schedules that addresses these three areas. Implementation hints are also provided. (CH)
Efficient bounding schemes for the two-center hybrid flow shop scheduling problem with removal times.

PubMed

Hidri, Lotfi; Gharbi, Anis; Louly, Mohamed Aly

2014-01-01

We focus on the two-center hybrid flow shop scheduling problem with identical parallel machines and removal times. The job removal time is the required duration to remove it from a machine after its processing. The objective is to minimize the maximum completion time (makespan). A heuristic and a lower bound are proposed for this NP-Hard problem. These procedures are based on the optimal solution of the parallel machine scheduling problem with release dates and delivery times. The heuristic is composed of two phases. The first one is a constructive phase in which an initial feasible solution is provided, while the second phase is an improvement one. Intensive computational experiments have been conducted to confirm the good performance of the proposed procedures.
Efficient Bounding Schemes for the Two-Center Hybrid Flow Shop Scheduling Problem with Removal Times

PubMed Central

2014-01-01

We focus on the two-center hybrid flow shop scheduling problem with identical parallel machines and removal times. The job removal time is the required duration to remove it from a machine after its processing. The objective is to minimize the maximum completion time (makespan). A heuristic and a lower bound are proposed for this NP-Hard problem. These procedures are based on the optimal solution of the parallel machine scheduling problem with release dates and delivery times. The heuristic is composed of two phases. The first one is a constructive phase in which an initial feasible solution is provided, while the second phase is an improvement one. Intensive computational experiments have been conducted to confirm the good performance of the proposed procedures. PMID:25610911
An Extended Deterministic Dendritic Cell Algorithm for Dynamic Job Shop Scheduling

NASA Astrophysics Data System (ADS)

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

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

PubMed

Madni, Syed Hamid Hussain; Abd Latiff, Muhammad Shafie; Abdullahi, Mohammed; Abdulhamid, Shafi'i Muhammad; Usman, Mohammed Joda

2017-01-01

Cloud computing infrastructure is suitable for meeting computational needs of large task sizes. Optimal scheduling of tasks in cloud computing environment has been proved to be an NP-complete problem, hence the need for the application of heuristic methods. Several heuristic algorithms have been developed and used in addressing this problem, but choosing the appropriate algorithm for solving task assignment problem of a particular nature is difficult since the methods are developed under different assumptions. Therefore, six rule based heuristic algorithms are implemented and used to schedule autonomous tasks in homogeneous and heterogeneous environments with the aim of comparing their performance in terms of cost, degree of imbalance, makespan and throughput. First Come First Serve (FCFS), Minimum Completion Time (MCT), Minimum Execution Time (MET), Max-min, Min-min and Sufferage are the heuristic algorithms considered for the performance comparison and analysis of task scheduling in cloud computing.

Performance comparison of heuristic algorithms for task scheduling in IaaS cloud computing environment

PubMed Central

Madni, Syed Hamid Hussain; Abd Latiff, Muhammad Shafie; Abdullahi, Mohammed; Usman, Mohammed Joda

2017-01-01

Cloud computing infrastructure is suitable for meeting computational needs of large task sizes. Optimal scheduling of tasks in cloud computing environment has been proved to be an NP-complete problem, hence the need for the application of heuristic methods. Several heuristic algorithms have been developed and used in addressing this problem, but choosing the appropriate algorithm for solving task assignment problem of a particular nature is difficult since the methods are developed under different assumptions. Therefore, six rule based heuristic algorithms are implemented and used to schedule autonomous tasks in homogeneous and heterogeneous environments with the aim of comparing their performance in terms of cost, degree of imbalance, makespan and throughput. First Come First Serve (FCFS), Minimum Completion Time (MCT), Minimum Execution Time (MET), Max-min, Min-min and Sufferage are the heuristic algorithms considered for the performance comparison and analysis of task scheduling in cloud computing. PMID:28467505
A Strategy for Autogeneration of Space Shuttle Ground Processing Simulation Models for Project Makespan Estimations

NASA Technical Reports Server (NTRS)

Madden, Michael G.; Wyrick, Roberta; O'Neill, Dale E.

2005-01-01

Space Shuttle Processing is a complicated and highly variable project. The planning and scheduling problem, categorized as a Resource Constrained - Stochastic Project Scheduling Problem (RC-SPSP), has a great deal of variability in the Orbiter Processing Facility (OPF) process flow from one flight to the next. Simulation Modeling is a useful tool in estimation of the makespan of the overall process. However, simulation requires a model to be developed, which itself is a labor and time consuming effort. With such a dynamic process, often the model would potentially be out of synchronization with the actual process, limiting the applicability of the simulation answers in solving the actual estimation problem. Integration of TEAMS model enabling software with our existing schedule program software is the basis of our solution. This paper explains the approach used to develop an auto-generated simulation model from planning and schedule efforts and available data.
Optimisation of assembly scheduling in VCIM systems using genetic algorithm

NASA Astrophysics Data System (ADS)

Dao, Son Duy; Abhary, Kazem; Marian, Romeo

2017-09-01

Assembly plays an important role in any production system as it constitutes a significant portion of the lead time and cost of a product. Virtual computer-integrated manufacturing (VCIM) system is a modern production system being conceptually developed to extend the application of traditional computer-integrated manufacturing (CIM) system to global level. Assembly scheduling in VCIM systems is quite different from one in traditional production systems because of the difference in the working principles of the two systems. In this article, the assembly scheduling problem in VCIM systems is modeled and then an integrated approach based on genetic algorithm (GA) is proposed to search for a global optimised solution to the problem. Because of dynamic nature of the scheduling problem, a novel GA with unique chromosome representation and modified genetic operations is developed herein. Robustness of the proposed approach is verified by a numerical example.
Some single-machine scheduling problems with learning effects and two competing agents.

PubMed

Li, Hongjie; Li, Zeyuan; Yin, Yunqiang

2014-01-01

This study considers a scheduling environment in which there are two agents and a set of jobs, each of which belongs to one of the two agents and its actual processing time is defined as a decreasing linear function of its starting time. Each of the two agents competes to process its respective jobs on a single machine and has its own scheduling objective to optimize. The objective is to assign the jobs so that the resulting schedule performs well with respect to the objectives of both agents. The objective functions addressed in this study include the maximum cost, the total weighted completion time, and the discounted total weighted completion time. We investigate three problems arising from different combinations of the objectives of the two agents. The computational complexity of the problems is discussed and solution algorithms where possible are presented.
Single machine total completion time minimization scheduling with a time-dependent learning effect and deteriorating jobs

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.
77 FR 27443 - Quick Path Information Disclosure Statement (QPIDS) Pilot Program

Federal Register 2010, 2011, 2012, 2013, 2014

2012-05-10

... associated with this pilot program must be filed via the USPTO's Electronic Filing System-Web (EFS-Web), and... forth in 37 CFR 1.97(e), with the IDS fee set forth in 37 CFR 1.17(p); (3) a Web-based ePetition to... at http://www.uspto.gov/about/offices/cfo/finance/Dep_Account_Rules_and_Info.jsp . 3. Web-Based e...
Electricity Usage Scheduling in Smart Building Environments Using Smart Devices

PubMed Central

Lee, Eunji; Bahn, Hyokyung

2013-01-01

With the recent advances in smart grid technologies as well as the increasing dissemination of smart meters, the electricity usage of every moment can be detected in modern smart building environments. Thus, the utility company adopts different price of electricity at each time slot considering the peak time. This paper presents a new electricity usage scheduling algorithm for smart buildings that adopts real-time pricing of electricity. The proposed algorithm detects the change of electricity prices by making use of a smart device and changes the power mode of each electric device dynamically. Specifically, we formulate the electricity usage scheduling problem as a real-time task scheduling problem and show that it is a complex search problem that has an exponential time complexity. An efficient heuristic based on genetic algorithms is performed on a smart device to cut down the huge searching space and find a reasonable schedule within a feasible time budget. Experimental results with various building conditions show that the proposed algorithm reduces the electricity charge of a smart building by 25.6% on average and up to 33.4%. PMID:24453860
A DAG Scheduling Scheme on Heterogeneous Computing Systems Using Tuple-Based Chemical Reaction Optimization

PubMed Central

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
A DAG scheduling scheme on heterogeneous computing systems using tuple-based chemical reaction optimization.

PubMed

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.
Efficient Computation of Separation-Compliant Speed Advisories for Air Traffic Arriving in Terminal Airspace

NASA Technical Reports Server (NTRS)

Sadovsky, Alexander V.; Davis, Damek; Isaacson, Douglas R.

2012-01-01

A class of problems in air traffic management asks for a scheduling algorithm that supplies the air traffic services authority not only with a schedule of arrivals and departures, but also with speed advisories. Since advisories must be finite, a scheduling algorithm must ultimately produce a finite data set, hence must either start with a purely discrete model or involve a discretization of a continuous one. The former choice, often preferred for intuitive clarity, naturally leads to mixed-integer programs, hindering proofs of correctness and computational cost bounds (crucial for real-time operations). In this paper, a hybrid control system is used to model air traffic scheduling, capturing both the discrete and continuous aspects. This framework is applied to a class of problems, called the Fully Routed Nominal Problem. We prove a number of geometric results on feasible schedules and use these results to formulate an algorithm that attempts to compute a collective speed advisory, effectively finite, and has computational cost polynomial in the number of aircraft. This work is a first step toward optimization and models refined with more realistic detail.
Electricity usage scheduling in smart building environments using smart devices.

PubMed

Lee, Eunji; Bahn, Hyokyung

2013-01-01

With the recent advances in smart grid technologies as well as the increasing dissemination of smart meters, the electricity usage of every moment can be detected in modern smart building environments. Thus, the utility company adopts different price of electricity at each time slot considering the peak time. This paper presents a new electricity usage scheduling algorithm for smart buildings that adopts real-time pricing of electricity. The proposed algorithm detects the change of electricity prices by making use of a smart device and changes the power mode of each electric device dynamically. Specifically, we formulate the electricity usage scheduling problem as a real-time task scheduling problem and show that it is a complex search problem that has an exponential time complexity. An efficient heuristic based on genetic algorithms is performed on a smart device to cut down the huge searching space and find a reasonable schedule within a feasible time budget. Experimental results with various building conditions show that the proposed algorithm reduces the electricity charge of a smart building by 25.6% on average and up to 33.4%.
Task and Participant Scheduling of Trading Platforms in Vehicular Participatory Sensing Networks

PubMed Central

Shi, Heyuan; Song, Xiaoyu; Gu, Ming; Sun, Jiaguang

2016-01-01

The vehicular participatory sensing network (VPSN) is now becoming more and more prevalent, and additionally has shown its great potential in various applications. A general VPSN consists of many tasks from task, publishers, trading platforms and a crowd of participants. Some literature treats publishers and the trading platform as a whole, which is impractical since they are two independent economic entities with respective purposes. For a trading platform in markets, its purpose is to maximize the profit by selecting tasks and recruiting participants who satisfy the requirements of accepted tasks, rather than to improve the quality of each task. This scheduling problem for a trading platform consists of two parts: which tasks should be selected and which participants to be recruited? In this paper, we investigate the scheduling problem in vehicular participatory sensing with the predictable mobility of each vehicle. A genetic-based trading scheduling algorithm (GTSA) is proposed to solve the scheduling problem. Experiments with a realistic dataset of taxi trajectories demonstrate that GTSA algorithm is efficient for trading platforms to gain considerable profit in VPSN. PMID:27916807
Task and Participant Scheduling of Trading Platforms in Vehicular Participatory Sensing Networks.

PubMed

Shi, Heyuan; Song, Xiaoyu; Gu, Ming; Sun, Jiaguang

2016-11-28

The vehicular participatory sensing network (VPSN) is now becoming more and more prevalent, and additionally has shown its great potential in various applications. A general VPSN consists of many tasks from task, publishers, trading platforms and a crowd of participants. Some literature treats publishers and the trading platform as a whole, which is impractical since they are two independent economic entities with respective purposes. For a trading platform in markets, its purpose is to maximize the profit by selecting tasks and recruiting participants who satisfy the requirements of accepted tasks, rather than to improve the quality of each task. This scheduling problem for a trading platform consists of two parts: which tasks should be selected and which participants to be recruited? In this paper, we investigate the scheduling problem in vehicular participatory sensing with the predictable mobility of each vehicle. A genetic-based trading scheduling algorithm (GTSA) is proposed to solve the scheduling problem. Experiments with a realistic dataset of taxi trajectories demonstrate that GTSA algorithm is efficient for trading platforms to gain considerable profit in VPSN.
Scheduling real-time, periodic jobs using imprecise results

NASA Technical Reports Server (NTRS)

Liu, Jane W. S.; Lin, Kwei-Jay; Natarajan, Swaminathan

1987-01-01

A process is called a monotone process if the accuracy of its intermediate results is non-decreasing as more time is spent to obtain the result. The result produced by a monotone process upon its normal termination is the desired result; the error in this result is zero. External events such as timeouts or crashes may cause the process to terminate prematurely. If the intermediate result produced by the process upon its premature termination is saved and made available, the application may still find the result unusable and, hence, acceptable; such a result is said to be an imprecise one. The error in an imprecise result is nonzero. The problem of scheduling periodic jobs to meet deadlines on a system that provides the necessary programming language primitives and run-time support for processes to return imprecise results is discussed. This problem differs from the traditional scheduling problems since the scheduler may choose to terminate a task before it is completed, causing it to produce an acceptable but imprecise result. Consequently, the amounts of processor time assigned to tasks in a valid schedule can be less than the amounts of time required to complete the tasks. A meaningful formulation of this problem taking into account the quality of the overall result is discussed. Three algorithms for scheduling jobs for which the effects of errors in results produced in different periods are not cumulative are described, and their relative merits are evaluated.
A note on resource allocation scheduling with group technology and learning effects on a single machine

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.
Algorithms for Scheduling and Network Problems

DTIC Science & Technology

1991-09-01

time. We already know, by Lemma 2.2.1, that WOPT = O(log( mpU )), so if we could solve this integer program optimally we would be done. However, the...Folydirat, 15:177-191, 1982. [6] I.S. Belov and Ya. N. Stolin. An algorithm in a single path operations scheduling problem. In Mathematical Economics and
Electromagnetic interference-aware transmission scheduling and power control for dynamic wireless access in hospital environments.

PubMed

Phunchongharn, Phond; Hossain, Ekram; Camorlinga, Sergio

2011-11-01

We study the multiple access problem for e-Health applications (referred to as secondary users) coexisting with medical devices (referred to as primary or protected users) in a hospital environment. In particular, we focus on transmission scheduling and power control of secondary users in multiple spatial reuse time-division multiple access (STDMA) networks. The objective is to maximize the spectrum utilization of secondary users and minimize their power consumption subject to the electromagnetic interference (EMI) constraints for active and passive medical devices and minimum throughput guarantee for secondary users. The multiple access problem is formulated as a dual objective optimization problem which is shown to be NP-complete. We propose a joint scheduling and power control algorithm based on a greedy approach to solve the problem with much lower computational complexity. To this end, an enhanced greedy algorithm is proposed to improve the performance of the greedy algorithm by finding the optimal sequence of secondary users for scheduling. Using extensive simulations, the tradeoff in performance in terms of spectrum utilization, energy consumption, and computational complexity is evaluated for both the algorithms.
Space power system scheduling using an expert system

NASA Technical Reports Server (NTRS)

Bahrami, K. A.; Biefeld, E.; Costello, L.; Klein, J. W.

1986-01-01

A most pressing problem in space exploration is timely spacecraft power system sequence generation, which requires the scheduling of a set of loads given a set of resource constraints. This is particularly important after an anomaly or failure. This paper discusses the power scheduling problem and how the software program, Plan-It, can be used as a consultant for scheduling power system activities. Modeling of power activities, human interface, and two of the many strategies used by Plan-It are discussed. Preliminary results showing the development of a conflict-free sequence from an initial sequence with conflicts is presented. It shows that a 4-day schedule can be generated in a matter of a few minutes, which provides sufficient time in many cases to aid the crew in the replanning of loads and generation use following a failure or anomaly.
Nonstandard maternal work schedules during infancy: Implications for children's early behavior problems

PubMed Central

Daniel, Stephanie S.; Grzywacz, Joseph G.; Leerkes, Esther; Tucker, Jenna; Han, Wen-Jui

2009-01-01

This paper examines the associations between maternal nonstandard work schedules during infancy and children's early behavior problems, and the extent to which infant temperament may moderate these associations. Hypothesized associations were tested using data from the National Institute of Child Health and Human Development (NICHD) Study of Early Child Care (Phase I). Analyses focused on mothers who returned to work by the time the child was 6 months of age, and who worked an average of at least 35 h per week from 6 through 36 months. At 24 and 36 months, children whose mothers worked a nonstandard schedule had higher internalizing and externalizing behaviors. Modest, albeit inconsistent, evidence suggests that temperamentally reactive children may be more vulnerable to maternal work schedules. Maternal depressive symptoms partially mediated associations between nonstandard maternal work schedules and child behavior outcomes. PMID:19233479
Aiding USAF/UPT (Undergraduate Pilot Training) Aircrew Scheduling Using Network Flow Models.

