Relevant bibliographies by topics / Static scheduling problems

Academic literature on the topic 'Static scheduling problems'

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Published: 10 December 2022
Last updated: 28 January 2023

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Journal articles on the topic "Static scheduling problems"

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Ma, Yuliang, Yinghua Han, Jinkuan Wang, and Qiang Zhao. "A Constrained Static Scheduling Strategy in Edge Computing for Industrial Cloud Systems." International Journal of Information Technologies and Systems Approach 14, no. 1 (January 2021): 33–61. http://dx.doi.org/10.4018/ijitsa.2021010103.

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With the development of industrial internet, attention has been paid for edge computing due to the low latency. However, some problems remain about the task scheduling and resource management. In this paper, an edge computing supported industrial cloud system is investigated. According to the system, a constrained static scheduling strategy is proposed to over the deficiency of dynamic scheduling. The strategy is divided into the following steps. Firstly, the queue theory is introduced to calculate the expectations of task completion time. Thereupon, the task scheduling and resource management problems are formulated and turned into an integer non-linear programming (INLP) problem. Then, tasks that can be scheduled statically are selected based on the expectation of task completion and constrains of various aspects of task. Finally, a multi-elites-based co-evolutionary genetic algorithm (MEB-CGA) is proposed to solve the INLP problem. Simulation result shows that the MEB-CGA significantly outperforms the scheduling quality of greedy algorithm.
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Kämpke, Thomas. "Necessary optimality conditions for priority policies in stochastic weighted flowtime scheduling problems." Advances in Applied Probability 19, no. 3 (September 1987): 749–50. http://dx.doi.org/10.2307/1427418.

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Kämpke, Thomas. "Necessary optimality conditions for priority policies in stochastic weighted flowtime scheduling problems." Advances in Applied Probability 19, no. 03 (September 1987): 749–50. http://dx.doi.org/10.1017/s0001867800016876.

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Sharma, Manik, and Smriti Smriti. "STATIC AND DYNAMIC BNP PARALLEL SCHEDULING ALGORITHMS FOR DISTRIBUTED DATABASE." INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY 1, no. 1 (December 30, 2011): 10–15. http://dx.doi.org/10.24297/ijct.v1i1.2601.

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Parallel processing is a technique of executing the multiple tasksconcurrently on different processors. Parallel processing is usedto solve the complex problems that require vast amount ofprocessing time. Task scheduling is one of the major problemsof parallel processing. The objective of this study is to analyzethe performance of static (HLFET) and dynamic (DLS) BNPparallel scheduling algorithm for allocating the tasks ofdistributed database over number of processors. In the wholestudy the focus will be given on measuring the impact ofnumber of processors on different metrics of performance likemakespan, speed up and processor utilization by using HLFETand DLS BNP task scheduling algorithms.
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Terekhov, Daria, Tony Tran, Douglas Down, and J. Christopher Beck. "Long-Run Stability in Dynamic Scheduling." Proceedings of the International Conference on Automated Planning and Scheduling 22 (May 14, 2012): 261–69. http://dx.doi.org/10.1609/icaps.v22i1.13524.

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Stability analysis consists of identifying conditions under which the number of jobs in a system is guaranteed to remain bounded over time. To date, such long-run performance guarantees have not been available for periodic approaches to dynamic scheduling problems. However, stability has been extensively studied in queueing theory. In this paper, we introduce stability to the dynamic scheduling literature and demonstrate that stability guarantees can be obtained for methods that build the schedule for a dynamic problem by periodically solving static deterministic sub-problems. Specifically, we analyze the stability of two dynamic environments: a two-machine flow shop, which has received significant attention in scheduling research, and a polling system with a flow-shop server, an extension of systems typically considered in queueing. We demonstrate that, among stable policies, methods based on periodic optimization of static schedules may achieve better mean flow times than traditional queueing approaches.
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Hui, Ji Zhuang, Xiang Ding, and Kai Gao. "A FMS Dynamic Scheduling Optimization Strategy and Simulation Research." Applied Mechanics and Materials 389 (August 2013): 692–97. http://dx.doi.org/10.4028/www.scientific.net/amm.389.692.

