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Journal articles on the topic 'Scheduling'

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Author: Grafiati

Published: 4 June 2021

Last updated: 28 July 2024

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1

Fithri, Prima, and Fitri Ramawinta. "Penjadwalan Mesin dengan Menggunakan Algoritma Pembangkitan Jadwal Aktif dan Algoritma Penjadwalan Non-Delay untuk Produk Hydrotiller dan Hammermil pada CV. Cherry Sarana Agro." Jurnal Optimasi Sistem Industri 12, no. 2 (April 25, 2016): 377. http://dx.doi.org/10.25077/josi.v12.n2.p377-399.2013.

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Fulfillment of all demands of consumers who come to the product is one thing that always wanted to be achieved by a company. These requests are not independent of the company's ability to manufacture certain products. CV Cherry Sarana Agro manufactures a wide range of agricultural equipment, one of which is the product hydrotiller and hammermil. Demand for both products are always in large numbers for each period, however, the company could not meet the entire demand. One of the main factors that led this small company's production capacity for these two products is not optimal scheduling of machines made by companies, causing many to be a queue on a particular machine so that the total process operating time becomes very large. Scheduling method is used to optimize the scheduling of machines working on the report of this practice is actively scheduling method and the method of non-delay scheduling. The data needed to perform scheduling with both of these methods is the data used machines, data processing operations and data processing time of operation. With these three data, can be compared to the actual scheduling done by the company with the scheduling is done using active scheduling method and the method of non-delay scheduling. The most optimal scheduling is obtained after comparing the three methods used are scheduling using the non-delay scheduling. This method was chosen because the resulting make span is much smaller than the two other methods. This method is well applied in the company because in addition to reducing the total processing time, can also increase production capacity, so that all requests can be met.Keywords: Active schedulling method, non-delay schedulling method, makespan, hydrotiller, hammermil

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2

Wang, Kui, Bu Han Zhang, Jia Jun Zhai, Wen Shao, Xiao Shan Wu, and Cheng Xiong Mao. "Coordination between Short-Term and Real-Time Scheduling Incorporating Wind Power." Advanced Materials Research 512-515 (May 2012): 700–703. http://dx.doi.org/10.4028/www.scientific.net/amr.512-515.700.

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Coordination strategies between short-term (e.g., weekly and daily scheduling ) and real-time scheduling in wind power integrated system are disscussed. To cope with the uncertainty of wind power and load demands, weekly and daily rolling schedulings are applied. According to the latest updated prediction results of wind power and load demands, weekly rolling scheduling is applied to revise unit commitment and fuel allocation in remaining hours in a week. Daily rolling scheduling is applied to revise generation scheduling in remaining time in a day. A modified IEEE 118-bus system is applied to test the proposed approach.

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3

Jin, Wangkai, and Xiangjun Peng. "SLITS: Sparsity-Lightened Intelligent Thread Scheduling." ACM SIGMETRICS Performance Evaluation Review 51, no. 1 (June 26, 2023): 21–22. http://dx.doi.org/10.1145/3606376.3593568.

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To make the most of hardware resources in multi-core architectures, effective thread scheduling is crucial. To achieve this, various scheduling objectives have been developed, such as reducing hardware resource contention [1, 11], allocating resources evenly for co-running threads [ 5, 6], and following priority-based policies [7]. Current thread scheduling designs can be categorized into two types. The first type involves fixed-rule scheduling1, which does not depend on workload characteristics and cannot meet the needs of different scheduling objectives. The second type takes the scheduling objectives into account by collecting run-time information on threads together with their correlations (e.g., Cache Miss Count [10, 13], Thread IPC [20], dynamic priority requirements like Earliest Deadline First [2 , 8, 17]), and making scheduling decisions based on thread-to-thread interactions. A unified approach to these two types of scheduler designs can be achieved by focusing on Thread-Interaction statistics. To this end, we introduce the Thread-Interaction Matrix (TIM), which stores statistics on thread-to-thread interaction. These statistics can be any type of run-time statistics concerning the thread-to-thread pairs (e.g., Cache Miss Count [10 , 13], Thread IPC [20], dynamic priority requirements like Earliest Deadline First [2 , 8, 17])2. For fixed-rule scheduling, the TIM contains static values as the statistics do not affect the scheduling decisions. Based on the TIM, scheduling policies can be customized by specifying the rules of thread rescheduling, such as reschedule conditions and strategy. Combining the Thread-Interaction Matrix and scheduling policy provides a formalization of existing thread scheduler designs. Therefore, it is essential to design a general scheduler that can be tailored to different scheduling objectives by co-designing the Thread-Interaction Matrix and the scheduling policy in a synergistic manner.