DTIC Science & Technology

1986-06-01

51 3.4 Heuristic Modifications ............ 55 CHAPTER 4 STUDENT SCHEDULING PROBLEM (LEVEL 2) 4.0 Introduction 4.01 Constraints ............. 60 4.02...Covering" Complete Enumeration . . .. . 71 4.14 Heuristics . ............. 72 4.2 Heuristic Method for the Level 2 Problem 4.21 Step I ............... 73...4.22 Step 2 ............... 74 4.23 Advantages to the Heuristic Method. .... .. 78 4.24 Problems with the Heuristic Method. . ... 79 :,., . * CHAPTER5

Observations on SOFIA Observation Scheduling: Search and Inference in the Face of Discrete and Continuous Constraints

NASA Technical Reports Server (NTRS)

Frank, Jeremy; Gross, Michael; Kuerklu, Elif

2003-01-01

We did cool stuff to reduce the number of IVPs and BVPs needed to schedule SOFIA by restricting the problem. The restriction costs us little in terms of the value of the flight plans we can build. The restriction allowed us to reformulate part of the search problem as a zero-finding problem. The result is a simplified planning model and significant savings in computation time.
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.
A methodological proposal for the development of an HPC-based antenna array scheduler

NASA Astrophysics Data System (ADS)

Bonvallet, Roberto; Hoffstadt, Arturo; Herrera, Diego; López, Daniela; Gregorio, Rodrigo; Almuna, Manuel; Hiriart, Rafael; Solar, Mauricio

2010-07-01

As new astronomy projects choose interferometry to improve angular resolution and to minimize costs, preparing and optimizing schedules for an antenna array becomes an increasingly critical task. This problem shares similarities with the job-shop problem, which is known to be a NP-hard problem, making a complete approach infeasible. In the case of ALMA, 18000 projects per season are expected, and the best schedule must be found in the order of minutes. The problem imposes severe difficulties: the large domain of observation projects to be taken into account; a complex objective function, composed of several abstract, environmental, and hardware constraints; the number of restrictions imposed and the dynamic nature of the problem, as weather is an ever-changing variable. A solution can benefit from the use of High-Performance Computing for the final implementation to be deployed, but also for the development process. Our research group proposes the use of both metaheuristic search and statistical learning algorithms, in order to create schedules in a reasonable time. How these techniques will be applied is yet to be determined as part of the ongoing research. Several algorithms need to be implemented, tested and evaluated by the team. This work presents the methodology proposed to lead the development of the scheduler. The basic functionality is encapsulated into software components implemented on parallel architectures. These components expose a domain-level interface to the researchers, enabling then to develop early prototypes for evaluating and comparing their proposed techniques.
Design of an Aircrew Scheduling Decision Aid for the 6916th Electronic Security Squadron.

DTIC Science & Technology

1987-06-01

Security Classification) Design of an Aircrew Scheduling Decision Aid for the 6916th Electronic Security Squadron 12. PERSONAL AUTHOR(S) Thomas J. Kopf...Because of the great number of possible scheduling alternatives, it is difficult to find an optimal solution to-the scheduling problem. Additionally...changes to the original schedule make it even more difficult to find an optimal solution. The emergence of capable microcompu- ters, decision support
Scheduling of hybrid types of machines with two-machine flowshop as the first type and a single machine as the second type

NASA Astrophysics Data System (ADS)

Hsiao, Ming-Chih; Su, Ling-Huey

2018-02-01

This research addresses the problem of scheduling hybrid machine types, in which one type is a two-machine flowshop and another type is a single machine. A job is either processed on the two-machine flowshop or on the single machine. The objective is to determine a production schedule for all jobs so as to minimize the makespan. The problem is NP-hard since the two parallel machines problem was proved to be NP-hard. Simulated annealing algorithms are developed to solve the problem optimally. A mixed integer programming (MIP) is developed and used to evaluate the performance for two SAs. Computational experiments demonstrate the efficiency of the simulated annealing algorithms, the quality of the simulated annealing algorithms will also be reported.
Single-machine group scheduling problems with deteriorating and learning effect

NASA Astrophysics Data System (ADS)

Xingong, Zhang; Yong, Wang; Shikun, Bai

2016-07-01

The concepts of deteriorating jobs and learning effects have been individually studied in many scheduling problems. However, most studies considering the deteriorating and learning effects ignore the fact that production efficiency can be increased by grouping various parts and products with similar designs and/or production processes. This phenomenon is known as 'group technology' in the literature. In this paper, a new group scheduling model with deteriorating and learning effects is proposed, where learning effect depends not only on job position, but also on the position of the corresponding job group; deteriorating effect depends on its starting time of the job. This paper shows that the makespan and the total completion time problems remain polynomial optimal solvable under the proposed model. In addition, a polynomial optimal solution is also presented to minimise the maximum lateness problem under certain agreeable restriction.
Scheduling of an aircraft fleet

NASA Technical Reports Server (NTRS)

Paltrinieri, Massimo; Momigliano, Alberto; Torquati, Franco

1992-01-01

Scheduling is the task of assigning resources to operations. When the resources are mobile vehicles, they describe routes through the served stations. To emphasize such aspect, this problem is usually referred to as the routing problem. In particular, if vehicles are aircraft and stations are airports, the problem is known as aircraft routing. This paper describes the solution to such a problem developed in OMAR (Operative Management of Aircraft Routing), a system implemented by Bull HN for Alitalia. In our approach, aircraft routing is viewed as a Constraint Satisfaction Problem. The solving strategy combines network consistency and tree search techniques.
An Optimization of Manufacturing Systems using a Feedback Control Scheduling Model

NASA Astrophysics Data System (ADS)

Ikome, John M.; Kanakana, Grace M.

2018-03-01

In complex production system that involves multiple process, unplanned disruption often turn to make the entire production system vulnerable to a number of problems which leads to customer’s dissatisfaction. However, this problem has been an ongoing problem that requires a research and methods to streamline the entire process or develop a model that will address it, in contrast to this, we have developed a feedback scheduling model that can minimize some of this problem and after a number of experiment, it shows that some of this problems can be eliminated if the correct remedial actions are implemented on time.
Heuristic methods for the single machine scheduling problem with different ready times and a common due date

NASA Astrophysics Data System (ADS)

Birgin, Ernesto G.; Ronconi, Débora P.

2012-10-01

The single machine scheduling problem with a common due date and non-identical ready times for the jobs is examined in this work. Performance is measured by the minimization of the weighted sum of earliness and tardiness penalties of the jobs. Since this problem is NP-hard, the application of constructive heuristics that exploit specific characteristics of the problem to improve their performance is investigated. The proposed approaches are examined through a computational comparative study on a set of 280 benchmark test problems with up to 1000 jobs.
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.
Scheduling Projects with Multiskill Learning Effect

PubMed Central

2014-01-01

We investigate the project scheduling problem with multiskill learning effect. A new model is proposed to deal with the problem, where both autonomous and induced learning are considered. In order to obtain the optimal solution, a genetic algorithm with specific encoding and decoding schemes is introduced. A numerical example is used to illustrate the proposed model. The computational results show that the learning effect cannot be neglected in project scheduling. By means of determining the level of induced learning, the project manager can balance the project makespan with total cost. PMID:24683355
Scheduling projects with multiskill learning effect.

PubMed

Zha, Hong; Zhang, Lianying

2014-01-01

We investigate the project scheduling problem with multiskill learning effect. A new model is proposed to deal with the problem, where both autonomous and induced learning are considered. In order to obtain the optimal solution, a genetic algorithm with specific encoding and decoding schemes is introduced. A numerical example is used to illustrate the proposed model. The computational results show that the learning effect cannot be neglected in project scheduling. By means of determining the level of induced learning, the project manager can balance the project makespan with total cost.
Human-Machine Collaborative Optimization via Apprenticeship Scheduling

DTIC Science & Technology

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

PubMed Central

Cui, Laizhong; Lu, Nan; Chen, Fu

2014-01-01

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

NASA Astrophysics Data System (ADS)

Koshimura, Miyuki; Nabeshima, Hidetomo; Fujita, Hiroshi; Hasegawa, Ryuzo

This paper tries to solve open Job-Shop Scheduling Problems (JSSP) by translating them into Boolean Satisfiability Testing Problems (SAT). The encoding method is essentially the same as the one proposed by Crawford and Baker. The open problems are ABZ8, ABZ9, YN1, YN2, YN3, and YN4. We proved that the best known upper bounds 678 of ABZ9 and 884 of YN1 are indeed optimal. We also improved the upper bound of YN2 and lower bounds of ABZ8, YN2, YN3 and YN4.
ABOLISHING AND ESTABLISHING OPERATION ANALYSES OF SOCIAL ATTENTION AS POSITIVE REINFORCEMENT FOR PROBLEM BEHAVIOR

PubMed Central

McGinnis, Molly A; Houchins-Juárez, Nealetta; McDaniel, Jill L; Kennedy, Craig H

2010-01-01

Three participants whose problem behavior was maintained by contingent attention were exposed to 45-min presessions in which attention was withheld, provided on a fixed-time (FT) 15-s schedule, or provided on an FT 120-s schedule. Following each presession, participants were then tested in a 15-min session similar to the social attention condition of an analogue functional analysis. The results showed establishing operation conditions increased problem behavior during tests and that abolishing operation conditions decreased problem behavior during tests. PMID:20808502
Abolishing and establishing operation analyses of social attention as positive reinforcement for problem behavior.

PubMed

McGinnis, Molly A; Houchins-Juárez, Nealetta; McDaniel, Jill L; Kennedy, Craig H

2010-03-01

Three participants whose problem behavior was maintained by contingent attention were exposed to 45-min presessions in which attention was withheld, provided on a fixed-time (FT) 15-s schedule, or provided on an FT 120-s schedule. Following each presession, participants were then tested in a 15-min session similar to the social attention condition of an analogue functional analysis. The results showed establishing operation conditions increased problem behavior during tests and that abolishing operation conditions decreased problem behavior during tests.
Research on Scheduling Algorithm for Multi-satellite and Point Target Task on Swinging Mode

NASA Astrophysics Data System (ADS)

Wang, M.; Dai, G.; Peng, L.; Song, Z.; Chen, G.

2012-12-01

Nowadays, using satellite in space to observe ground is an important and major method to obtain ground information. With the development of the scientific technology in the field of space, many fields such as military and economic and other areas have more and more requirement of space technology because of the benefits of the satellite's widespread, timeliness and unlimited of area and country. And at the same time, because of the wide use of all kinds of satellites, sensors, repeater satellites and ground receiving stations, ground control system are now facing great challenge. Therefore, how to make the best value of satellite resources so as to make full use of them becomes an important problem of ground control system. Satellite scheduling is to distribute the resource to all tasks without conflict to obtain the scheduling result so as to complete as many tasks as possible to meet user's requirement under considering the condition of the requirement of satellites, sensors and ground receiving stations. Considering the size of the task, we can divide tasks into point task and area task. This paper only considers point targets. In this paper, a description of satellite scheduling problem and a chief introduction of the theory of satellite scheduling are firstly made. We also analyze the restriction of resource and task in scheduling satellites. The input and output flow of scheduling process are also chiefly described in the paper. On the basis of these analyses, we put forward a scheduling model named as multi-variable optimization model for multi-satellite and point target task on swinging mode. In the multi-variable optimization model, the scheduling problem is transformed the parametric optimization problem. The parameter we wish to optimize is the swinging angle of every time-window. In the view of the efficiency and accuracy, some important problems relating the satellite scheduling such as the angle relation between satellites and ground targets, positive and negative swinging angle and the computation of time window are analyzed and discussed. And many strategies to improve the efficiency of this model are also put forward. In order to solve the model, we bring forward the conception of activity sequence map. By using the activity sequence map, the activity choice and the start time of the activity can be divided. We also bring forward three neighborhood operators to search the result space. The front movement remaining time and the back movement remaining time are used to analyze the feasibility to generate solution from neighborhood operators. Lastly, the algorithm to solve the problem and model is put forward based genetic algorithm. Population initialization, crossover operator, mutation operator, individual evaluation, collision decrease operator, select operator and collision elimination operator is designed in the paper. Finally, the scheduling result and the simulation for a practical example on 5 satellites and 100 point targets with swinging mode is given, and the scheduling performances are also analyzed while the swinging angle in 0, 5, 10, 15, 25. It can be shown by the result that the model and the algorithm are more effective than those ones without swinging mode.
Multiple Hypothesis Tracking (MHT) for Space Surveillance: Results and Simulation Studies

DTIC Science & Technology

2013-09-01

processor. 1 . INTRODUCTION The Joint Space Operations Center (JSpOC) currently tracks more than 22,000 satellites and space debris orbiting the Earth... 1 , 2]. With the anticipated installation of more accurate sensors and the increased probability of future collisions between space objects, the...average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed
Kinetics of sulfate and hydrogen uptake by the thermophilic sulfate-reducing bacteria thermodesulfobacterium sp. Strain JSP and thermodesulfovibrio sp. Strain R1Ha3

PubMed

Sonne-Hansen; Westermann; Ahring

1999-03-01

Half-saturation constants (Km), maximum uptake rates (Vmax), and threshold concentrations for sulfate and hydrogen were determined for two thermophilic sulfate-reducing bacteria (SRB) in an incubation system without headspace. Km values determined for the thermophilic SRB were similar to the constants described for mesophilic SRB isolated from environments with low sulfate concentrations.

Kinetics of Sulfate and Hydrogen Uptake by the Thermophilic Sulfate-Reducing Bacteria Thermodesulfobacterium sp. Strain JSP and Thermodesulfovibrio sp. Strain R1Ha3

PubMed Central

Sonne-Hansen, Jacob; Westermann, Peter; Ahring, Birgitte K.

1999-01-01

Half-saturation constants (Km), maximum uptake rates (Vmax), and threshold concentrations for sulfate and hydrogen were determined for two thermophilic sulfate-reducing bacteria (SRB) in an incubation system without headspace. Km values determined for the thermophilic SRB were similar to the constants described for mesophilic SRB isolated from environments with low sulfate concentrations. PMID:10049897
75 FR 70921 - Simon Property Group, Inc.; Analysis of Proposed Agreement Containing Consent Orders To Aid...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-11-19

... site, at http:[sol][sol]www.ftc.gov[sol]os[sol]publiccomments.shtm. Because comments will be made.../simonproperty . If this Notice appears at http:[sol][sol]www.regulations.gov[sol]search[sol]index.jsp, you may... regulations.gov forwards to it. You may also visit the FTC Web site at http:[sol][sol]www.ftc.gov[sol] to read...
Deterministic Intracellular Modeling

DTIC Science & Technology

2003-03-01

eukaryotes encompass all plants, animal, fungi and protists [6:71]. Structures in this class are more defined. For example, cells in this class possess a...affect cells. 5.3 Recommendations Further research into the construction and evaluation of intracellular models would benefit Air Force toxicology studies...manual220/indexE.html. 16. MathWorks, “The Benefits of MATLAB.” Internet, 2003. http://www.mathworks.com/products/matlab/description1.jsp. 17. Mendes
Improving Interagency Coordination and Unity of Effort: An Organizational Analysis of the Contemporary Provincial Reconstruction Team

DTIC Science & Technology

2010-05-20

capability. A DOS PRT member, Linda Specht , recalls that: The contemporary PRT hierarchical organization achieves such integration and accountability...Linda Specht , 4 February 2008" (Fort Leavenworth, Kansas: Combat Studies Institute, 2008), 9, http://comarms.ipac.dynixasp.com/ipac20/ipac. jsp...term=interview+with+linda+ specht &index=.GW#focus (accessed February 10, 2010). Figure 2 represents the cross-functional contemporary PRT organization
Back from the Future: The Impact of Change on Airpower in the Decades Ahead

DTIC Science & Technology

2009-01-01

generic/story_generic.jsp?channel= awst &id=news/aw021108p2.xml&headline=Fate%20of%20F -22,%20C-17%20Lines%20Uncertain%20in%20Fiscal%202009; Pierre Sprey...second lot of low-rate initial production aircraft was announced on 22 May 2008 as $2.2 billion for 12 aircraft, and Maj Gen Charles R . Davis, USAF, the
China’s ASAT Test: Motivations and Implications

DTIC Science & Technology

2007-01-01

h i l l i P c . S a u n D e r S and c h a r l e S D . l u t e S Dr. Phillip C. saunders and Colonel Charles D. Lutes, UsaF, are senior Research...at <www.aviationweek.com/aw/generic/story_generic. jsp?channel= awst &id=news/aw012207p2.xml>. 11 Chris Buckley, “China confirms satellite test, says
Combat Service Support MOD II Design (CSS MOD II). Volume 2. Appendixes

DTIC Science & Technology

1986-10-01

through contractual aoreement with Michael Jackson , Ltd. London. The spelling, syntax, and word usage adopted throughout the document have been made...to conform to army standards. The design teas members wish to thank the followin, individuals for their assistances Mr. John Cameron, Michael Jackson , Ltd...JSP) methodology is a product of Michael Jackson Systems, Ltd., London, England. In 1984, Dr. Wilbur Payne, Director, TRADOC Operations Research
Search and Determine Integrated Environment (SADIE)

NASA Astrophysics Data System (ADS)

Sabol, C.; Schumacher, P.; Segerman, A.; Coffey, S.; Hoskins, A.