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This paper studied the FMS dynamic scheduling problem which was based on Petri net FMS static scheduling optimization algorithm, which in accorder to solve the FMS actual production scheduling problems. A rolling window dynamic re-scheduling strategy was proposed which based on event driven and cycle driven. Then take the emergency machine failure often appearing in the actual workshop for example, this scheduling strategy was analyzed and applied to dynamic simulation and finally the effectiveness of the dynamic scheduling strategy was verified.
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Yu, Bin, Keming Wang, Can Wang, and Baozhen Yao. "Ship scheduling problems in tramp shipping considering static and spot cargoes." International Journal of Shipping and Transport Logistics 9, no. 4 (2017): 391. http://dx.doi.org/10.1504/ijstl.2017.084825.

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Yao, Baozhen, Can Wang, Keming Wang, and Bin Yu. "Ship scheduling problems in tramp shipping considering static and spot cargoes." International Journal of Shipping and Transport Logistics 9, no. 4 (2017): 391. http://dx.doi.org/10.1504/ijstl.2017.10005461.

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Hart, Emma, and Kevin Sim. "A Hyper-Heuristic Ensemble Method for Static Job-Shop Scheduling." Evolutionary Computation 24, no. 4 (December 2016): 609–35. http://dx.doi.org/10.1162/evco_a_00183.

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We describe a new hyper-heuristic method NELLI-GP for solving job-shop scheduling problems (JSSP) that evolves an ensemble of heuristics. The ensemble adopts a divide-and-conquer approach in which each heuristic solves a unique subset of the instance set considered. NELLI-GP extends an existing ensemble method called NELLI by introducing a novel heuristic generator that evolves heuristics composed of linear sequences of dispatching rules: each rule is represented using a tree structure and is itself evolved. Following a training period, the ensemble is shown to outperform both existing dispatching rules and a standard genetic programming algorithm on a large set of new test instances. In addition, it obtains superior results on a set of 210 benchmark problems from the literature when compared to two state-of-the-art hyper-heuristic approaches. Further analysis of the relationship between heuristics in the evolved ensemble and the instances each solves provides new insights into features that might describe similar instances.
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Boutekkouk, Fateh. "Real Time Scheduling Optimization." Journal of Information Technology Research 12, no. 4 (October 2019): 132–52. http://dx.doi.org/10.4018/jitr.2019100107.

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This article deals with real time embedded multiprocessor systems scheduling optimization using conventional and quantum inspired genetic algorithms. Real time scheduling problems are known to be NP-hard. In order to resolve it, researchers have resorted to meta-heuristics instead of exact methods. Genetic algorithms seem to be a good choice to solve complex, non-linear, multi-objective and multi-modal problems. However, conventional genetic algorithms may consume much time to find good solutions. For this reason, to minimize the mean response time and the number of tasks missing their deadlines using quantum inspired genetic algorithms for multiprocessors architectures. Our proposed approach takes advantage of both static and dynamic preemptive scheduling. This article has the developed algorithms on a typical example showing a big improvement in research time of good solutions in quantum genetic algorithms with comparison to conventional ones.
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Dissertations / Theses on the topic "Static scheduling problems"

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Rusanova, Olga, Alexander Korochkin, and Oleg Shevelo. "Scheduling problems for mobile cloud computing." Thesis, National aviation university, 2021. https://er.nau.edu.ua/handle/NAU/50689.

