Relevant bibliographies by topics / Dynamic scheduling

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Dynamic scheduling'

Author: Grafiati
Published: 4 June 2021
Last updated: 20 February 2023

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Journal articles on the topic "Dynamic scheduling"

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Pan, Ying, Dong Juan Xue, Tian Yi Gao, Li Bin Zhou, and Xiao Yu Xie. "Modeling and Scheme Generation of Dynamic Flexible Job-Shop Scheduling." Applied Mechanics and Materials 423-426 (September 2013): 2232–36. http://dx.doi.org/10.4028/www.scientific.net/amm.423-426.2232.

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Aiming at uncertain information and dynamic characteristic during flexible job-shop scheduling process, some kind of dynamic scheduling method for flexible job-shop scheduling problem (FJSP) is put forward based on real-time adjustment. A dynamic simulation solution mode framework is presented for FJSP. This framework is inspired by adaptive control, combined with the robust scheduling and foreseeing scheduling. It has both advantages of such two scheduling methods, and its stable and highly efficient. Preliminary scheme generation method based on foreseeing dynamics scheduling is introduced then. Foreseeing function is realized by fault-handling algorithm and dynamic simulation solver on the basis of Adaptive Genetic Algorithm (AGA).
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Jiang, Hai, and Cynthia Barnhart. "Dynamic Airline Scheduling." Transportation Science 43, no. 3 (August 2009): 336–54. http://dx.doi.org/10.1287/trsc.1090.0269.

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Yau, C. "Dynamic flight scheduling." Omega 17, no. 6 (January 1989): 533–42. http://dx.doi.org/10.1016/0305-0483(89)90057-1.

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Stillwell, Mark, Frederic Vivien, and Henri Casanova. "Dynamic Fractional Resource Scheduling versus Batch Scheduling." IEEE Transactions on Parallel and Distributed Systems 23, no. 3 (March 2012): 521–29. http://dx.doi.org/10.1109/tpds.2011.183.

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Huang, Yuan, Xiu Tian Yan, and Jing Yao Li. "Dual Resource Constrained Job Shop Dynamic Scheduling with Local Time Window." Advanced Materials Research 933 (May 2014): 708–13. http://dx.doi.org/10.4028/www.scientific.net/amr.933.708.

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To solve the Dual Resource Constrained Job Shop Dynamic Scheduling Problem with heterogeneous workers (DRCJDSP-HW),a three-tier dynamic scheduling system including dynamic disturbance analysis, dynamic disturbance evaluation and dynamic scheduling method was constructed based on the idea of scheduling with local time window. To minimize the revision of old scheduling scheme in DRCJDSP-HW, a hybrid dynamic scheduling algorithm was proposed based on the chromosome reduction mechanism and the scheduling optimization of local job in stages. The outstanding application effect of the dynamic scheduling system and the hybrid dynamic scheduling algorithm were validated reducing the influence of dynamic disturbances effectively by simulation experiment at last.
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Cheng, Mingang, Hiromi Itoh Ozaku, Noriaki Kuwahara, Kiyoshi Kogure, and Jun Ota. "Dynamic Scheduling in Inpatient Nursing." International Journal of Automation Technology 3, no. 2 (March 5, 2009): 174–84. http://dx.doi.org/10.20965/ijat.2009.p0174.

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To shorten the notoriously long waits for service in hospitals in Japan and to improve efficiency, we propose a scheduling algorithm with a 2-layer local search based on simulated annealing -- permutating (switching) (i) tasks among nurses and (ii) subtasks on each nurse. The scheduling algorithm generates a solution initializing our proposed dynamic scheduling to iteratively generate new, feasible schedules based on the scheduling algorithm to accommodate interruptions while preventing nurses' work hours from increasing. To verify the effectiveness of our proposed scheduling, we executed a set of nursing scheduling problems taken from those actually observed and focused on those that featuring frequent interruptions.
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Ivanov, D., and B. Sokolov. "Dynamic supply chain scheduling." Journal of Scheduling 15, no. 2 (August 11, 2010): 201–16. http://dx.doi.org/10.1007/s10951-010-0189-6.

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Agnetis, Alessandro, Stanisław Gawiejnowicz, Bertrand Miao-Tsong Lin, and Gur Mosheiov. "Editorial: Dynamic Scheduling Problems." Journal of Scheduling 23, no. 6 (October 24, 2020): 629–30. http://dx.doi.org/10.1007/s10951-020-00673-4.

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Taunton, J. C., and C. M. Ready. "Intelligent dynamic production scheduling." Food Research International 27, no. 2 (January 1994): 111–16. http://dx.doi.org/10.1016/0963-9969(94)90151-1.