2012-09-01

A new and integrated high performance computing software applications package called the Search and Determine Integrated Environment (SADIE) is being jointly developed and refined by the Air Force and Naval Research Laboratories (AFRL and NRL) to automatically resolve uncorrelated tracks (UCTs) and build a more complete space object catalog for improved Space Situational Awareness (SSA). The motivation for SADIE is to respond to very challenging needs identified and guidance received from Air Force Space Command (AFSPC) and other senior leaders to develop this technology to support the evolving Joint Space Operations Center (JSpOC) and Alternate Space Control Center (ASC2)-Dahlgren. The JSpOC and JMS SSA mission requirements and threads flow down from the United States Strategic Command (USSTRATCOM). The SADIE suite includes modification and integration of legacy applications and software components that include Search And Determine (SAD), Satellite Identification (SID), and Parallel Catalog (Parcat), as well as other utilities and scripts to enable end-to-end catalog building and maintenance in a parallel processing environment. SADIE is being developed to handle large catalog building challenges in all orbit regimes and includes the automatic processing of radar, fence, and optical data. Real data results are provided for the processing of Air Force Space Surveillance System fence observations and for the processing of Space Surveillance Telescope optical data.
Comparison of multiobjective evolutionary algorithms for operations scheduling under machine availability constraints.

PubMed

Frutos, M; Méndez, M; Tohmé, F; Broz, D

2013-01-01

Many of the problems that arise in production systems can be handled with multiobjective techniques. One of those problems is that of scheduling operations subject to constraints on the availability of machines and buffer capacity. In this paper we analyze different Evolutionary multiobjective Algorithms (MOEAs) for this kind of problems. We consider an experimental framework in which we schedule production operations for four real world Job-Shop contexts using three algorithms, NSGAII, SPEA2, and IBEA. Using two performance indexes, Hypervolume and R2, we found that SPEA2 and IBEA are the most efficient for the tasks at hand. On the other hand IBEA seems to be a better choice of tool since it yields more solutions in the approximate Pareto frontier.
QoS Differential Scheduling in Cognitive-Radio-Based Smart Grid Networks: An Adaptive Dynamic Programming Approach.

PubMed

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

2016-02-01

As the next-generation power grid, smart grid will be integrated with a variety of novel communication technologies to support the explosive data traffic and the diverse requirements of quality of service (QoS). Cognitive radio (CR), which has the favorable ability to improve the spectrum utilization, provides an efficient and reliable solution for smart grid communications networks. In this paper, we study the QoS differential scheduling problem in the CR-based smart grid communications networks. The scheduler is responsible for managing the spectrum resources and arranging the data transmissions of smart grid users (SGUs). To guarantee the differential QoS, the SGUs are assigned to have different priorities according to their roles and their current situations in the smart grid. Based on the QoS-aware priority policy, the scheduler adjusts the channels allocation to minimize the transmission delay of SGUs. The entire transmission scheduling problem is formulated as a semi-Markov decision process and solved by the methodology of adaptive dynamic programming. A heuristic dynamic programming (HDP) architecture is established for the scheduling problem. By the online network training, the HDP can learn from the activities of primary users and SGUs, and adjust the scheduling decision to achieve the purpose of transmission delay minimization. Simulation results illustrate that the proposed priority policy ensures the low transmission delay of high priority SGUs. In addition, the emergency data transmission delay is also reduced to a significantly low level, guaranteeing the differential QoS in smart grid.
A collaborative scheduling model for the supply-hub with multiple suppliers and multiple manufacturers.

PubMed

Li, Guo; Lv, Fei; Guan, Xu

2014-01-01

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

PubMed Central

Lv, Fei; Guan, Xu

2014-01-01

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

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.
Imaging Tasks Scheduling for High-Altitude Airship in Emergency Condition Based on Energy-Aware Strategy

PubMed Central

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
Minimizing conflicts: A heuristic repair method for constraint-satisfaction and scheduling problems

NASA Technical Reports Server (NTRS)

Minton, Steve; Johnston, Mark; Philips, Andrew; Laird, Phil

1992-01-01

This paper describes a simple heuristic approach to solving large-scale constraint satisfaction and scheduling problems. In this approach one starts with an inconsistent assignment for a set of variables and searches through the space of possible repairs. The search can be guided by a value-ordering heuristic, the min-conflicts heuristic, that attempts to minimize the number of constraint violations after each step. The heuristic can be used with a variety of different search strategies. We demonstrate empirically that on the n-queens problem, a technique based on this approach performs orders of magnitude better than traditional backtracking techniques. We also describe a scheduling application where the approach has been used successfully. A theoretical analysis is presented both to explain why this method works well on certain types of problems and to predict when it is likely to be most effective.
A random-key encoded harmony search approach for energy-efficient production scheduling with shared resources

NASA Astrophysics Data System (ADS)

Garcia-Santiago, C. A.; Del Ser, J.; Upton, C.; Quilligan, F.; Gil-Lopez, S.; Salcedo-Sanz, S.

2015-11-01

When seeking near-optimal solutions for complex scheduling problems, meta-heuristics demonstrate good performance with affordable computational effort. This has resulted in a gravitation towards these approaches when researching industrial use-cases such as energy-efficient production planning. However, much of the previous research makes assumptions about softer constraints that affect planning strategies and about how human planners interact with the algorithm in a live production environment. This article describes a job-shop problem that focuses on minimizing energy consumption across a production facility of shared resources. The application scenario is based on real facilities made available by the Irish Center for Manufacturing Research. The formulated problem is tackled via harmony search heuristics with random keys encoding. Simulation results are compared to a genetic algorithm, a simulated annealing approach and a first-come-first-served scheduling. The superior performance obtained by the proposed scheduler paves the way towards its practical implementation over industrial production chains.
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.
Naval Postgraduate School Scheduling Support System (NPS4)

DTIC Science & Technology

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
A scheduling algorithm for Spacelab telescope observations

NASA Technical Reports Server (NTRS)

Grone, B.

1982-01-01

An algorithm is developed for sequencing and scheduling of observations of stellar targets by equipment on Spacelab. The method is a general one. The scheduling problem is defined and examined. The method developed for its solution is documented. Suggestions for further development and implementation of this method are made.

Binary Trees and Parallel Scheduling Algorithms.

DTIC Science & Technology

1980-09-01

been pro- cessed for p. time units. If a job does not complete by its due time, it is tardy. In a nonpreemptive schedule, job i is scheduled to process...the preemptive schedule obtained by the algorithm of section 2.1.2 also minimizes 5Ti, this problem is easily solved in parallel. When lci is to e...August 1978, pp. 657-661. 14. Horn, W. A., "Some simple scheduling algorithms," Naval Res. Logist . Qur., Vol. 21, pp. 177-185, 1974. i5. Hforowitz, E
New scheduling rules for a dynamic flexible flow line problem with sequence-dependent setup times

NASA Astrophysics Data System (ADS)

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

2017-09-01

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

NASA Astrophysics Data System (ADS)

Afshar Nadjafi, Behrouz; Shadrokh, Shahram

This research considers a project scheduling problem with the object of minimizing weighted earliness-tardiness penalty costs, taking into account a deadline for the project and precedence relations among the activities. An exact recursive method has been proposed for solving the basic form of this problem. We present a new depth-first branch and bound algorithm for extended form of the problem, which time value of money is taken into account by discounting the cash flows. The algorithm is extended with two bounding rules in order to reduce the size of the branch and bound tree. Finally, some test problems are solved and computational results are reported.
Gallbladder cancer epidemiology, pathogenesis and molecular genetics: Recent update

PubMed Central

Sharma, Aarti; Sharma, Kiran Lata; Gupta, Annapurna; Yadav, Alka; Kumar, Ashok

2017-01-01

Gallbladder cancer is a malignancy of biliary tract which is infrequent in developed countries but common in some specific geographical regions of developing countries. Late diagnosis and deprived prognosis are major problems for treatment of gallbladder carcinoma. The dramatic associations of this orphan cancer with various genetic and environmental factors are responsible for its poorly defined pathogenesis. An understanding to the relationship between epidemiology, molecular genetics and pathogenesis of gallbladder cancer can add new insights to its undetermined pathophysiology. Present review article provides a recent update regarding epidemiology, pathogenesis, and molecular genetics of gallbladder cancer. We systematically reviewed published literature on gallbladder cancer from online search engine PubMed (http://www.ncbi.nlm.nih.gov/pubmed). Various keywords used for retrieval of articles were Gallbladder, cancer Epidemiology, molecular genetics and bullion operators like AND, OR, NOT. Cross references were manually searched from various online search engines (http://www.ncbi.nlm.nih.gov/pubmed,https://scholar.google.co.in/, http://www.medline.com/home.jsp). Most of the articles published from 1982 to 2015 in peer reviewed journals have been included in this review. PMID:28652652
Gallbladder cancer epidemiology, pathogenesis and molecular genetics: Recent update.

PubMed

Sharma, Aarti; Sharma, Kiran Lata; Gupta, Annapurna; Yadav, Alka; Kumar, Ashok

2017-06-14

Gallbladder cancer is a malignancy of biliary tract which is infrequent in developed countries but common in some specific geographical regions of developing countries. Late diagnosis and deprived prognosis are major problems for treatment of gallbladder carcinoma. The dramatic associations of this orphan cancer with various genetic and environmental factors are responsible for its poorly defined pathogenesis. An understanding to the relationship between epidemiology, molecular genetics and pathogenesis of gallbladder cancer can add new insights to its undetermined pathophysiology. Present review article provides a recent update regarding epidemiology, pathogenesis, and molecular genetics of gallbladder cancer. We systematically reviewed published literature on gallbladder cancer from online search engine PubMed (http://www.ncbi.nlm.nih.gov/pubmed). Various keywords used for retrieval of articles were Gallbladder, cancer Epidemiology, molecular genetics and bullion operators like AND, OR, NOT. Cross references were manually searched from various online search engines (http://www.ncbi.nlm.nih.gov/pubmed,https://scholar.google.co.in/, http://www.medline.com/home.jsp). Most of the articles published from 1982 to 2015 in peer reviewed journals have been included in this review.
Better approximation guarantees for job-shop scheduling

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

Goldberg, L.A.; Paterson, M.; Srinivasan, A.

1997-06-01

Job-shop scheduling is a classical NP-hard problem. Shmoys, Stein & Wein presented the first polynomial-time approximation algorithm for this problem that has a good (polylogarithmic) approximation guarantee. We improve the approximation guarantee of their work, and present further improvements for some important NP-hard special cases of this problem (e.g., in the preemptive case where machines can suspend work on operations and later resume). We also present NC algorithms with improved approximation guarantees for some NP-hard special cases.
Continual planning and scheduling for managing patient tests in hospital laboratories.

PubMed

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

2000-10-01

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

NASA Astrophysics Data System (ADS)

Widl, Magdalena; Musliu, Nysret

In this paper we consider solving a complex real life break scheduling problem. This problem of high practical relevance arises in many working areas, e.g. in air traffic control and other fields where supervision personnel is working. The objective is to assign breaks to employees such that various constraints reflecting legal demands or ergonomic criteria are satisfied and staffing requirement violations are minimised.
Abolishing and Establishing Operation Analyses of Social Attention as Positive Reinforcement for Problem Behavior

ERIC Educational Resources Information Center

McGinnis, Molly A.; Houchins-Juarez, Nealetta; McDaniel, Jill L.; Kennedy, Craig H.

2010-01-01

Three participants whose problem behavior was maintained by contingent attention were exposed to 45-min presessions in which attention was withheld, provided on a fixed-time (FT) 15-s schedule, or provided on an FT 120-s schedule. Following each presession, participants were then tested in a 15-min session similar to the social attention condition…
Longest jobs first algorithm in solving job shop scheduling using adaptive genetic algorithm (GA)

NASA Astrophysics Data System (ADS)

Alizadeh Sahzabi, Vahid; Karimi, Iman; Alizadeh Sahzabi, Navid; Mamaani Barnaghi, Peiman

2012-01-01

In this paper, genetic algorithm was used to solve job shop scheduling problems. One example discussed in JSSP (Job Shop Scheduling Problem) and I described how we can solve such these problems by genetic algorithm. The goal in JSSP is to gain the shortest process time. Furthermore I proposed a method to obtain best performance on performing all jobs in shortest time. The method mainly, is according to Genetic algorithm (GA) and crossing over between parents always follows the rule which the longest process is at the first in the job queue. In the other word chromosomes is suggested to sorts based on the longest processes to shortest i.e. "longest job first" says firstly look which machine contains most processing time during its performing all its jobs and that is the bottleneck. Secondly, start sort those jobs which are belonging to that specific machine descending. Based on the achieved results," longest jobs first" is the optimized status in job shop scheduling problems. In our results the accuracy would grow up to 94.7% for total processing time and the method improved 4% the accuracy of performing all jobs in the presented example.
Evaluation of fixed momentary dro schedules under signaled and unsignaled arrangements.

PubMed

Hammond, Jennifer L; Iwata, Brian A; Fritz, Jennifer N; Dempsey, Carrie M

2011-01-01

Fixed momentary schedules of differential reinforcement of other behavior (FM DRO) generally have been ineffective as treatment for problem behavior. Because most early research on FM DRO included presentation of a signal at the end of the DRO interval, it is unclear whether the limited effects of FM DRO were due to (a) the momentary response requirement of the schedule per se or (b) discrimination of the contingency made more salient by the signal. To separate these two potential influences, we compared the effects of signaled versus unsignaled FM DRO with 4 individuals with developmental disabilities whose problem behavior was maintained by social-positive reinforcement. During signaled FM DRO, the experimenter presented a visual stimulus 3 s prior to the end of the DRO interval and delivered reinforcement contingent on the absence of problem behavior at the second the interval elapsed. Unsignaled DRO was identical except that interval termination was not signaled. Results indicated that signaled FM DRO was effective in decreasing 2 subjects' problem behavior, whereas an unsignaled schedule was required for the remaining 2 subjects. These results suggest that the response requirement per se of FM DRO may not be problematic if it is not easily discriminated.
Surgery scheduling optimization considering real life constraints and comprehensive operation cost of operating room.

PubMed

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.
Decision support system for the operating room rescheduling problem.

PubMed

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

2012-12-01

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

NASA Astrophysics Data System (ADS)

Oktaviandri, Muchamad; Hassan, Adnan; Mohd Shaharoun, Awaluddin

2016-02-01

Majority of existing scheduling techniques are based on static demand and deterministic processing time, while most job shop scheduling problem are concerned with dynamic demand and stochastic processing time. As a consequence, the solutions obtained from the traditional scheduling technique are ineffective wherever changes occur to the system. Therefore, this research intends to develop a decision support tool (DST) based on promising artificial intelligent that is able to accommodate the dynamics that regularly occur in job shop scheduling problem. The DST was designed through three phases, i.e. (i) the look-up table generation, (ii) inverse model development and (iii) integration of DST components. This paper reports the generation of look-up tables for various scenarios as a part in development of the DST. A discrete event simulation model was used to compare the performance among SPT, EDD, FCFS, S/OPN and Slack rules; the best performances measures (mean flow time, mean tardiness and mean lateness) and the job order requirement (inter-arrival time, due dates tightness and setup time ratio) which were compiled into look-up tables. The well-known 6/6/J/Cmax Problem from Muth and Thompson (1963) was used as a case study. In the future, the performance measure of various scheduling scenarios and the job order requirement will be mapped using ANN inverse model.
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.
Asymptotic analysis of SPTA-based algorithms for no-wait flow shop scheduling problem with release dates.