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Nowadays the popularity of mobile devices is rapidly increased. New facilities of them (Wi-Fi, GPS, high speed processors etc.) allows to improve mobile applications in commerce, learning, gaming, health monitoring, sports etc. But really there are several reasons that limit mobile computing: limited storage capacity, limited battery life and limited processing power of mobile devices. This paper is dedicated to Mobile cloud computing (MCC). We consider MCC as combination of mobile and cloud computing where both data storage and data processing are performed outside the mobile device but inside the cloud.
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Guericke, Daniela [Verfasser]. "Routing and scheduling for home care services : solution approaches for static and dynamic settings / Daniela Guericke." Paderborn : Universitätsbibliothek, 2016. http://d-nb.info/1111627932/34.

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Yeleswarapu, Radhika M. "Scheduling Of 2-Operation Jobs On A Single Machine To Minimize The Number Of Tardy Jobs." [Tampa, Fla.] : University of South Florida, 2003. http://purl.fcla.edu/fcla/etd/SFE0000216.

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Books on the topic "Static scheduling problems"

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L, Dolce James, Krupp Joseph C, and United States. National Aeronautics and Space Administration., eds. Electric power scheduling: A distributed problem-solving approach. [Washington, D.C.]: NASA, 1990.

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Eva Maich, Katherine, Jamie K. McCallum, and Ari Grant-Sasson. Time’s Up! Shorter Hours, Public Policy, and Time Flexibility as an Antidote to Youth Unemployment. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780190685898.003.0011.

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This chapter explores the relationship between hours of work and unemployment. When it comes to time spent working in the United States at present, two problems immediately come to light. First, an asymmetrical distribution of working time persists, with some people overworked and others underemployed. Second, hours are increasingly unstable; precarious on-call work scheduling and gig economy–style employment relationships are the canaries in the coal mine of a labor market that produces fewer and fewer stable jobs. It is possible that some kind of shorter hours movement, especially one that places an emphasis on young workers, has the potential to address these problems. Some policies and processes are already in place to transition into a shorter hours economy right now even if those possibilities are mediated by an anti-worker political administration.
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McClintock, Cynthia. Conclusion and the Future of Presidential-Election Rules. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780190879754.003.0008.

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Runoff has been advantageous in Latin America and could be in the United States also. Amid the legitimacy deficits of the 2000 and 2016 elections in the United States, popular demand for change in electoral rules is strong. Although ranked-choice voting is the most common innovation in the United States, it is complex and relatively untested. By contrast, runoff has been tested in Latin America and shown to be successful. Runoff opened the electoral arena to new parties but, at the same time, assured that the president had majority support and was not at an ideological extreme. By contrast, plurality often facilitated political exclusion by dominant parties and exacerbated cynicism and polarization. Although the number of parties was larger under runoff, the concomitant problems can be ameliorated by such measures as the scheduling of the legislative election after the first round and raising the threshold for entry to the legislature.
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Bjørnerheim, Reidar, Genevieve Derumeaux, and Andrzej Gackowski. Digital echocardiography laboratory. Oxford University Press, 2016. http://dx.doi.org/10.1093/med/9780198726012.003.0017.

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Modern digital echo laboratories are based on echo scanners working in a network with file server(s) and work-station computers for offline analysis and reporting. They may be based on vendor-specific software, but are preferably based on vendor-independent software solutions, being able to handle data from all brands of scanners. To enable analysis of advanced echocardiographic techniques, plug-ins for vendor-specific solutions should be integrated in the otherwise vendor-independent software. To obtain full efficiency, the system should be integrated with the hospital information system for patient demographics and scheduling, and the approved report should automatically be returned to the electronic patient record without the need for scanning or other handling by manpower. To obtain this, a variety of standards have been developed, most of them for medical imaging in general. Scanners of all major brands deliver data compatible with those standards, even if compatibility problems may occur. When the optimal solution for the individual organization has been established, running the echo lab changes significantly. Digital images are stored on safe repositories without quality loss and are available for viewing outside the echo lab. Offline measurements, structured reporting, education, research, quality control, and financial analyses are available. The lab becomes more efficient and cost-effective.
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McClintock, Cynthia. Electoral Rules and Democracy in Latin America. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780190879754.001.0001.