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Serpanos, Dimitrios N., Asser N. Tantawi, and Ahmed N. Tantawy. "Credit scheduling: adaptive scheduling with dynamic service quota." Computer Communications 21, no. 10 (July 1998): 889–97. http://dx.doi.org/10.1016/s0140-3664(98)00141-8.

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Dissertations / Theses on the topic "Dynamic scheduling"

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Burke, Peter. "Scheduling in dynamic environments." Thesis, University of Strathclyde, 1989. http://oleg.lib.strath.ac.uk:80/R/?func=dbin-jump-full&object_id=21291.

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Much of the work in the area of automated scheduling systems is based on the assumption that the intended execution environment is static and deterministic. The work presented in this thesis is motivated by recognition of the fact that most real world scheduling environments are dynamic and stochastic. It views the scheduling task as one of satisfaction rather than optimisation, and maintenance over creation. This thesis reviews existing work in the area and identifies an opportunity to combine recent advances in scheduling technology with the power of distributed processing. Within a suitable problem-solving architecture it is argued that this combination can help to address the fundamental problems of execudonal uncertainty, conflicting objectives and combinatorial complexity. A scheduling system, DAS, which employs such a problem-solving architecture, is presented. It is distributed, asynchronous and hierarchical, and requires careful management of problem-solving effort. DAS adopts an opportunistic approach to problem-solving and the management of problem-solving effort. The mechanisms which manage problem-solving effort within DAS are also presented. In conclusion it is argued that the architecture and mechanisms presented lend themselves very well to the view taken of the scheduling task.
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Ellefsen, Kai Olav. "Dynamic Scheduling for Autonomous Robotics." Thesis, Norwegian University of Science and Technology, Department of Computer and Information Science, 2010. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-10857.

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This project report describes a hybrid genetic algorithm that works as a schedule generator for a complex robotic harvesting task. The task is set to a dynamic environment with a robotic opponent, making responsiveness of the planning algorithm particularly important. To solve this task, many previous scheduling algorithms were studied. Genetic algorithms have successfully been used in many dynamic scheduling tasks, due to their ability to incrementally adapt and optimize solutions when changes are made to the environment. Many of the previous approaches also used a separate heuristic to quicly adapt solutions to the new environment, making the algorithm more responsive. In addition, the study of previous work revealed the importance of population diversity when making a responsive genetic algorithm. Implementation was based on a genetic algorithm made as the author's fifth year specialization project for solving a static version of the same task. This algorithm was hybridized with a powerful local search technique that proved essential in generating good solutions for the complex harvesting task. When extending the algorithm to also work in a dynamically changing environment, several adaptations and extensions needed to be made, to make it more responsive. The extensions and adaptations include a fast-response heuristic for immediate adaptation to environmental changes, a decrease in genotype size to speed up local searches and a contingency planning module intending to solve problems before they arise. Experiments proved that the implemented dynamic planner successfully adapted its plans to a changing environment, clearly showing improvements compared to running a static plan. Further experiments also proved that the dynamic planner was able to deal with erroneous time estimates in its simulator module in a good way. Experiments on contingency planning gave no clear results, but indicated that using computational resources for planning ahead may be a good choice, if the contingency to plan for is carefully selected. As no unequivocal results were obtained, further studies of combining genetic algorithms and contingency planning may be an interesting task for future efforts.

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Anagnostopoulos, Eleftherios. "Bus Scheduling including Dynamic Events." Thesis, Uppsala universitet, Institutionen för informationsteknologi, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-333029.

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Modern transportation systems should be designed according to the requirements of their passengers, while considering operational costs for the managing organizations,as well as being environmentally friendly. The main objective of this work is to provide a realistic simulation of a transportation system, capable of identifying connections among the road network of operation areas, creating bus lines composedof multiple connected bus stops, simulating travel requests registered by potential passengers, as well as generating routes and timetables for bus vehicles, while taking into consideration factors which could affect the predefined schedule, includingun predictable events (e.g., traffic accidents) or dynamic levels of traffic density.The implemented bus management system is able to generate timetables dynamically,introducing a reasoning mechanism capable of evaluating travel requests based on dynamic clustering techniques, while offering the opportunity to its administrator to make decisions regarding the number of generated timetables, operating bus vehicles,passengers per timetable, waiting time of passengers, and processing time. In addition,the routes of bus lines are generated or updated dynamically, while taking into consideration real-time traffic data and evaluating parameters, such as covered distance or travelling time, in order to identify the most effective connectionsbetween the bus stops of each bus line and make adjustments to the corresponding timetables. Finally, the number of operating bus vehicles that are required in order to transport the passengers of each bus line is estimated, leading to a more efficient distribution of available resources.
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Ou, Jihong. "Dynamic scheduling of queueing networks." Thesis, Massachusetts Institute of Technology, 1991. http://hdl.handle.net/1721.1/13479.