PubMed

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.
A parallel-machine scheduling problem with two competing agents

NASA Astrophysics Data System (ADS)

Lee, Wen-Chiung; Chung, Yu-Hsiang; Wang, Jen-Ya

2017-06-01

Scheduling with two competing agents has become popular in recent years. Most of the research has focused on single-machine problems. This article considers a parallel-machine problem, the objective of which is to minimize the total completion time of jobs from the first agent given that the maximum tardiness of jobs from the second agent cannot exceed an upper bound. The NP-hardness of this problem is also examined. A genetic algorithm equipped with local search is proposed to search for the near-optimal solution. Computational experiments are conducted to evaluate the proposed genetic algorithm.
Asymptotic Analysis of SPTA-Based Algorithms for No-Wait Flow Shop Scheduling Problem with Release Dates

PubMed Central

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
AN EVALUATION OF ANTECEDENT EXERCISE ON BEHAVIOR MAINTAINED BY AUTOMATIC REINFORCEMENT USING A THREE-COMPONENT MULTIPLE SCHEDULE

PubMed Central

Morrison, Heather; Roscoe, Eileen M; Atwell, Amy

2011-01-01

We evaluated antecedent exercise for treating the automatically reinforced problem behavior of 4 individuals with autism. We conducted preference assessments to identify leisure and exercise items that were associated with high levels of engagement and low levels of problem behavior. Next, we conducted three 3-component multiple-schedule sequences: an antecedent-exercise test sequence, a noncontingent leisure-item control sequence, and a social-interaction control sequence. Within each sequence, we used a 3-component multiple schedule to evaluate preintervention, intervention, and postintervention effects. Problem behavior decreased during the postintervention component relative to the preintervention component for 3 of the 4 participants during the exercise-item assessment; however, the effects could not be attributed solely to exercise for 1 of these participants. PMID:21941383
Comparison of Multiobjective Evolutionary Algorithms for Operations Scheduling under Machine Availability Constraints

PubMed Central

Frutos, M.; Méndez, M.; Tohmé, F.; Broz, D.

2013-01-01

Many of the problems that arise in production systems can be handled with multiobjective techniques. One of those problems is that of scheduling operations subject to constraints on the availability of machines and buffer capacity. In this paper we analyze different Evolutionary multiobjective Algorithms (MOEAs) for this kind of problems. We consider an experimental framework in which we schedule production operations for four real world Job-Shop contexts using three algorithms, NSGAII, SPEA2, and IBEA. Using two performance indexes, Hypervolume and R2, we found that SPEA2 and IBEA are the most efficient for the tasks at hand. On the other hand IBEA seems to be a better choice of tool since it yields more solutions in the approximate Pareto frontier. PMID:24489502

In Brief: National Medal of Science nomination deadline

NASA Astrophysics Data System (ADS)

Showstack, Randy

2010-03-01

The deadline for nominations for the 2010 U.S. National Medal of Science is 31 March 2010. The Medal of Science, which is presented annually by the president of the United States to distinguished scientists and engineers, is the nation's highest honor for American scientists and engineers. For more information, visit http://www.nsf.gov/od/nms/nominations.jsp or contact Mayra Montrose at the U.S. National Science Foundation, mmontros@nsf.gov.
ReSEARCH: A Requirements Search Engine: Progress Report 2

DTIC Science & Technology

2008-09-01

and provides a convenient user interface for the search process. Ideally, the web application would be based on Tomcat, a free Java Servlet and JSP...Implementation issues Lucene Java is an Open Source project, available under the Apache License, which provides an accessible API for the development of...from the Apache Lucene website (Lucene- java Wiki , 2008). A search application developed with Lucene consists of the same two major com- ponents
Characterization and Performance Comparison of Low-Voltage, High-Speed, Push-Pull and Traveling-Wave Silicon Mach-Zehnder Modulators

DTIC Science & Technology

2014-03-27

2Fieeexplore.ieee.org%2Fxpls%2Fabs all.jsp%3Farnumber%3D5875447 [7] D. Marris- Morini , L. Vivien, G. Rasigade, J.-M. Fedeli, E. Cassan, X. Le Roux, P. Crozat...3rd ed., B. Zobrist, Ed. Wiley, 2002. [26] M. Ziebell, D. Marris- Morini , G. Rasigade, P. Crozat, J.-M. Fedeli, E. Cassan, and L. Vivien, “Low-loss and
Network Monitoring for Web-Based Threats

DTIC Science & Technology

2011-02-01

string to access files or folders that were not intended (see Figure 4-1). http://example.com/getUserProfile.jsp?item=../../../../etc/ passwd Figure...applied to vulnerable fields within a cookie (see Figure 4-2). Cookie: USER=1826cc8f:PSTYLE=../../../../etc/ passwd Figure 4-2: Path Traversal...further privileges. − For example, http://host/cgi- bin/lame.cgi?file=../../../../etc/ passwd • %00 requests − This is the hexadecimal value of a
The Fragility of Air Dominance

DTIC Science & Technology

2012-03-22

diversion of funds to prosecute an inadequately Congressionally supported war in Iraq and Afghanistan.55 General Barry R . McCaffrey, USA (Ret...Aviation Week, http://www.aviationweek.com/aw/generic/story.jsp?id=news/ awst /2011/01/03/AW_01_03_2011_ p18-279564.xml&channel=defense (accessed December 6...55 General Barry R . McCaffrey USA (Ret), “After Action Report-Visit Nellis and Scott AFB 14-17 August 2007,” memorandum for Colonel Mike Meese
CAS - A Turboprop Solution for the COIN Fight

DTIC Science & Technology

2009-01-01

Worlds First Civilian Tiltrotor. http://www.bellagusta.com/air ba main.cfm. Accessed 13 Jan 2009. Blake, Brett R , AT-6-The Best Investmentfor the Long War...Terroism and Counterinsurgency, CRS for Congress RL32737, Washington DC: Congressional Research Service, 24 Jan. 2005. Blake, Brett R Major USAF. AT-6...www.aviationweek.com/aw/generic/channel .jsp?channel= awst # (accessed 15 Jan 2009). 7 Bolkcom and Katzman, 24. 8 U.S. Congress, Office ofTechnology
Constraint monitoring in TOSCA

NASA Technical Reports Server (NTRS)

Beck, Howard

1992-01-01

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

NASA Technical Reports Server (NTRS)

Mollikarimi, Cindy; Gargan, Robert; Zweben, Monte

1991-01-01

A scheduling system incorporating AI is described and applied to the automated processing of the Space Shuttle. The unique problem of addressing the temporal, resource, and orbiter-configuration requirements of shuttle processing is described with comparisons to traditional project management for manufacturing processes. The present scheduling system is developed to handle the late inputs and complex programs that characterize shuttle processing by incorporating fixed preemptive scheduling, constraint-based simulated annealing, and the characteristics of an 'anytime' algorithm. The Space-Shuttle processing environment is modeled with 500 activities broken down into 4000 subtasks and with 1600 temporal constraints, 8000 resource constraints, and 3900 state requirements. The algorithm is shown to scale to very large problems and maintain anytime characteristics suggesting that an automated scheduling process is achievable and potentially cost-effective.
Computer-Assisted Scheduling of Army Unit Training: An Application of Simulated Annealing.

ERIC Educational Resources Information Center

Hart, Roland J.; Goehring, Dwight J.

This report of an ongoing research project intended to provide computer assistance to Army units for the scheduling of training focuses on the feasibility of simulated annealing, a heuristic approach for solving scheduling problems. Following an executive summary and brief introduction, the document is divided into three sections. First, the Army…
Mothers' Night Work and Children's Behavior Problems

ERIC Educational Resources Information Center

Dunifon, Rachel; Kalil, Ariel; Crosby, Danielle A.; Su, Jessica Houston

2013-01-01

Many mothers work in jobs with nonstandard schedules (i.e., schedules that involve work outside of the traditional 9-5, Monday through Friday schedule); this is particularly true for economically disadvantaged mothers. In the present article, we used longitudinal data from the Fragile Families and Child Wellbeing Survey (n = 2,367 mothers of…
The Isolation of Motivational, Motoric, and Schedule Effects on Operant Performance: A Modeling Approach

ERIC Educational Resources Information Center

Brackney, Ryan J.; Cheung, Timothy H. C.; Neisewander, Janet L.; Sanabria, Federico

2011-01-01

Dissociating motoric and motivational effects of pharmacological manipulations on operant behavior is a substantial challenge. To address this problem, we applied a response-bout analysis to data from rats trained to lever press for sucrose on variable-interval (VI) schedules of reinforcement. Motoric, motivational, and schedule factors (effort…
Temporal and Resource Reasoning for Planning, Scheduling and Execution in Autonomous Agents

NASA Technical Reports Server (NTRS)

Muscettola, Nicola; Hunsberger, Luke; Tsamardinos, Ioannis

2005-01-01

This viewgraph slide tutorial reviews methods for planning and scheduling events. The presentation reviews several methods and uses several examples of scheduling events for the successful and timely completion of the overall plan. Using constraint based models the presentation reviews planning with time, time representations in problem solving and resource reasoning.
Simulated Stochastic Approximation Annealing for Global Optimization with a Square-Root Cooling Schedule

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
A Study on Real-Time Scheduling Methods in Holonic Manufacturing Systems

NASA Astrophysics Data System (ADS)

Iwamura, Koji; Taimizu, Yoshitaka; Sugimura, Nobuhiro

Recently, new architectures of manufacturing systems have been proposed to realize flexible control structures of the manufacturing systems, which can cope with the dynamic changes in the volume and the variety of the products and also the unforeseen disruptions, such as failures of manufacturing resources and interruptions by high priority jobs. They are so called as the autonomous distributed manufacturing system, the biological manufacturing system and the holonic manufacturing system. Rule-based scheduling methods were proposed and applied to the real-time production scheduling problems of the HMS (Holonic Manufacturing System) in the previous report. However, there are still remaining problems from the viewpoint of the optimization of the whole production schedules. New procedures are proposed, in the present paper, to select the production schedules, aimed at generating effective production schedules in real-time. The proposed methods enable the individual holons to select suitable machining operations to be carried out in the next time period. Coordination process among the holons is also proposed to carry out the coordination based on the effectiveness values of the individual holons.
Towards a dynamical scheduler for ALMA: a science - software collaboration

NASA Astrophysics Data System (ADS)

Avarias, Jorge; Toledo, Ignacio; Espada, Daniel; Hibbard, John; Nyman, Lars-Ake; Hiriart, Rafael

2016-07-01

State-of-the art astronomical facilities are costly to build and operate, hence it is essential that these facilities must be operated as much efficiently as possible, trying to maximize the scientific output and at the same time minimizing overhead times. Over the latest decades the scheduling problem has drawn attention of research because new facilities have been demonstrated that is unfeasible to try to schedule observations manually, due the complexity to satisfy the astronomical and instrumental constraints and the number of scientific proposals to be reviewed and evaluated in near real-time. In addition, the dynamic nature of some constraints make this problem even more difficult. The Atacama Large Millimeter/submillimeter Array (ALMA) is a major collaboration effort between European (ESO), North American (NRAO) and East Asian countries (NAOJ), under operations on the Chilean Chajnantor plateau, at 5.000 meters of altitude. During normal operations at least two independent arrays are available, aiming to achieve different types of science. Since ALMA does not observe in the visible spectrum, observations are not limited to night time only, thus a 24/7 operation with little downtime as possible is expected when full operations state will have been reached. However, during preliminary operations (early-science) ALMA has been operated on tied schedules using around half of the whole day-time to conduct scientific observations. The purpose of this paper is to explain how the observation scheduling and its optimization is done within ALMA, giving details about the problem complexity, its similarities and differences with traditional scheduling problems found in the literature. The paper delves into the current recommendation system implementation and the difficulties found during the road to its deployment in production.
Mission scheduling

NASA Technical Reports Server (NTRS)

Gaspin, Christine

1989-01-01

How a neural network can work, compared to a hybrid system based on an operations research and artificial intelligence approach, is investigated through a mission scheduling problem. The characteristic features of each system are discussed.
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.
A System for Automatically Generating Scheduling Heuristics

NASA Technical Reports Server (NTRS)

Morris, Robert

1996-01-01

The goal of this research is to improve the performance of automated schedulers by designing and implementing an algorithm by automatically generating heuristics by selecting a schedule. The particular application selected by applying this method solves the problem of scheduling telescope observations, and is called the Associate Principal Astronomer. The input to the APA scheduler is a set of observation requests submitted by one or more astronomers. Each observation request specifies an observation program as well as scheduling constraints and preferences associated with the program. The scheduler employs greedy heuristic search to synthesize a schedule that satisfies all hard constraints of the domain and achieves a good score with respect to soft constraints expressed as an objective function established by an astronomer-user.
A Comparison of Earned Value Management and Earned Schedule as Schedule Predictors on DoD ACAT I Programs

DTIC Science & Technology

2013-03-01

33 Mario Vanhoucke and Stephan Vandevoorde – “Measuring the Accuracy of Earned Value/Earned Schedule Forecasting Predictors” (2007...technical problem to the present day ‘ super projects’” (Clark and Lorenzoni, 1997: 2). Cost engineering has “application regardless of industry...large construction projects, but also the acceptance of earned schedule principles on an international scale. Mario Vanhoucke and Stephan Vandevoorde
A Network Flow Approach to the Initial Skills Training Scheduling Problem

DTIC Science & Technology

2007-12-01

include (but are not limited to) queuing theory, stochastic analysis and simulation. After the demand schedule has been estimated, it can be ...software package has already been purchased and is in use by AFPC, AFPC has requested that the new algorithm be programmed in this language as well ...the discussed outputs from those schedules. Required Inputs A single input file details the students to be scheduled as well as the courses

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

PubMed

Xiang, Wei; Yin, Jiao; Lim, Gino

2015-02-01

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

ERIC Educational Resources Information Center

Beland, Robert M.

1983-01-01

With an increasing number of the nation's work force experiencing "bulk leisure" time because of new work scheduling procedures, parks and recreation offices are encouraged to examine their program scheduling and content. (JM)
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.
Optimal Rate Schedules with Data Sharing in Energy Harvesting Communication Systems.

PubMed

Wu, Weiwei; Li, Huafan; Shan, Feng; Zhao, Yingchao

2017-12-20

Despite the abundant research on energy-efficient rate scheduling polices in energy harvesting communication systems, few works have exploited data sharing among multiple applications to further enhance the energy utilization efficiency, considering that the harvested energy from environments is limited and unstable. In this paper, to overcome the energy shortage of wireless devices at transmitting data to a platform running multiple applications/requesters, we design rate scheduling policies to respond to data requests as soon as possible by encouraging data sharing among data requests and reducing the redundancy. We formulate the problem as a transmission completion time minimization problem under constraints of dynamical data requests and energy arrivals. We develop offline and online algorithms to solve this problem. For the offline setting, we discover the relationship between two problems: the completion time minimization problem and the energy consumption minimization problem with a given completion time. We first derive the optimal algorithm for the min-energy problem and then adopt it as a building block to compute the optimal solution for the min-completion-time problem. For the online setting without future information, we develop an event-driven online algorithm to complete the transmission as soon as possible. Simulation results validate the efficiency of the proposed algorithm.
Optimal Rate Schedules with Data Sharing in Energy Harvesting Communication Systems

PubMed Central

Wu, Weiwei; Li, Huafan; Shan, Feng; Zhao, Yingchao

2017-01-01

Despite the abundant research on energy-efficient rate scheduling polices in energy harvesting communication systems, few works have exploited data sharing among multiple applications to further enhance the energy utilization efficiency, considering that the harvested energy from environments is limited and unstable. In this paper, to overcome the energy shortage of wireless devices at transmitting data to a platform running multiple applications/requesters, we design rate scheduling policies to respond to data requests as soon as possible by encouraging data sharing among data requests and reducing the redundancy. We formulate the problem as a transmission completion time minimization problem under constraints of dynamical data requests and energy arrivals. We develop offline and online algorithms to solve this problem. For the offline setting, we discover the relationship between two problems: the completion time minimization problem and the energy consumption minimization problem with a given completion time. We first derive the optimal algorithm for the min-energy problem and then adopt it as a building block to compute the optimal solution for the min-completion-time problem. For the online setting without future information, we develop an event-driven online algorithm to complete the transmission as soon as possible. Simulation results validate the efficiency of the proposed algorithm. PMID:29261135
A novel feature extraction scheme with ensemble coding for protein-protein interaction prediction.