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During Latin America’s third democratic wave, a majority of countries adopted a runoff rule for the election of the president. This book is the first rigorous assessment of the implications of runoff versus plurality for democracy in the region. Despite previous scholarly skepticism about runoff, it has been positive for Latin America, and could be for the United States also. Primarily through qualitative analysis for each Latin American country, I explore why runoff is superior to plurality. Runoff opens the political arena to new parties but at the same time ensures that the president does not suffer a legitimacy deficit and is not at an ideological extreme. By contrast, in a region in which undemocratic political parties are common, the continuation of these parties is abetted by plurality; political exclusion provoked disillusionment and facilitated the emergence of presidents at ideological extremes. In regression analysis, runoff was statistically significant to superior levels of democracy. Between 1990 and 2016, Freedom House and Varieties of Democracy scores plummeted in countries with plurality but improved in countries with runoff. Plurality advocates’ primary concern is the larger number of political parties under runoff. Although a larger number of parties was not significant to inferior levels of democracy, a plethora of parties is problematic, leading to a paucity of legislative majorities and inchoate parties. To ameliorate the problem, I recommend not reductions in the 50% threshold but the scheduling of the legislative election after the first round or thresholds for entry into the legislature.
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Book chapters on the topic "Static scheduling problems"

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Park, Gyung-Leen, Behrooz Shirazi, and Jeff Marquis. "Comparative study of static scheduling with task duplication for distributed systems." In Solving Irregularly Structured Problems in Parallel, 123–34. Berlin, Heidelberg: Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/3-540-63138-0_12.

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Wägemann, Peter. "Static Worst-Case Analyses and Their Validation Techniques for Safety-Critical Systems." In Ernst Denert Award for Software Engineering 2020, 227–47. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-83128-8_11.

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AbstractThe reliable operation of systems with both timing and energy requirements is a fundamental challenge in the area of safety-critical embedded systems. In order to provide guarantees for the execution of tasks within given resource budgets, these systems demand bounds of the worst-case execution time (WCET) and the worst-case energy consumption (WCEC). While static WCET analysis techniques are well established in the software development process of real-time systems nowadays, these program analysis techniques are not directly applicable to the fundamentally different behavior of energy consumption and the determination of the WCEC. Besides the missing approaches for WCEC bounds, the domain of worst-case analyses generally faces the problem that the accuracy and validity of reported analysis bounds are unknown: Since the actual worst-case resource consumption of existing benchmark programs cannot be automatically determined, a comprehensive validation of these program analysis tools is not possible.This summary of my dissertation addresses these problems by first describing a novel program analysis approach for WCEC bounds, which accounts for temporarily power-consuming devices, scheduling with fixed real-time priorities, synchronous task activations, and asynchronous interrupt service routines. Regarding the fundamental problem of validating worst-case tools, this dissertation presents a technique for automatically generating benchmark programs. The generator combines program patterns so that the worst-case resource consumption is available along with the generated benchmark. Knowledge about the actual worst-case resource demand then serves as the baseline for evaluating and validating program analysis tools. The fact the benchmark generator helped to reveal previously undiscovered software bugs in a widespread WCET tool for safety-critical systems underlines the relevance of such a structured testing technique.
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Boeres, Cristina, and Vinod E. F. Rebello. "Solving the Static Task Scheduling Problem for Real Machines." In Applied Optimization, 53–84. Boston, MA: Springer US, 2002. http://dx.doi.org/10.1007/978-1-4757-3609-0_3.

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Vázquez, Manuel, and Darrell Whitley. "A Comparison of Genetic Algorithms for the Static Job Shop Scheduling Problem." In Parallel Problem Solving from Nature PPSN VI, 303–12. Berlin, Heidelberg: Springer Berlin Heidelberg, 2000. http://dx.doi.org/10.1007/3-540-45356-3_30.