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Rosas, Ham Demian. "Dynamic scheduling in multicore processors." Thesis, University of Manchester, 2012. https://www.research.manchester.ac.uk/portal/en/theses/dynamic-scheduling-in-multicore-processors(c96d6641-ba16-44d2-9da5-34c41fd15956).html.

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The advent of multi-core processors, particularly with projections that numbers of cores will continue to increase, has focused attention on parallel programming. It is widely recognized that current programming techniques, including those that are used for scientific parallel programming, will not allow the easy formulation of general purpose applications. An area which is receiving interest is the use of programming styles which do not have side-effects. Previous work on parallel functional programming demonstrated the potential of this to permit the easy exploitation of parallelism. This thesis investigates a dynamic load balancing system for shared memory Chip Multiprocessors. This system is based on a parallel computing model called SLAM (Spreading Load with Active Messages), which makes use of functional language evaluation techniques. A novel hardware/software mechanism for exploiting fine grain parallelism is presented. This mechanism comprises a runtime system which performs dynamic scheduling and synchronization automatically when executing parallel applications. Additionally the interface for using this mechanism is provided in the form of an API. The proposed system is evaluated using cycle-level models and multithreaded applications running in a full system simulation environment.
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Hsu, Chih-hua. "Dynamic scheduling of manufacturing systems /." Digital version accessible at:, 1998. http://wwwlib.umi.com/cr/utexas/main.

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Heasley, McKay N. "Dynamic Appointment Scheduling in Healthcare." BYU ScholarsArchive, 2011. https://scholarsarchive.byu.edu/etd/3176.

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In recent years, healthcare management has become fertile ground for the scheduling theory community. In addition to an extensive academic literature on this subject, there has also been a proliferation of healthcare scheduling software companies in the marketplace. Typical scheduling systems use rule-based analytics that give schedulers advisory information from programmable heuristics such as the Bailey-Welch rule cite{B,BW}, which recommends overbooking early in the day to fill-in potential no-shows later on. We propose a dynamic programming problem formulation to the scheduling problem that maximizes revenue. We formulate the problem and discuss the effectiveness of 3 different algorithms that solve the problem. We find that the 3rd algorithm, which has smallest amount of nodes in the decision tree, has an upper bound given by the Bell numbers. We then present an alternative problem formulation that includes stochastic appointment lengths and no shows.
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Khamooshi, H. "Heuristic network-based project scheduling : dynamic priority scheduling method; DPSM." Thesis, Lancaster University, 1994. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.267918.

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Li, Caiwei. "Dynamic scheduling of multiclass queueing networks." Diss., Georgia Institute of Technology, 2000. http://hdl.handle.net/1853/24339.

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Kreaseck, Barbara. "Dynamic autonomous scheduling on heterogeneous systmes /." Diss., Connect to a 24 p. preview or request complete full text in PDF format. Access restricted to UC campuses, 2003. http://wwwlib.umi.com/cr/ucsd/fullcit?p3102539.

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Books on the topic "Dynamic scheduling"

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Koole, G. M. Stochastic scheduling and dynamic programming. Amsterdam, Netherlands: Centrum voor Wiskunde en Informatica, 1995.

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Koole, G. M. Stochastic scheduling and dynamic programming. Amsterdam, Netherlands: Centrum voor Wiskunde en Informatica, 1995.

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Hirst, Eric. Ancillary-service details: Dynamic scheduling. Oak Ridge, Tenn: Oak Ridge National Laboratory, 1997.

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Koole, G. M. Stochastic scheduling and dynamic programming. Amsterdam, Netherlands: Centrum voor Wiskunde en Informatica, 1995.

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Vanhoucke, Mario. Project Management with Dynamic Scheduling. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-25175-7.

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Vanhoucke, Mario. Project Management with Dynamic Scheduling. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-40438-2.

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Shaw, Michael J. Dynamic scheduling in cellular manufacturing systems. [Urbana, Ill.]: College of Commerce and Business Administration, University of Illinois at Urbana-Champaign, 1987.

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service), SpringerLink (Online, ed. Project Management with Dynamic Scheduling: Baseline Scheduling, Risk Analysis and Project Control. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012.