PubMed

Du, Xiuquan; Cheng, Jiaxing; Zheng, Tingting; Duan, Zheng; Qian, Fulan

2014-07-18

Protein-protein interactions (PPIs) play key roles in most cellular processes, such as cell metabolism, immune response, endocrine function, DNA replication, and transcription regulation. PPI prediction is one of the most challenging problems in functional genomics. Although PPI data have been increasing because of the development of high-throughput technologies and computational methods, many problems are still far from being solved. In this study, a novel predictor was designed by using the Random Forest (RF) algorithm with the ensemble coding (EC) method. To reduce computational time, a feature selection method (DX) was adopted to rank the features and search the optimal feature combination. The DXEC method integrates many features and physicochemical/biochemical properties to predict PPIs. On the Gold Yeast dataset, the DXEC method achieves 67.2% overall precision, 80.74% recall, and 70.67% accuracy. On the Silver Yeast dataset, the DXEC method achieves 76.93% precision, 77.98% recall, and 77.27% accuracy. On the human dataset, the prediction accuracy reaches 80% for the DXEC-RF method. We extended the experiment to a bigger and more realistic dataset that maintains 50% recall on the Yeast All dataset and 80% recall on the Human All dataset. These results show that the DXEC method is suitable for performing PPI prediction. The prediction service of the DXEC-RF classifier is available at http://ailab.ahu.edu.cn:8087/ DXECPPI/index.jsp.
Protocols for distributive scheduling

NASA Technical Reports Server (NTRS)

Richards, Stephen F.; Fox, Barry

1993-01-01

The increasing complexity of space operations and the inclusion of interorganizational and international groups in the planning and control of space missions lead to requirements for greater communication, coordination, and cooperation among mission schedulers. These schedulers must jointly allocate scarce shared resources among the various operational and mission oriented activities while adhering to all constraints. This scheduling environment is complicated by such factors as the presence of varying perspectives and conflicting objectives among the schedulers, the need for different schedulers to work in parallel, and limited communication among schedulers. Smooth interaction among schedulers requires the use of protocols that govern such issues as resource sharing, authority to update the schedule, and communication of updates. This paper addresses the development and characteristics of such protocols and their use in a distributed scheduling environment that incorporates computer-aided scheduling tools. An example problem is drawn from the domain of space shuttle mission planning.
Distributed project scheduling at NASA: Requirements for manual protocols and computer-based support

NASA Technical Reports Server (NTRS)

Richards, Stephen F.

1992-01-01

The increasing complexity of space operations and the inclusion of interorganizational and international groups in the planning and control of space missions lead to requirements for greater communication, coordination, and cooperation among mission schedulers. These schedulers must jointly allocate scarce shared resources among the various operational and mission oriented activities while adhering to all constraints. This scheduling environment is complicated by such factors as the presence of varying perspectives and conflicting objectives among the schedulers, the need for different schedulers to work in parallel, and limited communication among schedulers. Smooth interaction among schedulers requires the use of protocols that govern such issues as resource sharing, authority to update the schedule, and communication of updates. This paper addresses the development and characteristics of such protocols and their use in a distributed scheduling environment that incorporates computer-aided scheduling tools. An example problem is drawn from the domain of Space Shuttle mission planning.
Production scheduling and rescheduling with genetic algorithms.

PubMed

Bierwirth, C; Mattfeld, D C

1999-01-01

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

NASA Technical Reports Server (NTRS)

Farrahi, Amir Hossein; Goldbert, Alan; Bagasol, Leonard Neil; Jung, Jaewoo

2017-01-01

Graph theory is used to investigate three different problems arising in air traffic management. First, using a polynomial reduction from a graph partitioning problem, it is shown that both the airspace sectorization problem and its incremental counterpart, the sector combination problem are NP-hard, in general, under several simple workload models. Second, using a polynomial time reduction from maximum independent set in graphs, it is shown that for any fixed e, the problem of finding a solution to the minimum delay scheduling problem in traffic flow management that is guaranteed to be within n1-e of the optimal, where n is the number of aircraft in the problem instance, is NP-hard. Finally, a problem arising in precision arrival scheduling is formulated and solved using graph reachability. These results demonstrate that graph theory provides a powerful framework for modeling, reasoning about, and devising algorithmic solutions to diverse problems arising in air traffic management.
Applying Graph Theory to Problems in Air Traffic Management

NASA Technical Reports Server (NTRS)

Farrahi, Amir H.; Goldberg, Alan T.; Bagasol, Leonard N.; Jung, Jaewoo

2017-01-01

Graph theory is used to investigate three different problems arising in air traffic management. First, using a polynomial reduction from a graph partitioning problem, it isshown that both the airspace sectorization problem and its incremental counterpart, the sector combination problem are NP-hard, in general, under several simple workload models. Second, using a polynomial time reduction from maximum independent set in graphs, it is shown that for any fixed e, the problem of finding a solution to the minimum delay scheduling problem in traffic flow management that is guaranteed to be within n1-e of the optimal, where n is the number of aircraft in the problem instance, is NP-hard. Finally, a problem arising in precision arrival scheduling is formulated and solved using graph reachability. These results demonstrate that graph theory provides a powerful framework for modeling, reasoning about, and devising algorithmic solutions to diverse problems arising in air traffic management.
Scheduling Jobs with Variable Job Processing Times on Unrelated Parallel Machines

PubMed Central

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

PubMed

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

1993-01-01

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

NASA Astrophysics Data System (ADS)

Moreno-Camacho, Carlos A.; Montoya-Torres, Jairo R.; Vélez-Gallego, Mario C.

2018-06-01

Only a few studies in the available scientific literature address the problem of having a group of workers that do not share identical levels of productivity during the planning horizon. This study considers a workforce scheduling problem in which the actual processing time is a function of the scheduling sequence to represent the decline in workers' performance, evaluating two classical performance measures separately: makespan and maximum tardiness. Several mathematical models are compared with each other to highlight the advantages of each approach. The mathematical models are tested with randomly generated instances available from a public e-library.
Transportation Network Analysis and Decomposition Methods

DOT National Transportation Integrated Search

1978-03-01

The report outlines research in transportation network analysis using decomposition techniques as a basis for problem solutions. Two transportation network problems were considered in detail: a freight network flow problem and a scheduling problem fo...
A Hybrid Cellular Genetic Algorithm for Multi-objective Crew Scheduling Problem

NASA Astrophysics Data System (ADS)

Jolai, Fariborz; Assadipour, Ghazal

Crew scheduling is one of the important problems of the airline industry. This problem aims to cover a number of flights by crew members, such that all the flights are covered. In a robust scheduling the assignment should be so that the total cost, delays, and unbalanced utilization are minimized. As the problem is NP-hard and the objectives are in conflict with each other, a multi-objective meta-heuristic called CellDE, which is a hybrid cellular genetic algorithm, is implemented as the optimization method. The proposed algorithm provides the decision maker with a set of non-dominated or Pareto-optimal solutions, and enables them to choose the best one according to their preferences. A set of problems of different sizes is generated and solved using the proposed algorithm. Evaluating the performance of the proposed algorithm, three metrics are suggested, and the diversity and the convergence of the achieved Pareto front are appraised. Finally a comparison is made between CellDE and PAES, another meta-heuristic algorithm. The results show the superiority of CellDE.
Due-Window Assignment Scheduling with Variable Job Processing Times

PubMed Central

Wu, Yu-Bin

2015-01-01

We consider a common due-window assignment scheduling problem jobs with variable job processing times on a single machine, where the processing time of a job is a function of its position in a sequence (i.e., learning effect) or its starting time (i.e., deteriorating effect). The problem is to determine the optimal due-windows, and the processing sequence simultaneously to minimize a cost function includes earliness, tardiness, the window location, window size, and weighted number of tardy jobs. We prove that the problem can be solved in polynomial time. PMID:25918745
Single machine scheduling with slack due dates assignment

NASA Astrophysics Data System (ADS)

Liu, Weiguo; Hu, Xiangpei; Wang, Xuyin

2017-04-01

This paper considers a single machine scheduling problem in which each job is assigned an individual due date based on a common flow allowance (i.e. all jobs have slack due date). The goal is to find a sequence for jobs, together with a due date assignment, that minimizes a non-regular criterion comprising the total weighted absolute lateness value and common flow allowance cost, where the weight is a position-dependent weight. In order to solve this problem, an ? time algorithm is proposed. Some extensions of the problem are also shown.
Constraint satisfaction adaptive neural network and heuristics combined approaches for generalized job-shop scheduling.

PubMed

Yang, S; Wang, D

2000-01-01

This paper presents a constraint satisfaction adaptive neural network, together with several heuristics, to solve the generalized job-shop scheduling problem, one of NP-complete constraint satisfaction problems. The proposed neural network can be easily constructed and can adaptively adjust its weights of connections and biases of units based on the sequence and resource constraints of the job-shop scheduling problem during its processing. Several heuristics that can be combined with the neural network are also presented. In the combined approaches, the neural network is used to obtain feasible solutions, the heuristic algorithms are used to improve the performance of the neural network and the quality of the obtained solutions. Simulations have shown that the proposed neural network and its combined approaches are efficient with respect to the quality of solutions and the solving speed.

Future aircraft networks and schedules

NASA Astrophysics Data System (ADS)

Shu, Yan

2011-07-01

Because of the importance of air transportation scheduling, the emergence of small aircraft and the vision of future fuel-efficient aircraft, this thesis has focused on the study of aircraft scheduling and network design involving multiple types of aircraft and flight services. It develops models and solution algorithms for the schedule design problem and analyzes the computational results. First, based on the current development of small aircraft and on-demand flight services, this thesis expands a business model for integrating on-demand flight services with the traditional scheduled flight services. This thesis proposes a three-step approach to the design of aircraft schedules and networks from scratch under the model. In the first step, both a frequency assignment model for scheduled flights that incorporates a passenger path choice model and a frequency assignment model for on-demand flights that incorporates a passenger mode choice model are created. In the second step, a rough fleet assignment model that determines a set of flight legs, each of which is assigned an aircraft type and a rough departure time is constructed. In the third step, a timetable model that determines an exact departure time for each flight leg is developed. Based on the models proposed in the three steps, this thesis creates schedule design instances that involve almost all the major airports and markets in the United States. The instances of the frequency assignment model created in this thesis are large-scale non-convex mixed-integer programming problems, and this dissertation develops an overall network structure and proposes iterative algorithms for solving these instances. The instances of both the rough fleet assignment model and the timetable model created in this thesis are large-scale mixed-integer programming problems, and this dissertation develops subproblem schemes for solving these instances. Based on these solution algorithms, this dissertation also presents computational results of these large-scale instances. To validate the models and solution algorithms developed, this thesis also compares the daily flight schedules that it designs with the schedules of the existing airlines. Furthermore, it creates instances that represent different economic and fuel-prices conditions and derives schedules under these different conditions. In addition, it discusses the implication of using new aircraft in the future flight schedules. Finally, future research in three areas---model, computational method, and simulation for validation---is proposed.
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.
Optimization Models for Scheduling of Jobs

PubMed Central

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
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.
Artificial Immune Algorithm for Subtask Industrial Robot Scheduling in Cloud Manufacturing

NASA Astrophysics Data System (ADS)

Suma, T.; Murugesan, R.

2018-04-01

The current generation of manufacturing industry requires an intelligent scheduling model to achieve an effective utilization of distributed manufacturing resources, which motivated us to work on an Artificial Immune Algorithm for subtask robot scheduling in cloud manufacturing. This scheduling model enables a collaborative work between the industrial robots in different manufacturing centers. This paper discussed two optimizing objectives which includes minimizing the cost and load balance of industrial robots through scheduling. To solve these scheduling problems, we used the algorithm based on Artificial Immune system. The parameters are simulated with MATLAB and the results compared with the existing algorithms. The result shows better performance than existing.
Extended precedence preservative crossover for job shop scheduling problems

NASA Astrophysics Data System (ADS)

Ong, Chung Sin; Moin, Noor Hasnah; Omar, Mohd

2013-04-01

Job shop scheduling problems (JSSP) is one of difficult combinatorial scheduling problems. A wide range of genetic algorithms based on the two parents crossover have been applied to solve the problem but multi parents (more than two parents) crossover in solving the JSSP is still lacking. This paper proposes the extended precedence preservative crossover (EPPX) which uses multi parents for recombination in the genetic algorithms. EPPX is a variation of the precedence preservative crossover (PPX) which is one of the crossovers that perform well to find the solutions for the JSSP. EPPX is based on a vector to determine the gene selected in recombination for the next generation. Legalization of children (offspring) can be eliminated due to the JSSP representation encoded by using permutation with repetition that guarantees the feasibility of chromosomes. The simulations are performed on a set of benchmarks from the literatures and the results are compared to ensure the sustainability of multi parents recombination in solving the JSSP.
Manipulating Tabu List to Handle Machine Breakdowns in Job Shop Scheduling Problems

NASA Astrophysics Data System (ADS)

Nababan, Erna Budhiarti; SalimSitompul, Opim

2011-06-01

Machine breakdowns in a production schedule may occur on a random basis that make the well-known hard combinatorial problem of Job Shop Scheduling Problems (JSSP) becomes more complex. One of popular techniques used to solve the combinatorial problems is Tabu Search. In this technique, moves that will be not allowed to be revisited are retained in a tabu list in order to avoid in gaining solutions that have been obtained previously. In this paper, we propose an algorithm to employ a second tabu list to keep broken machines, in addition to the tabu list that keeps the moves. The period of how long the broken machines will be kept on the list is categorized using fuzzy membership function. Our technique are tested to the benchmark data of JSSP available on the OR library. From the experiment, we found that our algorithm is promising to help a decision maker to face the event of machine breakdowns.
CABINS: Case-based interactive scheduler

NASA Technical Reports Server (NTRS)

Miyashita, Kazuo; Sycara, Katia

1992-01-01

In this paper we discuss the need for interactive factory schedule repair and improvement, and we identify case-based reasoning (CBR) as an appropriate methodology. Case-based reasoning is the problem solving paradigm that relies on a memory for past problem solving experiences (cases) to guide current problem solving. Cases similar to the current case are retrieved from the case memory, and similarities and differences of the current case to past cases are identified. Then a best case is selected, and its repair plan is adapted to fit the current problem description. If a repair solution fails, an explanation for the failure is stored along with the case in memory, so that the user can avoid repeating similar failures in the future. So far we have identified a number of repair strategies and tactics for factory scheduling and have implemented a part of our approach in a prototype system, called CABINS. As a future work, we are going to scale up CABINS to evaluate its usefulness in a real manufacturing environment.
A Study of the Operating Room Scheduling System at Tripler Army Medical Center, Hawaii

DTIC Science & Technology

1981-08-01

PROCESSING CLASS V SYSTEM .... .......... . A BIBLIOGRAPHY ....... ........... . . . .. . ii ’I. INTRODUCTIO9 Development of the Problem Convinced that...of the most difficult administrativo tasks that a modern hospital must face, and proposed using a combination of a master posting sheet and a...deal with scheduling problems.9 This particular process also incorporates the two-room system doscribed earlier, and the author admits that this
Scheduling Jobs and a Variable Maintenance on a Single Machine with Common Due-Date Assignment

PubMed Central

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
Translations on North Korea No. 618

DTIC Science & Technology

1978-09-25

United Nations," which are maneuvers to fabricate "Two Koreas,’ and we will attempt to overcome the Japan-South Korea alliance in the Diet as well as...outside the Diet . We will do our utmost to fight for our struggle, includ- ing the withdrawal of American troops from Okinawa. Let our two parties...The JSP) is appealing within and outside the Diet that independent peaceful unification is right. In addition, we must vigorously fight to get
Optimizing Preventive Strategies and Malaria Diagnostics to Reduce the Impact of Malaria on US Military Forces

DTIC Science & Technology

2012-05-01

but not limited to dengue fever , early shigellosis, typhoid fever , rickettsiosis, leptospirosis or acute retroviral syndrome). (strong recommendation...provided support for a Multiplex RDT to identify fever causing pathogens in the blood, but the performance of this assay was deemed inadequate and...index.jsp 7 Yeboah-Antwi K, Pilingana P, Macleod WB, et al. Community case management of fever due to malaria and pneumonia in children under five in
Information system building of the urban electromagnetic environment

NASA Astrophysics Data System (ADS)

Wang, Jiechen; Rui, Yikang; Shen, Dingtao; Yu, Qing

2007-06-01

The pollution of urban electromagnetic radiation has become more serious, however, there is still lack of a perfect and interactive User System to manage, analyze and issue the information. In this study, taking the electromagnetic environment of Nanjing as an example, an information system based on WebGIS with the techniques of ArcIMS and JSP has been developed, in order to provide the services and technique supports for information query of public and decision making of relevant departments.
Defense Strategy and Forces: Setting Future Directions