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Verhoeven, M. G. A., and E. H. L. Aarts. "Parallel Local Search and Job Shop Scheduling." In Parallel Algorithms for Irregular Problems: State of the Art, 195–212. Boston, MA: Springer US, 1995. http://dx.doi.org/10.1007/978-1-4757-6130-6_10.

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Gerasoulis, Apostolos, Jiao Jia, and Yang Tao. "Applications of Graph Scheduling Techniques in Parallelizing Irregular Scientific Computation." In Parallel Algorithms for Irregular Problems: State of the Art, 245–67. Boston, MA: Springer US, 1995. http://dx.doi.org/10.1007/978-1-4757-6130-6_13.

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Thepphakorn, Thatchai, Saisumpan Sooncharoen, and Pupong Pongcharoen. "Static and Dynamic Parameter Settings of Accelerated Particle Swarm Optimisation for Solving Course Scheduling Problem." In Lecture Notes in Computer Science, 368–80. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-60816-3_40.

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Johnson, Andrew, and Thomas Wahl. "Delay-Bounded Scheduling Without Delay!" In Computer Aided Verification, 380–402. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-81685-8_18.

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AbstractWe consider the broad problem of analyzing safety properties of asynchronous concurrent programs under arbitrary thread interleavings. Delay-bounded deterministic scheduling, introduced in prior work, is an efficient bug-finding technique to curb the large cost associated with full scheduling nondeterminism. In this paper we first present a technique to lift the delay bound for the case of finite-domain variable programs, thus adding to the efficiency of bug detection the ability to prove safety of programs under arbitrary thread interleavings. Second, we demonstrate how, combined with predicate abstraction, our technique can both refute and verify safety properties of programs with unbounded variable domains, even for unbounded thread counts. Previous work has established that, for non-trivial concurrency routines, predicate abstraction induces a highly complex abstract program semantics. Our technique, however, never statically constructs an abstract parametric program; it only requires some abstract-states set to be closed under certain actions, thus eliminating the dependence on the existence of verification algorithms for abstract programs. We demonstrate the efficiency of our technique on many examples used in prior work, and showcase its simplicity compared to earlier approaches on the unbounded-thread Ticket Lock protocol.
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Herrmann, Jeffrey W., Chung-Yee Lee, and Jane L. Snowdon. "A Classification of Static Scheduling Problems." In Complexity in Numerical Optimization, 203–53. WORLD SCIENTIFIC, 1993. http://dx.doi.org/10.1142/9789814354363_0011.

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Ma, Yuliang, Yinghua Han, Jinkuan Wang, and Qiang Zhao. "A Constrained Static Scheduling Strategy in Edge Computing for Industrial Cloud Systems." In Research Anthology on Edge Computing Protocols, Applications, and Integration, 681–714. IGI Global, 2022. http://dx.doi.org/10.4018/978-1-6684-5700-9.ch034.

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With the development of industrial internet, attention has been paid for edge computing due to the low latency. However, some problems remain about the task scheduling and resource management. In this paper, an edge computing supported industrial cloud system is investigated. According to the system, a constrained static scheduling strategy is proposed to over the deficiency of dynamic scheduling. The strategy is divided into the following steps. Firstly, the queue theory is introduced to calculate the expectations of task completion time. Thereupon, the task scheduling and resource management problems are formulated and turned into an integer non-linear programming (INLP) problem. Then, tasks that can be scheduled statically are selected based on the expectation of task completion and constrains of various aspects of task. Finally, a multi-elites-based co-evolutionary genetic algorithm (MEB-CGA) is proposed to solve the INLP problem. Simulation result shows that the MEB-CGA significantly outperforms the scheduling quality of greedy algorithm.
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Conference papers on the topic "Static scheduling problems"

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Xhafa, Fatos, Leonard Barolli, Juan Antonio Gonzalez, and Pawel Jura. "A Static Benchmarking for Grid Scheduling Problems." In 2009 International Conference on Advanced Information Networking and Applications Workshops (WAINA). IEEE, 2009. http://dx.doi.org/10.1109/waina.2009.30.