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Brown, Gerald J. Dynamic task scheduling for the Knowledge Worker System. Champaign, IL: U.S. Army Construction Engineering Research Laboratory, 1996.

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Reiman, M. I. Dynamic scheduling of a two-class queue with setups. Cambridge, Mass: Alfred P. Sloan School of Management, Massachusetts Institute of Technology, 1994.

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Book chapters on the topic "Dynamic scheduling"

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Pinedo, Michael L. "Deterministic and Stochastic Dynamic Programming." In Scheduling, 573–79. Boston, MA: Springer US, 2011. http://dx.doi.org/10.1007/978-1-4614-2361-4_22.

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Salleh, Shaharuddin, and Albert Y. Zomaya. "Dynamic Scheduling." In Scheduling in Parallel Computing Systems, 93–125. Boston, MA: Springer US, 1999. http://dx.doi.org/10.1007/978-1-4615-5065-5_5.

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Ulfsby, Stig. "Dynamic production scheduling." In Computer Integrated Manufacturing, 153–69. London: Springer London, 1990. http://dx.doi.org/10.1007/978-1-4471-1786-5_13.

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Jakoby, Andreas, Maciej Liśkiewicz, and Rüdiger Reischuk. "Scheduling Dynamic Graphs." In STACS 99, 383–92. Berlin, Heidelberg: Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/3-540-49116-3_36.

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Pillai, Padmanabhan S., and Kang G. Shin. "Dynamic DVFS Scheduling." In Designing Embedded Processors, 243–58. Dordrecht: Springer Netherlands, 2007. http://dx.doi.org/10.1007/978-1-4020-5869-1_11.

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Ruth, Matthias, and Bruce Hannon. "Scheduling Flows." In Modeling Dynamic Economic Systems, 56–75. New York, NY: Springer New York, 1997. http://dx.doi.org/10.1007/978-1-4612-2268-2_4.

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Ruth, Matthias, and Bruce Hannon. "Scheduling Flows." In Modeling Dynamic Economic Systems, 53–70. Boston, MA: Springer US, 2012. http://dx.doi.org/10.1007/978-1-4614-2209-9_4.

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Vanhoucke, Mario. "Dynamic Scheduling with ProTrack." In Project Management with Dynamic Scheduling, 275–89. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-40438-2_15.

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Vanhoucke, Mario. "Dynamic Scheduling with ProTrack." In Project Management with Dynamic Scheduling, 273–82. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-25175-7_15.

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Kennedy, John O. S. "Scheduling, Replacement and Inventory Management." In Dynamic Programming, 129–55. Dordrecht: Springer Netherlands, 1986. http://dx.doi.org/10.1007/978-94-009-4191-5_5.

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Conference papers on the topic "Dynamic scheduling"

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Uetz, Marc. "Approximation algorithms for scheduling under uncertainty." In Workshop on dynamic scheduling problems. Polish Mathematical Society, 2016. http://dx.doi.org/10.14708/isbn.978-83-937220-7-5p25-28.

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Uetz, Marc. "Approximation algorithms for scheduling under uncertainty." In Workshop on dynamic scheduling problems. Polish Mathematical Society, 2016. http://dx.doi.org/10.14708/isbn.978-83-937220-7-5p25-30.

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Lin, Bertrand M.-T. "Relocation scheduling with optional recycling operations." In Workshop on dynamic scheduling problems. Polish Mathematical Society, 2016. http://dx.doi.org/10.14708/isbn.978-83-937220-7-5p55-58.

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Berlińska, Joanna. "The first international workshop on dynamic scheduling problems." In Workshop on dynamic scheduling problems. Polish Mathematical Society, 2016. http://dx.doi.org/10.14708/isbn.978-83-937220-7-5p31-34.

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Kovalyov, Mikhail Y., Xavier Delorme, and Alexandre Dolgui. "Workforce planning for cyclic production of multiple parts." In Workshop on dynamic scheduling problems. Polish Mathematical Society, 2016. http://dx.doi.org/10.14708/isbn.978-83-937220-7-5p47-50.

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Gawiejnowicz, Stanisław, and Wiesław Kurc. "Solving a time-dependent scheduling problem by interior point method." In Workshop on dynamic scheduling problems. Polish Mathematical Society, 2016. http://dx.doi.org/10.14708/isbn.978-83-937220-7-5p35-38.

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Gerstl, Enrique, Baruch Mor, and Gur Mosheiov. "Minmax scheduling with acceptable lead-times: Extensions to position-dependent processing times, due-window and job rejection." In Workshop on dynamic scheduling problems. Polish Mathematical Society, 2016. http://dx.doi.org/10.14708/isbn.978-83-937220-7-5p39-41.