DTIC Science & Technology

2007-11-15

Howard Fireman, and Christopher Deegan , “A Question of Cost,” Armed Forces Journal, June 2007, pp. 24– 27, 47. See also Emelie Rutherford, “Affordable...2 is under construction. 24. Craig Covault, “Final Cape Titan Propels NRO’s Secret Operations,” 8 May 2005, available at http://www.aviationweek.com...aw/generic/story_generic.jsp?channel=awst&id =news/05095p04.xml (accessed November 2007); and Craig Covault, “Space Recon Dwindles as Iran, China
Joint Space Operations Center (JSpOC) Mission System Increment 2 (JMS Inc 2)

DTIC Science & Technology

2016-03-01

Defense Acquisition Executive DoD - Department of Defense DoDAF - DoD Architecture Framework FD - Full Deployment FDD - Full Deployment Decision FY...date has slipped from September 2016 to December 2016 and FDD has slipped from October 2016 to March 2017 since the last MAIS Annual Report...testing. This added test time, in combination with funding reductions and the US Government furlough and shutdown in FY13, caused a total FDD slip
CAS -- A Turboprop Solution for the COIN Fight

DTIC Science & Technology

2009-04-14

Civilian Tiltrotor. http://www.bellagusta.com/air ba main.cfm. Accessed 13 Jan 2009. Blake, Brett R , AT-6-The Best Investmentfor the Long War, Air...Counterinsurgency, CRS for Congress RL32737, Washington DC: Congressional Research Service, 24 Jan. 2005. Blake, Brett R Major USAF. AT-6-The Best...www.aviationweek.com/aw/generic/channel .jsp?channel= awst # (accessed 15 Jan 2009). 7 Bolkcom and Katzman, 24. 8 U.S. Congress, Office ofTechnology Assessment, Global
The Mechanical Robustness of Atomic-Layer- and Molecular-Layer-Deposited Coatings on Polymer Substrates

DTIC Science & Technology

2009-01-01

coatings include flexible liquid crystal displays, OLEDs , and photovoltaic modules.15 Additional applications include packaging for medical devices...copyright, see http://jap.aip.org/jap/copyright.jsp ics of TFT Technology on Flexible Substrates, Flexible Flat Panel Dis- plays, edited by G. P. Crawford...grade “Teonex Q65” is commonly used in the organic light emitting diode OLED field because it is both heat stabilized and coated with a scratch
Earthquake-induced ground failures in Italy from a reviewed database

NASA Astrophysics Data System (ADS)

Martino, S.; Prestininzi, A.; Romeo, R. W.

2014-04-01

A database (Italian acronym CEDIT) of earthquake-induced ground failures in Italy is presented, and the related content is analysed. The catalogue collects data regarding landslides, liquefaction, ground cracks, surface faulting and ground changes triggered by earthquakes of Mercalli epicentral intensity 8 or greater that occurred in the last millennium in Italy. As of January 2013, the CEDIT database has been available online for public use (http://www.ceri.uniroma1.it/cn/gis.jsp ) and is presently hosted by the website of the Research Centre for Geological Risks (CERI) of the Sapienza University of Rome. Summary statistics of the database content indicate that 14% of the Italian municipalities have experienced at least one earthquake-induced ground failure and that landslides are the most common ground effects (approximately 45%), followed by ground cracks (32%) and liquefaction (18%). The relationships between ground effects and earthquake parameters such as seismic source energy (earthquake magnitude and epicentral intensity), local conditions (site intensity) and source-to-site distances are also analysed. The analysis indicates that liquefaction, surface faulting and ground changes are much more dependent on the earthquake source energy (i.e. magnitude) than landslides and ground cracks. In contrast, the latter effects are triggered at lower site intensities and greater epicentral distances than the other environmental effects.
Scheduling from the perspective of the application

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

Berman, F.; Wolski, R.

1996-12-31

Metacomputing is the aggregation of distributed and high-performance resources on coordinated networks. With careful scheduling, resource-intensive applications can be implemented efficiently on metacomputing systems at the sizes of interest to developers and users. In this paper we focus on the problem of scheduling applications on metacomputing systems. We introduce the concept of application-centric scheduling in which everything about the system is evaluated in terms of its impact on the application. Application-centric scheduling is used by virtually all metacomputer programmers to achieve performance on metacomputing systems. We describe two successful metacomputing applications to illustrate this approach, and describe AppLeS scheduling agentsmore » which generalize the application-centric scheduling approach. Finally, we show preliminary results which compare AppLeS-derived schedules with conventional strip and blocked schedules for a two-dimensional Jacobi code.« less
Chandra mission scheduling on-orbit experience

NASA Astrophysics Data System (ADS)

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

2008-07-01

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

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

PubMed Central

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

2013-01-01

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

PubMed

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

2013-01-01

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

NASA Technical Reports Server (NTRS)

Civeit, Thomas

2013-01-01

The NASA Stratospheric Observatory for Infrared Astronomy (SOFIA) is a joint US/German project to develop and operate a gyro-stabilized 2.5-meter telescope in a Boeing 747SP. SOFIA's first science observations were made in December 2010. During 2011, SOFIA accomplished 30 flights in the "Early Science" program as well as a deployment to Germany. The new observing period, known as Cycle 1, is scheduled to begin in 2012. It includes 46 science flights grouped in four multi-week observing campaigns spread through a 13-month span. Automation of the flight scheduling process offers a major challenge to the SOFIA mission operations. First because it is needed to mitigate its relatively high cost per unit observing time compared to space-borne missions. Second because automated scheduling techniques available for ground-based and space-based telescopes are inappropriate for an airborne observatory. Although serious attempts have been made in the past to solve part of the problem, until recently mission operations staff was still manually scheduling flights. We present in this paper a new automated solution for generating SOFIA long-term schedules that will be used in operations from the Cycle 1 observing period. We describe the constraints that should be satisfied to solve the SOFIA scheduling problem in the context of real operations. We establish key formulas required to efficiently calculate the aircraft course over ground when evaluating flight schedules. We describe the foundations of the SOFIA long-term scheduler, the constraint representation, and the random search based algorithm that generates observation and instrument schedules. Finally, we report on how the new long-term scheduler has been used in operations to date.
Hybrid Metaheuristics for Solving a Fuzzy Single Batch-Processing Machine Scheduling Problem

PubMed Central

Molla-Alizadeh-Zavardehi, S.; Tavakkoli-Moghaddam, R.; Lotfi, F. Hosseinzadeh

2014-01-01

This paper deals with a problem of minimizing total weighted tardiness of jobs in a real-world single batch-processing machine (SBPM) scheduling in the presence of fuzzy due date. In this paper, first a fuzzy mixed integer linear programming model is developed. Then, due to the complexity of the problem, which is NP-hard, we design two hybrid metaheuristics called GA-VNS and VNS-SA applying the advantages of genetic algorithm (GA), variable neighborhood search (VNS), and simulated annealing (SA) frameworks. Besides, we propose three fuzzy earliest due date heuristics to solve the given problem. Through computational experiments with several random test problems, a robust calibration is applied on the parameters. Finally, computational results on different-scale test problems are presented to compare the proposed algorithms. PMID:24883359
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.
A three-stage heuristic for harvest scheduling with access road network development

Treesearch

Mark M. Clark; Russell D. Meller; Timothy P. McDonald

2000-01-01

In this article we present a new model for the scheduling of forest harvesting with spatial and temporal constraints. Our approach is unique in that we incorporate access road network development into the harvest scheduling selection process. Due to the difficulty of solving the problem optimally, we develop a heuristic that consists of a solution construction stage...
A Chaotic Particle Swarm Optimization-Based Heuristic for Market-Oriented Task-Level Scheduling in Cloud Workflow Systems.

PubMed

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

PubMed

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

2013-04-01

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

NASA Astrophysics Data System (ADS)

Ghatpande, Abhay; Nakazato, Hidenori; Beaumont, Olivier; Watanabe, Hiroshi

Divisible Load Theory (DLT) is an established mathematical framework to study Divisible Load Scheduling (DLS). However, traditional DLT does not address the scheduling of results back to source (i. e., result collection), nor does it comprehensively deal with system heterogeneity. In this paper, the DLSRCHETS (DLS with Result Collection on HET-erogeneous Systems) problem is addressed. The few papers to date that have dealt with DLSRCHETS, proposed simplistic LIFO (Last In, First Out) and FIFO (First In, First Out) type of schedules as solutions to DLSRCHETS. In this paper, a new polynomial time heuristic algorithm, SPORT (System Parameters based Optimized Result Transfer), is proposed as a solution to the DLSRCHETS problem. With the help of simulations, it is proved that the performance of SPORT is significantly better than existing algorithms. The other major contributions of this paper include, for the first time ever, (a) the derivation of the condition to identify the presence of idle time in a FIFO schedule for two processors, (b) the identification of the limiting condition for the optimality of FIFO and LIFO schedules for two processors, and (c) the introduction of the concept of equivalent processor in DLS for heterogeneous systems with result collection.
A Chaotic Particle Swarm Optimization-Based Heuristic for Market-Oriented Task-Level Scheduling in Cloud Workflow Systems

PubMed Central

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
APGEN Scheduling: 15 Years of Experience in Planning Automation

NASA Technical Reports Server (NTRS)

Maldague, Pierre F.; Wissler, Steve; Lenda, Matthew; Finnerty, Daniel

2014-01-01

In this paper, we discuss the scheduling capability of APGEN (Activity Plan Generator), a multi-mission planning application that is part of the NASA AMMOS (Advanced Multi- Mission Operations System), and how APGEN scheduling evolved over its applications to specific Space Missions. Our analysis identifies two major reasons for the successful application of APGEN scheduling to real problems: an expressive DSL (Domain-Specific Language) for formulating scheduling algorithms, and a well-defined process for enlisting the help of auxiliary modeling tools in providing high-fidelity, system-level simulations of the combined spacecraft and ground support system.
Shift scheduling model considering workload and worker’s preference for security department

NASA Astrophysics Data System (ADS)

Herawati, A.; Yuniartha, D. R.; Purnama, I. L. I.; Dewi, LT

2018-04-01

Security department operates for 24 hours and applies shift scheduling to organize its workers as well as in hotel industry. This research has been conducted to develop shift scheduling model considering the workers physical workload using rating of perceived exertion (RPE) Borg’s Scale and workers’ preference to accommodate schedule flexibility. The mathematic model is developed in integer linear programming and results optimal solution for simple problem. Resulting shift schedule of the developed model has equally distribution shift allocation among workers to balance the physical workload and give flexibility for workers in working hours arrangement.
Improved teaching-learning-based and JAYA optimization algorithms for solving flexible flow shop scheduling problems

NASA Astrophysics Data System (ADS)

Buddala, Raviteja; Mahapatra, Siba Sankar

2017-11-01

Flexible flow shop (or a hybrid flow shop) scheduling problem is an extension of classical flow shop scheduling problem. In a simple flow shop configuration, a job having `g' operations is performed on `g' operation centres (stages) with each stage having only one machine. If any stage contains more than one machine for providing alternate processing facility, then the problem becomes a flexible flow shop problem (FFSP). FFSP which contains all the complexities involved in a simple flow shop and parallel machine scheduling problems is a well-known NP-hard (Non-deterministic polynomial time) problem. Owing to high computational complexity involved in solving these problems, it is not always possible to obtain an optimal solution in a reasonable computation time. To obtain near-optimal solutions in a reasonable computation time, a large variety of meta-heuristics have been proposed in the past. However, tuning algorithm-specific parameters for solving FFSP is rather tricky and time consuming. To address this limitation, teaching-learning-based optimization (TLBO) and JAYA algorithm are chosen for the study because these are not only recent meta-heuristics but they do not require tuning of algorithm-specific parameters. Although these algorithms seem to be elegant, they lose solution diversity after few iterations and get trapped at the local optima. To alleviate such drawback, a new local search procedure is proposed in this paper to improve the solution quality. Further, mutation strategy (inspired from genetic algorithm) is incorporated in the basic algorithm to maintain solution diversity in the population. Computational experiments have been conducted on standard benchmark problems to calculate makespan and computational time. It is found that the rate of convergence of TLBO is superior to JAYA. From the results, it is found that TLBO and JAYA outperform many algorithms reported in the literature and can be treated as efficient methods for solving the FFSP.
Production Scheduling of Sequenced Tapes for Printed Circuit Pack Assembly.

DTIC Science & Technology

1987-07-09

detail. L j 6 The subject matter of this thesis is inspired directly from their technical report. The goals of this research are twofold: 1) Test their...The subject matter of the following chapters describes a heuristic approach to another variation of the sequenced tape production scheduling problem...assignment problem, comprise the subject matter of Chapter 5. It is sufficient to note that the three definitions of the term common correspond to the
Resource-constrained scheduling with hard due windows and rejection penalties

NASA Astrophysics Data System (ADS)

Garcia, Christopher

2016-09-01

This work studies a scheduling problem where each job must be either accepted and scheduled to complete within its specified due window, or rejected altogether. Each job has a certain processing time and contributes a certain profit if accepted or penalty cost if rejected. There is a set of renewable resources, and no resource limit can be exceeded at any time. Each job requires a certain amount of each resource when processed, and the objective is to maximize total profit. A mixed-integer programming formulation and three approximation algorithms are presented: a priority rule heuristic, an algorithm based on the metaheuristic for randomized priority search and an evolutionary algorithm. Computational experiments comparing these four solution methods were performed on a set of generated benchmark problems covering a wide range of problem characteristics. The evolutionary algorithm outperformed the other methods in most cases, often significantly, and never significantly underperformed any method.
Simultaneous personnel and vehicle shift scheduling in the waste management sector.

PubMed

Ghiani, Gianpaolo; Guerriero, Emanuela; Manni, Andrea; Manni, Emanuele; Potenza, Agostino

2013-07-01

Urban waste management is becoming an increasingly complex task, absorbing a huge amount of resources, and having a major environmental impact. The design of a waste management system consists in various activities, and one of these is related to the definition of shift schedules for both personnel and vehicles. This activity has a great incidence on the tactical and operational cost for companies. In this paper, we propose an integer programming model to find an optimal solution to the integrated problem. The aim is to determine optimal schedules at minimum cost. Moreover, we design a fast and effective heuristic to face large-size problems. Both approaches are tested on data from a real-world case in Southern Italy and compared to the current practice utilized by the company managing the service, showing that simultaneously solving these problems can lead to significant monetary savings. Copyright © 2013 Elsevier Ltd. All rights reserved.
SMEX-Lite Modular Solar Array Architecture

NASA Technical Reports Server (NTRS)

Lyons, John W.; Day, John (Technical Monitor)

2002-01-01

The NASA Small Explorer (SMEX) missions have typically had three years between mission definition and launch. This short schedule has posed significant challenges with respect to solar array design and procurement. Typically, the solar panel geometry is frozen prior to going out with a procurement. However, with the SMEX schedule, it has been virtually impossible to freeze the geometry in time to avoid scheduling problems with integrating the solar panels to the spacecraft. A modular solar array architecture was developed to alleviate this problem. This approach involves procuring sufficient modules for multiple missions and assembling the modules onto a solar array framework that is unique to each mission. The modular approach removes the solar array from the critical path of the SMEX integration and testing schedule. It also reduces the cost per unit area of the solar arrays and facilitates the inclusion of experiments involving new solar cell or panel technologies in the SMEX missions.
Final Report on DOE Project entitled Dynamic Optimized Advanced Scheduling of Bandwidth Demands for Large-Scale Science Applications

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

Ramamurthy, Byravamurthy

2014-05-05

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

NASA Astrophysics Data System (ADS)

Li, Rui; Liu, Yu-Jun; Hamada, Kunihiro

2010-12-01

Manufacturing of ship piping systems is one of the major production activities in shipbuilding. The schedule of pipe production has an important impact on the master schedule of shipbuilding. In this research, the ITOC concept was introduced to solve the scheduling problems of a piping factory, and an intelligent scheduling system was developed. The system, in which a product model, an operation model, a factory model, and a knowledge database of piping production were integrated, automated the planning process and production scheduling. Details of the above points were discussed. Moreover, an application of the system in a piping factory, which achieved a higher level of performance as measured by tardiness, lead time, and inventory, was demonstrated.

Scenario-based, closed-loop model predictive control with application to emergency vehicle scheduling

NASA Astrophysics Data System (ADS)

Goodwin, Graham. C.; Medioli, Adrian. M.