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Santos, T. N., and A. L. Diniz. "A comparison of static and dynamic models for hydro production in generation scheduling problems." In Energy Society General Meeting. IEEE, 2010. http://dx.doi.org/10.1109/pes.2010.5589895.

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Gorsky, S. A., and A. G. Feoktistov. "Static-dynamic algorithm for managing asynchronous computations in distributed environments." In 1st International Workshop on Advanced Information and Computation Technologies and Systems 2020. Crossref, 2021. http://dx.doi.org/10.47350/aicts.2020.07.

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The paper addresses a relevant problem of computation scheduling in scientific applications (distributed applied software packages) executed in distributed environments. Forming an optimal schedule of jobs for executing of applied software (modules) is an NP-hard problem. Therefore, in practice, heuristic methods of scheduling are often used. In this regard, we propose a new static-dynamic algorithm for managing computations in heterogeneous distributed environments. The results of operating the proposed algorithm are simulated in comparison with other scenarios for computing management. They show that applying the algorithm makes it possible to achieve a rational balance between the scheduling time and the computations makespan.
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Song, Yu-Kun, and Jun Yang. "An iterative list scheduling algorithm for static task scheduling problem on multiprocessor systems." In The 3rd Annual International Conference on Design, Manufacturing and Mechatronics (ICDMM2016). WORLD SCIENTIFIC, 2017. http://dx.doi.org/10.1142/9789813208322_0007.

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Dong, Hang, Boshi Wang, Bo Qiao, Wenqian Xing, Chuan Luo, Si Qin, Qingwei Lin, Dongmei Zhang, Gurpreet Virdi, and Thomas Moscibroda. "Predictive Job Scheduling under Uncertain Constraints in Cloud Computing." In Thirtieth International Joint Conference on Artificial Intelligence {IJCAI-21}. California: International Joint Conferences on Artificial Intelligence Organization, 2021. http://dx.doi.org/10.24963/ijcai.2021/499.

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Capacity management has always been a great challenge for cloud platforms due to massive, heterogeneous on-demand instances running at different times. To better plan the capacity for the whole platform, a class of cloud computing instances have been released to collect computing demands beforehand. To use such instances, users are allowed to submit jobs to run for a pre-specified uninterrupted duration in a flexible range of time in the future with a discount compared to the normal on-demand instances. Proactively scheduling those pre-collected job requests considering the capacity status over the platform can greatly help balance the computing workloads along time. In this work, we formulate the scheduling problem for these pre-collected job requests under uncertain available capacity as a Prediction + Optimization problem with uncertainty in constraints, and propose an effective algorithm called Controlling under Uncertain Constraints (CUC), where the predicted capacity guides the optimization of job scheduling and job scheduling results are leveraged to improve the prediction of capacity through Bayesian optimization. The proposed formulation and solution are commonly applicable for proactively scheduling problems in cloud computing. Our extensive experiments on three public, industrial datasets shows that CUC has great potential for supporting high reliability in cloud platforms.
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Liao, Qi, Bohong Wang, Zhengbing Li, Haoran Zhang, Yongtu Liang, and Jun Liang. "A Novel Depth-First Searching Approach for Detailed Scheduling of Operations in a Multi-Product Pipeline With Multiple Pump Stations." In 2018 12th International Pipeline Conference. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/ipc2018-78341.