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4

Kromodihardjo, Sudiyono, and Ergo Swasono Kromodihardjo. "Modeling of Well Service and Workover to Optimize Scheduling of Oil Well Maintenance." Applied Mechanics and Materials 836 (June 2016): 311–16. http://dx.doi.org/10.4028/www.scientific.net/amm.836.311.

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Well maintenance (well service and workover) is an operation needed by oil company to guarantee the optimum productionof its oil well.Well maintenance is performed using large equipment called hydraulic workover unit (HWU-Rig) which is available in limited number. Scheduling sequence of the HWU-Rig to do well service must meet the goal of the maintenance that is to minimize the loss of oil well production due to well breakdown. Thus minimizing breakdown time of well with high rate production is a priority. However, scheduling secuence of the HWU-Rig to perform its task for few days ahead become complicated due to the numerous alternatives of secuence to choose. Each alternatives of sequence yields a certain production loss. Arbitrarily scheduling sequence may not yield the goal og minimizing the loss of well production. This research was done by analyzing workover scheduling system and data from Kondur Petroleum such as well location, well production rate, and service time needed to be performed on wells. Algorithm to create schedulling sequence was developed in the research. The algorithm was then implemented in discrete simulation software, and yield the result of absolute global optimal solution, near optimal solution and local optimal solution of the HWU scheduling problem.

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5

Thenata, Angelina Pramana, and Andhika Galuh Prabawati. "EVALUATION INFORMATION TECHNOLOGY UTILIZATION OF SCHOOL SUBJECT SCHEDULING USING PIECES FRAMEWORK." Jurnal Terapan Teknologi Informasi 2, no. 1 (July 23, 2018): 53–63. http://dx.doi.org/10.21460/jutei.2018.21.97.

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Abstract— Information technology has been widely used by several aspects, such as in the scope of business, industry, government, education, and service. The use of information technology in various aspects of spatial planning can help in its business process. One of the use of information technology in the field of education is e-learning, scheduling, financial information systems, and others. SMK N 1 Kaliwungu is one of the schools that already utilize information technology, such as Program Scheduling Subject Schedule. The program helps scheduling in its implementation need to be evaluated to improve more accurate objectives. In this study, will be discussed about system scheduling program Lesson using PIECES Framework. The Framework section is one way of ordering systems or applications related to Performance, Information, Economics, Control, Efficiency, Application Services. Theuse of this framework aims to determine theimplementation of scheduling aids program at SMKN1 Kaliwungu works as a support, enabler, ordriver in the utilization of Information Technology. This research using data from interviews,observations on the curriculum and provision ofquestionnaires to 30 teachers SMKN 1 Kaliwungu. The result of the evaluation obtained from this research is the utilization of scheduling aidsprogram can improve the curriculum performance program can improve the curriculum performance and teaching process to be smoothly without anycollision schedule. The results of evaluation in this research can be said that the utilization of auxiliary programscheduling at SMKN 1 Kaliwungu role as an enabler. Keyword ----- Evaluation, Technology Information, PIECESFramework, Schedulling

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6

Antonova, Anna, Konstantin Aksyonov, and Olga Aksyonova. "An Imitation and Heuristic Method for Scheduling with Subcontracted Resources." Mathematics 9, no. 17 (August 30, 2021): 2098. http://dx.doi.org/10.3390/math9172098.

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A scheduling problem with subcontracted resources is widely spread and is associated with the distribution of limited renewable and non-renewable resources, both own and subcontracted ones based on the work’s due dates and the earliest start time. Scheduling’s goal is to reduce the cost of the subcontracted resources. In the paper, application of a few scheduling methods based on scheduling theory and the optimization algorithm is considered; limitations of these methods’ application are highlighted. It is shown that the use of simulation modeling with heuristic rules for allocation of the renewable resources makes it possible to overcome the identified limitations. A new imitation and heuristic method for solving the assigned scheduling problem is proposed. The comparison of the new method with existing ones in terms of the quality of the found solution and performance of the methods is carried out. A case study is presented that allowed a four-fold reduction of the overall subcontracted resources cost in a real project portfolio.