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Kononov, Alexander, and Yulia Kovalenko. "An 'almost-exact' solution to speed scaling scheduling of parallel jobs with preemption." In Workshop on dynamic scheduling problems. Polish Mathematical Society, 2016. http://dx.doi.org/10.14708/isbn.978-83-937220-7-5p43-46.

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Kurc, Wiesław, and Stanisław Gawiejnowicz. "Directed sets, Möbius inversing formula and time-dependent scheduling on precedence-constrained machines." In Workshop on dynamic scheduling problems. Polish Mathematical Society, 2016. http://dx.doi.org/10.14708/isbn.978-83-937220-7-5p51-54.

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Ocetkiewicz, Krzysztof M., and Michał Małafiejski. "Financial scheduling with time-dependent resource consumption." In Workshop on dynamic scheduling problems. Polish Mathematical Society, 2016. http://dx.doi.org/10.14708/isbn.978-83-937220-7-5p59-62.

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Reports on the topic "Dynamic scheduling"

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Castanon, David A., David A. Logan, Dimitri P. Bertsekas, and Stephen D. Patek. Planning and Scheduling: Dynamic Assignment and Scheduling with Contingencies. Fort Belvoir, VA: Defense Technical Information Center, March 1998. http://dx.doi.org/10.21236/ada342494.

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Hirst, E., and B. Kirby. Ancillary-service details: Dynamic scheduling. Office of Scientific and Technical Information (OSTI), January 1997. http://dx.doi.org/10.2172/631228.

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Kang, Byeong Ho, Paul Compton, Hiroshi Motoda, and John Salerno. Dynamic Scheduling for Web Monitoring Crawler. Fort Belvoir, VA: Defense Technical Information Center, February 2009. http://dx.doi.org/10.21236/ada494589.

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Crawford, Elisabeth, and Manuela Veloso. Learning Dynamic Time Preferences in Multi-Agent Meeting Scheduling. Fort Belvoir, VA: Defense Technical Information Center, July 2005. http://dx.doi.org/10.21236/ada457066.

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Smith, Sharon L., and Robert B. Schnabel. Centralized and Distributed Dynamic Scheduling for Adaptive, Parallel Algorithms. Fort Belvoir, VA: Defense Technical Information Center, February 1991. http://dx.doi.org/10.21236/ada233557.

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Cassandras, Christos G. Discrete-Event-Dynamic-System-Based Approaches for Scheduling Transmissions in Multihop Packet Radio Networks. Fort Belvoir, VA: Defense Technical Information Center, January 1993. http://dx.doi.org/10.21236/ada276566.

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Ramamurthy, Byravamurthy. Final Report on DOE Project entitled Dynamic Optimized Advanced Scheduling of Bandwidth Demands for Large-Scale Science Applications. Office of Scientific and Technical Information (OSTI), May 2014. http://dx.doi.org/10.2172/1130458.

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Miller, Allan. Nonpreemptive run-time scheduling issues on a multitasked, multiprogrammed multiprocessor with dependencies, bidimensional tasks, folding and dynamic graphs. Office of Scientific and Technical Information (OSTI), May 1987. http://dx.doi.org/10.2172/5546139.

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Fee, Kyle D. Does Job Quality Affect Occupational Mobility? Federal Reserve Bank of Cleveland, August 2022. http://dx.doi.org/10.26509/frbc-cd-20220804.

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Job quality, a well-known topic in workforce development circles, is an underutilized but useful lens with which to examine labor market conditions. The Aspen Institute (2020), a long-time advocate for job quality, defines it as “a range of attributes that drive worker experiences: wages, benefits, scheduling, legal rights, equity and inclusion, opportunity to build skills and advance, supportive work environment, and worker voice.” Given the record number of resignations and available job openings, especially in the lower-paid industry sectors, along with popular labor market narratives around the Great R’s (Resignation, Renegotiation, Reshuffle), I wonder to what extent job quality plays a role in the occupational mobility of workers. Occupational mobility includes all potential outcomes an individual has when holding a job. For instance, in addition to the option of changing to another occupation, an individual can remain in that occupation, become unemployed, or leave the labor force. Occupational mobility metrics are an appealing way to explore labor market conditions because they provide a dynamic perspective, while traditional metrics such as unemployment and labor force participation rates tend to be static observations.
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Chiang, Mung. Distributed Scheduling in MANET: Tackling the Challenges of Dimensionality, Non-convexity, and Stochastic Dynamics. Fort Belvoir, VA: Defense Technical Information Center, September 2012. http://dx.doi.org/10.21236/ada577488.

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