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Considering market’s diversified demand and transport economy, large volumes of various refined products commonly move down the pipeline in batches, which are pumped at pump stations and delivered to respective delivery stations. The integrate detailed scheduling optimization is a sophisticated problem due to the characteristics of multi-product pipelines, such as market-oriented, fluctuated demand, various processing technique and complicated hydraulic calculation during batch migration. The integrate detailed scheduling optimization has been widely studied during the last decade, however, most of them studied pipeline scheduling and pump scheduling separately. Besides, the proposed methods are mathematical models, whose computational efficiency greatly decreases in large-scale pipeline scheduling, let alone in the problems coupling with pump scheduling. Aiming at this problem, this paper presents a novel depth-first searching approach based on flowrate ratio to deal with the detailed scheduling of operations in a multi-product pipeline with multiple pump stations. As for each single time interval, the proposed method decides an ideal flowrate ratio according to current status, then solves out the optimal flowrate that mostly conforms to the ideal ratio and satisfies all operational constraints, and finally updates information for next time interval. However, during the computational procedure, backtracking method would be adopted to modify the previous flowrate ratios and recalculate new flowrate when the actual delivered products are insufficient. Finally, a case tested on a Chinese real-world pipeline with 6 delivery stations is given to demonstrate the veracity and practicability of the proposed method. From the results, computing time of the case is within 1 minute, and the solved detailed scheduling plans can fulfill demand with stable pump operations. Besides, the proposed approach is scarcely influenced by the scale of pipeline structure and time horizon, so it is also applicable to the long-term scheduling of a pipeline with many delivery stations.
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Aljasmi, Alia, Reem Al Kaabi, and Noura Al Hassani. "A static-hybrid berth allocation problem with multi ship crane scheduling." In 2016 7th International Conference on Information, Intelligence, Systems & Applications (IISA). IEEE, 2016. http://dx.doi.org/10.1109/iisa.2016.7785352.

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Mourtzis, Dimitris, Ekaterini Vlachou, Michael Doukas, Nikolaos Kanakis, Nikitas Xanthopoulos, and Angelos Koutoupes. "Cloud-Based Adaptive Shop-Floor Scheduling Considering Machine Tool Availability." In ASME 2015 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/imece2015-53025.

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Short-term scheduling belongs to the typical decision-making problems in manufacturing that continue to draw attention from industry and academia due to its inherent difficulties. The trend of mass customization and the increasing product variety generate further uncertainties and turbulences on modern shop-floors, thus, making scheduling a challenging daily problem. These challenges dictate the need for replacing rigid centralized scheduling tools with adaptive and robust scheduling solutions. The integration between ICT based decision support tools in manufacturing can be further enhanced to achieve shop-floor awareness and a common information flow, which is necessary to improve decision-making. Towards this objective, advanced monitoring techniques consisting of smart sensor networks and seamless communication procedures can provide the required awareness to decision making process. Further to that, Cloud, as an emerging enabling technology, can support the integration among multiple IT tools and provide ubiquitous access to data. Cloud-based and resource-aware scheduling tools are therefore considered as enablers for increasing the adaptability and agility of a manufacturing system. The proposed research work, presents a cloud-based framework consisting of a monitoring service and a short-term scheduling application that aims to generate and dispatch feasible and highly-productive schedules in a timely manner. The short-term scheduling application is enriched with data obtained by the monitoring service and generates resource-aware schedules by considering not only machine tools suitability but also their imminent status and availability. The scheduling application utilizes an intelligent search algorithm, which allows the generation of alternative schedules and their evaluation though a set of multiple conflicting criteria including among others cost, time and quality. The produced schedules are assessed using a set of performance indicators of makespan and resource utilization. The monitoring service gathers data from two data sources, namely a multi-sensory system and the machine tool operator. Through an information fusion procedure, the monitoring service provides to the scheduling application the machine tools status as well as the machine tools available time windows. The sensory system is deployed on five axes work-centers to monitor the axis and spindle drives in near real-time. The human operator reports to the monitoring system the status of the machine tool, the currently running task, and the cutting-tool availability through mobile devices on the shop-floor. The information fusion technique, consisting of the Analytic Hierarchy Process and the Dempster’s Shafer theory of evidence, processes these heterogeneous information sources and derives the status of the machine tool and future availability windows. The proposed framework is applied and validated in a real-life case study obtained from a high precision mold-making industry.
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Yun, Sang-Hyuk, Hyo-Sung Ahn, Sun-Ju Park, Ok-Chul Jung, and Dae-Won Chung. "Ground Antenna Scheduling Algorithm for Multi-Satellite Tracking." In ASME 2011 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2011. http://dx.doi.org/10.1115/detc2011-48042.