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7

hia, M. Sop. "Review on Scheduling-Job Scheduling." International Journal of Engineering Trends and Technology 60, no. 1 (June 25, 2018): 42–44. http://dx.doi.org/10.14445/22315381/ijett-v60p205.

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8

Wang, Huijun, and Oliver Sinnen. "List-Scheduling versus Cluster-Scheduling." IEEE Transactions on Parallel and Distributed Systems 29, no. 8 (August 1, 2018): 1736–49. http://dx.doi.org/10.1109/tpds.2018.2808959.

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9

Belmabrouk, Mounira, and Mounir Marrakchi. "Design, analysis and performance evaluation of parallel algorithms for solving triangular linear systems on multicore platforms." RAIRO - Operations Research 55, no. 2 (March 2021): 545–59. http://dx.doi.org/10.1051/ro/2021009.

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In this paper, we focus on the schedulings of 2-steps graph with constant task cost obtained when parallelizing algorithm solving a triangular linear system. We present three scheduling approaches having the same least theoretical execution time. The first is designed through solving a 0-1 integer problem by Mixed Integer Programming (MIP), the second is based on the Critical Path Algorithm (CPA) and the third is a particular Column-Oriented Scheduling (COS). The MIP approach experiments were carried out and confirmed that the makespan values of the MIP scheduling coincide with those of the corresponding lower bound already reached. Experimental results of the last two approaches detailing both makespans and efficiencies are presented and show that their practical performances differ though they are theoretically identical. We compare also these results to those of the appropriate procedure into so-called PLASMA library (Parallel Linear Algebra for Scalable Multi-core Architectures).

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10

Larco, J. A., J. C. Fransoo, and V. C. S. Wiers. "Scheduling the scheduling task: a time-management perspective on scheduling." Cognition, Technology & Work 20, no. 1 (October 28, 2017): 1–10. http://dx.doi.org/10.1007/s10111-017-0443-1.

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11

Hamilton, James E. "SCHEDULING." Journal of the American Society for Naval Engineers 58, no. 3 (March 18, 2009): 399–417. http://dx.doi.org/10.1111/j.1559-3584.1946.tb01732.x.

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12

de Vries, Tonny T., and Arif A. Anwar. "Irrigation Scheduling Using Complex Machine Scheduling." Journal of Irrigation and Drainage Engineering 141, no. 5 (May 2015): 04014065. http://dx.doi.org/10.1061/(asce)ir.1943-4774.0000824.

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13

Ling, Yibei, and Jie Mi. "An optimal trade-off between content freshness and refresh cost." Journal of Applied Probability 41, no. 3 (September 2004): 721–34. http://dx.doi.org/10.1239/jap/1091543421.

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Caching is an effective mechanism for reducing bandwidth usage and alleviating server load. However, the use of caching entails a compromise between content freshness and refresh cost. Constant refreshing allows a high degree of content freshness at a greater cost of system resource. Conversely, too little refreshing reduces content freshness but saves the cost of resource usage. To address the freshness-cost problem, we formulate the refresh scheduling problem with a generic cost model and use this cost model to determine an optimal refresh frequency that gives the best trade-off between refresh cost and content freshness. We prove the existence and uniqueness of an optimal refresh frequency under the assumptions that the arrival of updated content is Poisson and the age-related cost monotonically increases with decreasing freshness. In addition, we provide an analytic comparison of system performance under fixed refresh scheduling and random refresh scheduling, showing that two refresh schedulings with the same average refresh frequency are mathematically equivalent in terms of the long-run average cost.

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Ling, Yibei, and Jie Mi. "An optimal trade-off between content freshness and refresh cost." Journal of Applied Probability 41, no. 03 (September 2004): 721–34. http://dx.doi.org/10.1017/s0021900200020507.

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Caching is an effective mechanism for reducing bandwidth usage and alleviating server load. However, the use of caching entails a compromise between content freshness and refresh cost. Constant refreshing allows a high degree of content freshness at a greater cost of system resource. Conversely, too little refreshing reduces content freshness but saves the cost of resource usage. To address the freshness-cost problem, we formulate the refresh scheduling problem with a generic cost model and use this cost model to determine an optimal refresh frequency that gives the best trade-off between refresh cost and content freshness. We prove the existence and uniqueness of an optimal refresh frequency under the assumptions that the arrival of updated content is Poisson and the age-related cost monotonically increases with decreasing freshness. In addition, we provide an analytic comparison of system performance under fixed refresh scheduling and random refresh scheduling, showing that two refresh schedulings with the same average refresh frequency are mathematically equivalent in terms of the long-run average cost.