2013-08-01

Model predictive control has been a major success story in process control. More recently, the methodology has been used in other contexts, including automotive engine control, power electronics and telecommunications. Most applications focus on set-point tracking and use single-sequence optimisation. Here we consider an alternative class of problems motivated by the scheduling of emergency vehicles. Here disturbances are the dominant feature. We develop a novel closed-loop model predictive control strategy aimed at this class of problems. We motivate, and illustrate, the ideas via the problem of fluid deployment of ambulance resources.
Technology for planning and scheduling under complex constraints

NASA Astrophysics Data System (ADS)

Alguire, Karen M.; Pedro Gomes, Carla O.

1997-02-01

Within the context of law enforcement, several problems fall into the category of planning and scheduling under constraints. Examples include resource and personnel scheduling, and court scheduling. In the case of court scheduling, a schedule must be generated considering available resources, e.g., court rooms and personnel. Additionally, there are constraints on individual court cases, e.g., temporal and spatial, and between different cases, e.g., precedence. Finally, there are overall objectives that the schedule should satisfy such as timely processing of cases and optimal use of court facilities. Manually generating a schedule that satisfies all of the constraints is a very time consuming task. As the number of court cases and constraints increases, this becomes increasingly harder to handle without the assistance of automatic scheduling techniques. This paper describes artificial intelligence (AI) technology that has been used to develop several high performance scheduling applications including a military transportation scheduler, a military in-theater airlift scheduler, and a nuclear power plant outage scheduler. We discuss possible law enforcement applications where we feel the same technology could provide long-term benefits to law enforcement agencies and their operations personnel.
Enhancements of evolutionary algorithm for the complex requirements of a nurse scheduling problem

NASA Astrophysics Data System (ADS)

Tein, Lim Huai; Ramli, Razamin

2014-12-01

Over the years, nurse scheduling is a noticeable problem that is affected by the global nurse turnover crisis. The more nurses are unsatisfied with their working environment the more severe the condition or implication they tend to leave. Therefore, the current undesirable work schedule is partly due to that working condition. Basically, there is a lack of complimentary requirement between the head nurse's liability and the nurses' need. In particular, subject to highly nurse preferences issue, the sophisticated challenge of doing nurse scheduling is failure to stimulate tolerance behavior between both parties during shifts assignment in real working scenarios. Inevitably, the flexibility in shifts assignment is hard to achieve for the sake of satisfying nurse diverse requests with upholding imperative nurse ward coverage. Hence, Evolutionary Algorithm (EA) is proposed to cater for this complexity in a nurse scheduling problem (NSP). The restriction of EA is discussed and thus, enhancement on the EA operators is suggested so that the EA would have the characteristic of a flexible search. This paper consists of three types of constraints which are the hard, semi-hard and soft constraints that can be handled by the EA with enhanced parent selection and specialized mutation operators. These operators and EA as a whole contribute to the efficiency of constraint handling, fitness computation as well as flexibility in the search, which correspond to the employment of exploration and exploitation principles.
More reliable protein NMR peak assignment via improved 2-interval scheduling.

PubMed

Chen, Zhi-Zhong; Lin, Guohui; Rizzi, Romeo; Wen, Jianjun; Xu, Dong; Xu, Ying; Jiang, Tao

2005-03-01

Protein NMR peak assignment refers to the process of assigning a group of "spin systems" obtained experimentally to a protein sequence of amino acids. The automation of this process is still an unsolved and challenging problem in NMR protein structure determination. Recently, protein NMR peak assignment has been formulated as an interval scheduling problem (ISP), where a protein sequence P of amino acids is viewed as a discrete time interval I (the amino acids on P one-to-one correspond to the time units of I), each subset S of spin systems that are known to originate from consecutive amino acids from P is viewed as a "job" j(s), the preference of assigning S to a subsequence P of consecutive amino acids on P is viewed as the profit of executing job j(s) in the subinterval of I corresponding to P, and the goal is to maximize the total profit of executing the jobs (on a single machine) during I. The interval scheduling problem is max SNP-hard in general; but in the real practice of protein NMR peak assignment, each job j(s) usually requires at most 10 consecutive time units, and typically the jobs that require one or two consecutive time units are the most difficult to assign/schedule. In order to solve these most difficult assignments, we present an efficient 13/7-approximation algorithm for the special case of the interval scheduling problem where each job takes one or two consecutive time units. Combining this algorithm with a greedy filtering strategy for handling long jobs (i.e., jobs that need more than two consecutive time units), we obtain a new efficient heuristic for protein NMR peak assignment. Our experimental study shows that the new heuristic produces the best peak assignment in most of the cases, compared with the NMR peak assignment algorithms in the recent literature. The above algorithm is also the first approximation algorithm for a nontrivial case of the well-known interval scheduling problem that breaks the ratio 2 barrier.
Intelligent Planning and Scheduling for Controlled Life Support Systems

NASA Technical Reports Server (NTRS)

Leon, V. Jorge

1996-01-01

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

PubMed

Kim, Sungmin; Eo, Hae-Seok; Koo, Hyeyoung; Choi, Jun-Kil; Kim, Won

2010-12-01

In this study, we applied DNA barcoding to identify species using short DNA sequence analysis. We examined the utility of DNA barcoding by identifying 53 Korean freshwater fish species, 233 other freshwater fish species, and 1339 saltwater fish species. We successfully developed a web-based molecular identification system for fish (MISF) using a profile hidden Markov model. MISF facilitates efficient and reliable species identification, overcoming the limitations of conventional taxonomic approaches. MISF is freely accessible at http://bioinfosys.snu.ac.kr:8080/MISF/misf.jsp .
Balancing Act: Synergy of Combat Airpower Functions

DTIC Science & Technology

2011-06-01

man, army, or power writ large. In its simplest form, a fighting man should have his sword, his shield, and his legs . These are what give him his...some point later in their careers.15 However, for Sir John Slessor, the only path to military service was through aviation, as his legs were infirm...www.aviationweek.com/aw/generic/story_channel.jsp?channel=defense&id=new s/ dti /2011/04/01/DT_04_01_2011_p38- 297236.xml&headline=U.S.%20Wants%20COIN
VizieR Online Data Catalog: Algorithm for correcting CoRoT raw light curves (Mislis+, 2010)

NASA Astrophysics Data System (ADS)

Mislis, D.; Schmitt, J. H. M. M.; Carone, L.; Guenther, E. W.; Patzold, M.

2010-10-01

Requirements : gfortran (or g77, ifort) compiler Input Files : The input files sould be raw CoRoT txt files (http://idoc-corot.ias.u-psud.fr/index.jsp) with names CoRoT*.txt Run the cda by typing C>: ./cda.csh (code and data sould be in the same directory) Output files : CDA creates one ascii output file with name - CoRoT*.R.cor for R filter (2 data files).
National Medal of Science

NASA Astrophysics Data System (ADS)

Wendel, JoAnna

2014-04-01

The nation's highest honor for American scientists and engineers, the National Medal of Science is awarded annually by the president of the United States to individuals who have made outstanding contributions to or for the total impact of their work on the current state of chemical, physical, biological, social or behavioral sciences; mathematics; or engineering. Anyone can submit a nomination. Submit a short description of the nominee's contribution and three letters of support to http://www.nsf.gov/od/nms/medal.jsp by 1 May 2014.
Definition and Measurement of Complexity in the Context of Safety Assurance

DTIC Science & Technology

2016-11-01

design for each sys- tem and on a larger design from a NASA report. The complexity measurement must be matched to available review time to determine...ARP4754A to Flight Critical Systems.” NASA , 2015. http://ntrs.nasa.gov/search.jsp?R=20160001634 [Rayner 2016] Rayner, Keith; Schotter, Elizabeth R...systems. We tested it on a second design for each system and on a larger design from a NASA report. The complexity measurement must be matched to
Manufacturing Technology Support (MATES). Task Order 0021: Air Force Technology and Industrial Base Research and Analysis, Subtask Order 06: Direct Digital Manufacturing

DTIC Science & Technology

2011-08-01

industries and key players providing equipment include Flow and OMAX. The decision tree for waterjet machining is shown in Figure 28. Figure 28...about the melt pool. Process parameters including powder flow , laser power, and scan speed are adjusted accordingly • Multiple materials o BD...project.eu.com/home/home_page_static.jsp o Working with multiple partners; one is Cochlear . Using LMD or SLM to fabricate cochlear implants with 10
The New Wizard War: Challenges and Opportunities for Electronic Warfare in the Information Age

DTIC Science & Technology

2007-11-06

Camp: Preparing for Conflict in the Information Age (Santa Monica, CA: RAND Corporation, 1997):175. 17. Jeffrey R . Cares, “An Information Age Combat...60. Stephen Trimble, “US Army Moves Back Into Electronic Attack Mission.” 61. Richard R . Burgess, “Jamming: The Marine Corps Refines Its Vision of...November 7, 2005), http://www.aviationweek.com/aw/generic/story_generic.jsp?channel= awst &id=news/11075p 2.xml (accessed 29 Oct 07). 74. David A
2035 Air Dominance Requirements for State-On-State Conflict

DTIC Science & Technology

2011-02-16

story.jsp?id=news/ awst /2011/01/10/AW_01_10_ 2011_p58-280833.xml&channel=misc (accessed 3 Jan 2011). Bilbro, James. “Technology Readiness Levels.” JB...channel = awst &id =news/aw121508p2.xml&headline=null&prev=10. (accessed 3 January 2011). Global Security.org. “Miniature Air-Launched Decoy (MALD...Battle.” Center for Strategic and Budgetary Assessment, http://www.csba online.com/4Publications/PubLibrary/ R .20100518.Slides_AirSea_Batt/ R .20100518
The Future of the Fighter Pilot ... Will There Be a 6th Generation Fighter?

DTIC Science & Technology

2012-02-02

tndudtng suggestioos lor r &ducing this burden to Washington Headquarters Service, Directorate ror Information Operations and Reports, 1215 Jefferson DaviS...replacement. 22 The concept of spreading R &D risk in this manner at the same time as pre-signing a wide number of future customers was designed to...aviationweek.com/aw/generic/story_channel.jsp ?channel=Defense &id=news/ awst /2011/03/21/AW_03 _21_2011_p27297530.xml&headline=null&next=20>. 33 Ibid
Controle du vol longitudinal d'un avion civil avec satisfaction de qualiies de manoeuvrabilite

NASA Astrophysics Data System (ADS)

Saussie, David Alexandre

2010-03-01

Fulfilling handling qualities still remains a challenging problem during flight control design. These criteria of different nature are derived from a wide experience based upon flight tests and data analysis, and they have to be considered if one expects a good behaviour of the aircraft. The goal of this thesis is to develop synthesis methods able to satisfy these criteria with fixed classical architectures imposed by the manufacturer or with a new flight control architecture. This is applied to the longitudinal flight model of a Bombardier Inc. business jet aircraft, namely the Challenger 604. A first step of our work consists in compiling the most commonly used handling qualities in order to compare them. A special attention is devoted to the dropback criterion for which theoretical analysis leads us to establish a practical formulation for synthesis purpose. Moreover, the comparison of the criteria through a reference model highlighted dominant criteria that, once satisfied, ensure that other ones are satisfied too. Consequently, we are able to consider the fulfillment of these criteria in the fixed control architecture framework. Guardian maps (Saydy et al., 1990) are then considered to handle the problem. Initially for robustness study, they are integrated in various algorithms for controller synthesis. Incidently, this fixed architecture problem is similar to the static output feedback stabilization problem and reduced-order controller synthesis. Algorithms performing stabilization and pole assignment in a specific region of the complex plane are then proposed. Afterwards, they are extended to handle the gain-scheduling problem. The controller is then scheduled through the entire flight envelope with respect to scheduling parameters. Thereafter, the fixed architecture is put aside while only conserving the same output signals. The main idea is to use Hinfinity synthesis to obtain an initial controller satisfying handling qualities thanks to reference model pairing and robust versus mass and center of gravity variations. Using robust modal control (Magni, 2002), we are able to reduce substantially the controller order and to structure it in order to come close to a classical architecture. An auto-scheduling method finally allows us to schedule the controller with respect to scheduling parameters. Two different paths are used to solve the same problem; each one exhibits its own advantages and disadvantages.
Optimizing Department of Defense Acquisition Development Test and Evaluation Scheduling

DTIC Science & Technology

2015-06-01

CPM Critical Path Method DOD Department of Defense DT&E development test and evaluation EMD engineering and manufacturing development GAMS...these, including the Program Evaluation Review Technique (PERT), the Critical Path Method ( CPM ), and the resource- constrained project-scheduling...problem (RCPSP). These are of particular interest to this thesis as the current scheduling method uses elements of the PERT/ CPM , and the test
A Mechanized Decision Support System for Academic Scheduling.

DTIC Science & Technology

1986-03-01

an operational system called software. The first step in the development phase is Design . Designers destribute software control by factoring the Data...SUBJECT TERMS (Continue on reverse if necessary and identify by block number) ELD GROUP SUB-GROUP Scheduling, Decision Support System , Software Design ...scheduling system . It will also examine software - design techniques to identify the most appropriate method- ology for this problem. " - Chapter 3 will
Scheduling language and algorithm development study. Volume 2: Use of the basic language and module library

NASA Technical Reports Server (NTRS)

Chamberlain, R. A.; Cornick, D. E.; Flater, J. F.; Odoherty, R. J.; Peterson, F. M.; Ramsey, H. R.; Willoughby, J. K.

1974-01-01

The capabilities of the specified scheduling language and the program module library are outlined. The summary is written with the potential user in mind and, therefore, provides maximum insight on how the capabilities will be helpful in writing scheduling programs. Simple examples and illustrations are provided to assist the potential user in applying the capabilities of his problem.
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.

Advance Resource Provisioning in Bulk Data Scheduling

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

Balman, Mehmet

2012-10-01

Today?s scientific and business applications generate mas- sive data sets that need to be transferred to remote sites for sharing, processing, and long term storage. Because of increasing data volumes and enhancement in current net- work technology that provide on-demand high-speed data access between collaborating institutions, data handling and scheduling problems have reached a new scale. In this paper, we present a new data scheduling model with ad- vance resource provisioning, in which data movement operations are defined with earliest start and latest comple- tion times. We analyze time-dependent resource assign- ment problem, and propose a new methodology to improvemore » the current systems by allowing researchers and higher-level meta-schedulers to use data-placement as-a-service, so they can plan ahead and submit transfer requests in advance. In general, scheduling with time and resource conflicts is NP-hard. We introduce an efficient algorithm to organize multiple requests on the fly, while satisfying users? time and resource constraints. We successfully tested our algorithm in a simple benchmark simulator that we have developed, and demonstrated its performance with initial test results.« less
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.
Applying Squeaky-Wheel Optimization Schedule Airborne Astronomy Observations

NASA Technical Reports Server (NTRS)

Frank, Jeremy; Kuerklue, Elif

2004-01-01

We apply the Squeaky Wheel Optimization (SWO) algorithm to the problem of scheduling astronomy observations for the Stratospheric Observatory for Infrared Astronomy, an airborne observatory. The problem contains complex constraints relating the feasibility of an astronomical observation to the position and time at which the observation begins, telescope elevation limits, special use airspace, and available fuel. Solving the problem requires making discrete choices (e.g. selection and sequencing of observations) and continuous ones (e.g. takeoff time and setting up observations by repositioning the aircraft). The problem also includes optimization criteria such as maximizing observing time while simultaneously minimizing total flight time. Previous approaches to the problem fail to scale when accounting for all constraints. We describe how to customize SWO to solve this problem, and show that it finds better flight plans, often with less computation time, than previous approaches.
Run-time scheduling and execution of loops on message passing machines

NASA Technical Reports Server (NTRS)

Crowley, Kay; Saltz, Joel; Mirchandaney, Ravi; Berryman, Harry

1989-01-01

Sparse system solvers and general purpose codes for solving partial differential equations are examples of the many types of problems whose irregularity can result in poor performance on distributed memory machines. Often, the data structures used in these problems are very flexible. Crucial details concerning loop dependences are encoded in these structures rather than being explicitly represented in the program. Good methods for parallelizing and partitioning these types of problems require assignment of computations in rather arbitrary ways. Naive implementations of programs on distributed memory machines requiring general loop partitions can be extremely inefficient. Instead, the scheduling mechanism needs to capture the data reference patterns of the loops in order to partition the problem. First, the indices assigned to each processor must be locally numbered. Next, it is necessary to precompute what information is needed by each processor at various points in the computation. The precomputed information is then used to generate an execution template designed to carry out the computation, communication, and partitioning of data, in an optimized manner. The design is presented for a general preprocessor and schedule executer, the structures of which do not vary, even though the details of the computation and of the type of information are problem dependent.
Run-time scheduling and execution of loops on message passing machines

NASA Technical Reports Server (NTRS)

Saltz, Joel; Crowley, Kathleen; Mirchandaney, Ravi; Berryman, Harry

1990-01-01

Sparse system solvers and general purpose codes for solving partial differential equations are examples of the many types of problems whose irregularity can result in poor performance on distributed memory machines. Often, the data structures used in these problems are very flexible. Crucial details concerning loop dependences are encoded in these structures rather than being explicitly represented in the program. Good methods for parallelizing and partitioning these types of problems require assignment of computations in rather arbitrary ways. Naive implementations of programs on distributed memory machines requiring general loop partitions can be extremely inefficient. Instead, the scheduling mechanism needs to capture the data reference patterns of the loops in order to partition the problem. First, the indices assigned to each processor must be locally numbered. Next, it is necessary to precompute what information is needed by each processor at various points in the computation. The precomputed information is then used to generate an execution template designed to carry out the computation, communication, and partitioning of data, in an optimized manner. The design is presented for a general preprocessor and schedule executer, the structures of which do not vary, even though the details of the computation and of the type of information are problem dependent.
A neural network approach to job-shop scheduling.