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In this paper, we address the optimal ground antenna scheduling problem for multiple satellites when multiple satellites have visibility conflicts at a ground station. Visibility conflict occurs when multiple satellites have either overlapping visibilities at a ground station or difference with time of loss of signal (LOS) of a satellite and time of acquisition of signal (AOS) of another satellite is less than reconfiguration time of ground station. Each satellite has a priority value that is a weight function with various factors. Multi-antenna scheduling (MAS) algorithm 1 and Multi-antenna scheduling (MAS) algorithm 2 are proposed to find the optimal schedule of multi-antenna at a ground station using pre-assigned priority values of satellites. We use the depth first search (DFS) method to search the optimal schedule in MAS algorithm 1 and MAS algorithm 2. Through the simulations, we confirm the efficiency of these algorithms by comparing with greedy algorithm.
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10

Islam, Mohammad Rubyet, and Peter Sandborn. "Application of Prognostics and Health Management (PHM) to Software System Fault and Remaining Useful Life (RUL) Prediction." In ASME 2021 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2021. http://dx.doi.org/10.1115/detc2021-70508.

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Abstract Prognostics and Health Management (PHM) is an engineering discipline focused on predicting the point at which systems or components will no longer perform as intended. The prediction is often articulated as a Remaining Useful Life (RUL). RUL is an important decision-making tool for contingency mitigation, i.e., the prediction of an RUL (and its associated confidence) enables decisions to be made about how and when to maintain the system. PHM is generally applied to hardware systems in the electronics and non-electronics application domains. The application of PHM (and RUL) concepts has not been explored for application to software. Today, software (SW) health management is confined to diagnostic assessments that identify problems, whereas prognostic assessment potentially indicates when in the future a problem will become detrimental to the operation of the system. Relevant areas such as SW defect prediction, SW reliability prediction, predictive maintenance of SW, SW degradation, and SW performance prediction, exist, but all represent static models, built upon historical data — none of which can calculate an RUL. This paper addresses the application of PHM concepts to software systems for fault predictions and RUL estimation. Specifically, we wish to address how PHM can be used to make decisions for SW systems such as version update, module changes, rejuvenation, maintenance scheduling and abandonment. This paper presents a method to prognostically and continuously predict the RUL of a SW system based on usage parameters (e.g., numbers and categories of releases) and multiple performance parameters (e.g., response time). The model is validated based on actual data (on performance parameters), generated by the test beds versus predicted data, generated by a predictive model. Statistical validation (regression validation) has been carried out as well. The test beds replicate and validate faults, collected from a real application, in a controlled and standard test (staging) environment. A case study based on publicly available data on faults and enhancement requests for the open-source Bugzilla application is presented. This case study demonstrates that PHM concepts can be applied to SW systems and RUL can be calculated to make decisions on software version update or upgrade, module changes, rejuvenation, maintenance schedule and total abandonment.
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Reports on the topic "Static scheduling problems"

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Merzlykin, Pavlo, Natalia Kharadzjan, Dmytro Medvedev, Irina Zakarljuka, and Liliia Fadeeva. Scheduling Algorithms Exploring via Robotics Learning. [б. в.], 2018. http://dx.doi.org/10.31812/123456789/2877.

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The new approach to schedule-related problems learning with use of robotics is reported. The materials are based on the authors' teaching experience within framework of Robotics School at Kryvyi Rih State Pedagogical University. The proposed learning problem may be used both for scheduling algorithms exploring and robotics competitions.
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