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15

IWAMURA, Koji, Yoshitaka TANIMIZU, and Nobuhiro SUGIMURA. "A Study on Real-Time Scheduling of Holonic Manufacturing Systems(Manufacturing systems and Scheduling)." Proceedings of International Conference on Leading Edge Manufacturing in 21st century : LEM21 2005.2 (2005): 421–26. http://dx.doi.org/10.1299/jsmelem.2005.2.421.

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16

SAKAGUCHI, Tatsuhiko, Yoshitaka TANIMIZU, Tsuyoshi MIYAMAE, Yasuhiro MAEDA, Keiichi SHIRASE, and Nobuhiro SUGIMURA. "Improvement of crossover operator in genetic algorithm for reactive scheduling(Manufacturing systems and Scheduling)." Proceedings of International Conference on Leading Edge Manufacturing in 21st century : LEM21 2005.2 (2005): 427–32. http://dx.doi.org/10.1299/jsmelem.2005.2.427.

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17

Setialana, Pradana, Muhamad Rizki Fajri, Abdul Rachman Pambudi, and Ratna Wardani. "ATLAS (Application for Tracking and Scheduling) as Location Guide and Academic Schedulling at Campus YSU (Yogyakarta State University)." International Journal of Computer and Communication Engineering 3, no. 4 (2014): 274–78. http://dx.doi.org/10.7763/ijcce.2014.v3.335.

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18

Asmawar, Mellysa. "USULAN PENJADWALAN PRODUKSI PRODUK ST 37777 PT EBAKO NUSANTARA PADA DEPARTEMEN SMOOTHMILLING UNTUK MEMINIMASI MAKESPAN." J@ti Undip : Jurnal Teknik Industri 13, no. 1 (March 31, 2018): 61. http://dx.doi.org/10.14710/jati.13.1.61-66.

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AbstrakProses produksi ST 37777 di PT Ebako Nusantara menggunakan jadwal yang didasarkan oleh proses-proses yang dilakukan dengan menggunakan data historis yang telah ada dari proses produksi yang telah dilakukan. PT Ebako Nusantara merupakan industri manufaktur yang bergerak di bidang furnitur yang berlokasi di Terboyo, Semarang, Jawa Tengah. Dalam proses produksi ST 37777, terdapat 11 mesin dan 16 job dimana setiap job memiliki urutan mesin yang berbeda. Penjadwalan yang ada untuk produk tipe ST 37777 dengan tipe jobshop belum menerapkan suatu ketetapan dalam penentuan waktu dan urutan pengerjaan mesin yang efektif sehingga masih banyak job yang selesai terlambat. Untuk itu diperlukan suatu penjadwalan mesin yang efektif sehingga dapat memenuhi waktu produksi pesanan sesuai dengan yang telah disepakati. Penjadwalan jobshop diperlukan untuk memaksimumkan efisiensi dan utilitas sumber daya di lantai produksi. Penentuan jadwal mesin ini bertujuan meminimasi makespan dengan menggunakan Software WINQSB modul job schedulling. Metode yang digunakan adalah metode Short Processing Time. Hasil penjadwalan menggunakan Software WINQSB diperoleh makespan menjadi 15 jam dengan hasil penjadwalan tersebut tidak ada job yang terlambat dan semua job dikerjakan berurutan. AbstractThe production process of ST 37777 in PT Ebako Nusantara uses a schedule based on the processes performed using existing historical data from the production process that has been done. PT Ebako Nusantara is a manufacturing industry engaged in furnitur located in Terboyo, Semarang, Central Java. In the production process ST 37777, there are 11 machines and 16 jobs where each job has a different sequence of machines. The existing scheduling for ST 37777 type product with jobshop type has not been applied a determination in the timing and sequence of effective machine work so that many jobs are finished too late. For that required an effective engine scheduling so that it can meet the production time of orders in accordance with the agreed. Jobshop scheduling is needed to maximize efficiency and resource utilities on the production floor. Determination of this machine schedule aims to minimize the makespan using WINQSB Software job scheduling module. The method used is the method of Short Processing Time. The scheduling result using WINQSB software obtained makespan to 15 hours with scheduling result no job is late and all job done in sequence. Keywords: Jobshop Scheduling; Short Processing Time; Makespan Minimization

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19

Xu, Bin-yang, He-ping Pu, and Shao-qian Li. "Scheduling Algorithm Design for Enhanced Scheduling Fairness." Journal of Electronics & Information Technology 30, no. 6 (March 16, 2011): 1462–65. http://dx.doi.org/10.3724/sp.j.1146.2006.01043.