PubMed

Zhou, D N; Cherkassky, V; Baldwin, T R; Olson, D E

1991-01-01

A novel analog computational network is presented for solving NP-complete constraint satisfaction problems, i.e. job-shop scheduling. In contrast to most neural approaches to combinatorial optimization based on quadratic energy cost function, the authors propose to use linear cost functions. As a result, the network complexity (number of neurons and the number of resistive interconnections) grows only linearly with problem size, and large-scale implementations become possible. The proposed approach is related to the linear programming network described by D.W. Tank and J.J. Hopfield (1985), which also uses a linear cost function for a simple optimization problem. It is shown how to map a difficult constraint-satisfaction problem onto a simple neural net in which the number of neural processors equals the number of subjobs (operations) and the number of interconnections grows linearly with the total number of operations. Simulations show that the authors' approach produces better solutions than existing neural approaches to job-shop scheduling, i.e. the traveling salesman problem-type Hopfield approach and integer linear programming approach of J.P.S. Foo and Y. Takefuji (1988), in terms of the quality of the solution and the network complexity.
A Two-Stage Stochastic Mixed-Integer Programming Approach to the Smart House Scheduling Problem

NASA Astrophysics Data System (ADS)

Ozoe, Shunsuke; Tanaka, Yoichi; Fukushima, Masao

A “Smart House” is a highly energy-optimized house equipped with photovoltaic systems (PV systems), electric battery systems, fuel cell cogeneration systems (FC systems), electric vehicles (EVs) and so on. Smart houses are attracting much attention recently thanks to their enhanced ability to save energy by making full use of renewable energy and by achieving power grid stability despite an increased power draw for installed PV systems. Yet running a smart house's power system, with its multiple power sources and power storages, is no simple task. In this paper, we consider the problem of power scheduling for a smart house with a PV system, an FC system and an EV. We formulate the problem as a mixed integer programming problem, and then extend it to a stochastic programming problem involving recourse costs to cope with uncertain electricity demand, heat demand and PV power generation. Using our method, we seek to achieve the optimal power schedule running at the minimum expected operation cost. We present some results of numerical experiments with data on real-life demands and PV power generation to show the effectiveness of our method.
Deconstructing Nowicki and Smutnickis i-TSAB tabu search algorithm for the job-shop scheduling problem.

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

Whitley, L. Darrell; Watson, Jean-Paul; Howe, Adele E.

Over the last decade and a half, tabu search algorithms for machine scheduling have gained a near-mythical reputation by consistently equaling or establishing state-of-the-art performance levels on a range of academic and real-world problems. Yet, despite these successes, remarkably little research has been devoted to developing an understanding of why tabu search is so effective on this problem class. In this paper, we report results that provide significant progress in this direction. We consider Nowicki and Smutnicki's i-TSAB tabu search algorithm, which represents the current state-of-the-art for the makespan-minimization form of the classical jobshop scheduling problem. Via a series ofmore » controlled experiments, we identify those components of i-TSAB that enable it to achieve state-of-the-art performance levels. In doing so, we expose a number of misconceptions regarding the behavior and/or benefits of tabu search and other local search metaheuristics for the job-shop problem. Our results also serve to focus future research, by identifying those specific directions that are most likely to yield further improvements in performance.« less
Generating effective project scheduling heuristics by abstraction and reconstitution

NASA Technical Reports Server (NTRS)

Janakiraman, Bhaskar; Prieditis, Armand

1992-01-01

A project scheduling problem consists of a finite set of jobs, each with fixed integer duration, requiring one or more resources such as personnel or equipment, and each subject to a set of precedence relations, which specify allowable job orderings, and a set of mutual exclusion relations, which specify jobs that cannot overlap. No job can be interrupted once started. The objective is to minimize project duration. This objective arises in nearly every large construction project--from software to hardware to buildings. Because such project scheduling problems are NP-hard, they are typically solved by branch-and-bound algorithms. In these algorithms, lower-bound duration estimates (admissible heuristics) are used to improve efficiency. One way to obtain an admissible heuristic is to remove (abstract) all resources and mutual exclusion constraints and then obtain the minimal project duration for the abstracted problem; this minimal duration is the admissible heuristic. Although such abstracted problems can be solved efficiently, they yield inaccurate admissible heuristics precisely because those constraints that are central to solving the original problem are abstracted. This paper describes a method to reconstitute the abstracted constraints back into the solution to the abstracted problem while maintaining efficiency, thereby generating better admissible heuristics. Our results suggest that reconstitution can make good admissible heuristics even better.
Cooperative Scheduling of Imaging Observation Tasks for High-Altitude Airships Based on Propagation Algorithm

PubMed Central

Chuan, He; Dishan, Qiu; Jin, Liu

2012-01-01

The cooperative scheduling problem on high-altitude airships for imaging observation tasks is discussed. A constraint programming model is established by analyzing the main constraints, which takes the maximum task benefit and the minimum cruising distance as two optimization objectives. The cooperative scheduling problem of high-altitude airships is converted into a main problem and a subproblem by adopting hierarchy architecture. The solution to the main problem can construct the preliminary matching between tasks and observation resource in order to reduce the search space of the original problem. Furthermore, the solution to the sub-problem can detect the key nodes that each airship needs to fly through in sequence, so as to get the cruising path. Firstly, the task set is divided by using k-core neighborhood growth cluster algorithm (K-NGCA). Then, a novel swarm intelligence algorithm named propagation algorithm (PA) is combined with the key node search algorithm (KNSA) to optimize the cruising path of each airship and determine the execution time interval of each task. Meanwhile, this paper also provides the realization approach of the above algorithm and especially makes a detailed introduction on the encoding rules, search models, and propagation mechanism of the PA. Finally, the application results and comparison analysis show the proposed models and algorithms are effective and feasible. PMID:23365522
A bi-objective integer programming model for partly-restricted flight departure scheduling

PubMed Central

Guan, Wei; Zhang, Wenyi; Jiang, Shixiong; Fan, Lingling

2018-01-01

The normal studies on air traffic departure scheduling problem (DSP) mainly deal with an independent airport in which the departure traffic is not affected by surrounded airports, which, however, is not a consistent case. In reality, there still exist cases where several commercial airports are closely located and one of them possesses a higher priority. During the peak hours, the departure activities of the lower-priority airports are usually required to give way to those of higher-priority airport. These giving-way requirements can inflict a set of changes on the modeling of departure scheduling problem with respect to the lower-priority airports. To the best of our knowledge, studies on DSP under this condition are scarce. Accordingly, this paper develops a bi-objective integer programming model to address the flight departure scheduling of the partly-restricted (e.g., lower-priority) one among several adjacent airports. An adapted tabu search algorithm is designed to solve the current problem. It is demonstrated from the case study of Tianjin Binhai International Airport in China that the proposed method can obviously improve the operation efficiency, while still realizing superior equity and regularity among restricted flows. PMID:29715299
A bi-objective integer programming model for partly-restricted flight departure scheduling.

PubMed

Zhong, Han; Guan, Wei; Zhang, Wenyi; Jiang, Shixiong; Fan, Lingling

2018-01-01

The normal studies on air traffic departure scheduling problem (DSP) mainly deal with an independent airport in which the departure traffic is not affected by surrounded airports, which, however, is not a consistent case. In reality, there still exist cases where several commercial airports are closely located and one of them possesses a higher priority. During the peak hours, the departure activities of the lower-priority airports are usually required to give way to those of higher-priority airport. These giving-way requirements can inflict a set of changes on the modeling of departure scheduling problem with respect to the lower-priority airports. To the best of our knowledge, studies on DSP under this condition are scarce. Accordingly, this paper develops a bi-objective integer programming model to address the flight departure scheduling of the partly-restricted (e.g., lower-priority) one among several adjacent airports. An adapted tabu search algorithm is designed to solve the current problem. It is demonstrated from the case study of Tianjin Binhai International Airport in China that the proposed method can obviously improve the operation efficiency, while still realizing superior equity and regularity among restricted flows.
Optimization of municipal waste collection scheduling and routing using vehicle assignment problem (case study of Surabaya city waste collection)

NASA Astrophysics Data System (ADS)

Ramdhani, M. N.; Baihaqi, I.; Siswanto, N.

2018-04-01

Waste collection and disposal become a major problem for many metropolitan cities. Growing population, limited vehicles, and increased road traffic make the waste transportation become more complex. Waste collection involves some key considerations, such as vehicle assignment, vehicle routes, and vehicle scheduling. In the scheduling process, each vehicle has a scheduled departure that serve each route. Therefore, vehicle’s assignments should consider the time required to finish one assigment on that route. The objective of this study is to minimize the number of vehicles needed to serve all routes by developing a mathematical model which uses assignment problem approach. The first step is to generated possible routes from the existing routes, followed by vehicle assignments for those certain routes. The result of the model shows fewer vehicles required to perform waste collection asa well as the the number of journeys that the vehicle to collect the waste to the landfill. The comparison of existing conditions with the model result indicates that the latter’s has better condition than the existing condition because each vehicle with certain route has an equal workload, all the result’s model has the maximum of two journeys for each route.
Flexible Job-Shop Scheduling with Dual-Resource Constraints to Minimize Tardiness Using Genetic Algorithm

NASA Astrophysics Data System (ADS)

Paksi, A. B. N.; Ma'ruf, A.

2016-02-01

In general, both machines and human resources are needed for processing a job on production floor. However, most classical scheduling problems have ignored the possible constraint caused by availability of workers and have considered only machines as a limited resource. In addition, along with production technology development, routing flexibility appears as a consequence of high product variety and medium demand for each product. Routing flexibility is caused by capability of machines that offers more than one machining process. This paper presents a method to address scheduling problem constrained by both machines and workers, considering routing flexibility. Scheduling in a Dual-Resource Constrained shop is categorized as NP-hard problem that needs long computational time. Meta-heuristic approach, based on Genetic Algorithm, is used due to its practical implementation in industry. Developed Genetic Algorithm uses indirect chromosome representative and procedure to transform chromosome into Gantt chart. Genetic operators, namely selection, elitism, crossover, and mutation are developed to search the best fitness value until steady state condition is achieved. A case study in a manufacturing SME is used to minimize tardiness as objective function. The algorithm has shown 25.6% reduction of tardiness, equal to 43.5 hours.
A software tool for dataflow graph scheduling

NASA Technical Reports Server (NTRS)

Jones, Robert L., III

1994-01-01

A graph-theoretic design process and software tool is presented for selecting a multiprocessing scheduling solution for a class of computational problems. The problems of interest are those that can be described using a dataflow graph and are intended to be executed repetitively on multiple processors. The dataflow paradigm is very useful in exposing the parallelism inherent in algorithms. It provides a graphical and mathematical model which describes a partial ordering of algorithm tasks based on data precedence.
Scheduling periodic jobs using imprecise results

NASA Technical Reports Server (NTRS)

Chung, Jen-Yao; Liu, Jane W. S.; Lin, Kwei-Jay

1987-01-01

One approach to avoid timing faults in hard, real-time systems is to make available intermediate, imprecise results produced by real-time processes. When a result of the desired quality cannot be produced in time, an imprecise result of acceptable quality produced before the deadline can be used. The problem of scheduling periodic jobs to meet deadlines on a system that provides the necessary programming language primitives and run-time support for processes to return imprecise results is discussed. Since the scheduler may choose to terminate a task before it is completed, causing it to produce an acceptable but imprecise result, the amount of processor time assigned to any task in a valid schedule can be less than the amount of time required to complete the task. A meaningful formulation of the scheduling problem must take into account the overall quality of the results. Depending on the different types of undesirable effects caused by errors, jobs are classified as type N or type C. For type N jobs, the effects of errors in results produced in different periods are not cumulative. A reasonable performance measure is the average error over all jobs. Three heuristic algorithms that lead to feasible schedules with small average errors are described. For type C jobs, the undesirable effects of errors produced in different periods are cumulative. Schedulability criteria of type C jobs are discussed.
An Improved Hierarchical Genetic Algorithm for Sheet Cutting Scheduling with Process Constraints

PubMed Central

Rao, Yunqing; Qi, Dezhong; Li, Jinling

2013-01-01

For the first time, an improved hierarchical genetic algorithm for sheet cutting problem which involves n cutting patterns for m non-identical parallel machines with process constraints has been proposed in the integrated cutting stock model. The objective of the cutting scheduling problem is minimizing the weighted completed time. A mathematical model for this problem is presented, an improved hierarchical genetic algorithm (ant colony—hierarchical genetic algorithm) is developed for better solution, and a hierarchical coding method is used based on the characteristics of the problem. Furthermore, to speed up convergence rates and resolve local convergence issues, a kind of adaptive crossover probability and mutation probability is used in this algorithm. The computational result and comparison prove that the presented approach is quite effective for the considered problem. PMID:24489491
Asymptotic analysis of online algorithms and improved scheme for the flow shop scheduling problem with release dates

NASA Astrophysics Data System (ADS)

Bai, Danyu

2015-08-01

This paper discusses the flow shop scheduling problem to minimise the total quadratic completion time (TQCT) with release dates in offline and online environments. For this NP-hard problem, the investigation is focused on the performance of two online algorithms based on the Shortest Processing Time among Available jobs rule. Theoretical results indicate the asymptotic optimality of the algorithms as the problem scale is sufficiently large. To further enhance the quality of the original solutions, the improvement scheme is provided for these algorithms. A new lower bound with performance guarantee is provided, and computational experiments show the effectiveness of these heuristics. Moreover, several results of the single-machine TQCT problem with release dates are also obtained for the deduction of the main theorem.
An improved hierarchical genetic algorithm for sheet cutting scheduling with process constraints.

PubMed

Rao, Yunqing; Qi, Dezhong; Li, Jinling

2013-01-01

For the first time, an improved hierarchical genetic algorithm for sheet cutting problem which involves n cutting patterns for m non-identical parallel machines with process constraints has been proposed in the integrated cutting stock model. The objective of the cutting scheduling problem is minimizing the weighted completed time. A mathematical model for this problem is presented, an improved hierarchical genetic algorithm (ant colony--hierarchical genetic algorithm) is developed for better solution, and a hierarchical coding method is used based on the characteristics of the problem. Furthermore, to speed up convergence rates and resolve local convergence issues, a kind of adaptive crossover probability and mutation probability is used in this algorithm. The computational result and comparison prove that the presented approach is quite effective for the considered problem.
Space communications scheduler: A rule-based approach to adaptive deadline scheduling

NASA Technical Reports Server (NTRS)

Straguzzi, Nicholas

1990-01-01

Job scheduling is a deceptively complex subfield of computer science. The highly combinatorial nature of the problem, which is NP-complete in nearly all cases, requires a scheduling program to intelligently transverse an immense search tree to create the best possible schedule in a minimal amount of time. In addition, the program must continually make adjustments to the initial schedule when faced with last-minute user requests, cancellations, unexpected device failures, quests, cancellations, unexpected device failures, etc. A good scheduler must be quick, flexible, and efficient, even at the expense of generating slightly less-than-optimal schedules. The Space Communication Scheduler (SCS) is an intelligent rule-based scheduling system. SCS is an adaptive deadline scheduler which allocates modular communications resources to meet an ordered set of user-specified job requests on board the NASA Space Station. SCS uses pattern matching techniques to detect potential conflicts through algorithmic and heuristic means. As a result, the system generates and maintains high density schedules without relying heavily on backtracking or blind search techniques. SCS is suitable for many common real-world applications.

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