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20

Lelchook, Ariel Maya, James E. Martin, and Agnieszka Shepard. ""Sunday Work, Scheduling Preferences, and Scheduling Attitudes"." Academy of Management Proceedings 2013, no. 1 (January 2013): 17237. http://dx.doi.org/10.5465/ambpp.2013.17237abstract.

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21

Vemuri, S., A. B. Ranjit Kumar, and A. Halimah. "Fuel Resource Scheduling??? The Daily Scheduling Problem." IEEE Power Engineering Review PER-5, no. 2 (February 1985): 33–34. http://dx.doi.org/10.1109/mper.1985.5528868.

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22

Verstichel, Jannes, Patrick De Causmaecker, and Greet Vanden Berghe. "Scheduling algorithms for the lock scheduling problem." Procedia - Social and Behavioral Sciences 20 (2011): 806–15. http://dx.doi.org/10.1016/j.sbspro.2011.08.089.

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23

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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24

Xu, J., and D. L. Parnas. "Priority Scheduling Versus Pre-Run-Time Scheduling." IFAC Proceedings Volumes 31, no. 14 (June 1998): 53–60. http://dx.doi.org/10.1016/s1474-6670(17)44872-5.

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25

Burleson, W., J. Ko, D. Niehaus, K. Ramamritham, J. A. Stankovic, G. Wallace, and C. Weems. "The spring scheduling coprocessor: a scheduling accelerator." IEEE Transactions on Very Large Scale Integration (VLSI) Systems 7, no. 1 (March 1999): 38–47. http://dx.doi.org/10.1109/92.748199.

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26

Ranjit Kumar, A., S. Vemuri, and A. Halimah. "Fuel Resource Scheduling The Daily Scheduling Problem." IEEE Transactions on Power Apparatus and Systems PAS-104, no. 2 (February 1985): 313–20. http://dx.doi.org/10.1109/tpas.1985.319045.

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27

Kaplansky, Eliezer, and Amnon Meisels. "Distributed personnel scheduling—negotiation among scheduling agents." Annals of Operations Research 155, no. 1 (July 17, 2007): 227–55. http://dx.doi.org/10.1007/s10479-007-0206-0.

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28

You, Wanqing, Kai Qian, and Ying Qian. "Hierarchical Queue-Based Task Scheduling." Journal of Advances in Computer Networks 2, no. 2 (2014): 138–41. http://dx.doi.org/10.7763/jacn.2014.v2.98.

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29

WU, MIN-YOU. "PARALLEL INCREMENTAL SCHEDULING." Parallel Processing Letters 05, no. 04 (December 1995): 659–70. http://dx.doi.org/10.1142/s0129626495000588.

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Parallel incremental scheduling is a new approach for load balancing. In parallel scheduling, all processors cooperate together to balance the workload. Parallel scheduling accurately balances the load by using global load information. In incremental scheduling, the system scheduling activity alternates with the underlying computation work. This paper provides an overview of parallel incremental scheduling. Different categories of parallel incremental scheduling are discussed.

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30

Selvarajah, Esaignani, and George Steiner. "BATCH SCHEDULING IN CUSTOMER-CENTRIC SUPPLY CHAINS(Advanced Planning and Scheduling for Supply Chain Management)." Journal of the Operations Research Society of Japan 49, no. 3 (2006): 174–87. http://dx.doi.org/10.15807/jorsj.49.174.

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31

Huang, Guo Xun, Wei Xiang, Chong Li, Qian Zheng, Shan Zhou, Bing Qian Shen, and Sai Feng Chen. "Surgical Scheduling Based on Hybrid Flow-Shop Scheduling." Applied Mechanics and Materials 201-202 (October 2012): 1004–7. http://dx.doi.org/10.4028/www.scientific.net/amm.201-202.1004.

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The efficient surgical scheduling of the operating theatre plays a significant role in hospital’s income and cost. Currently surgical scheduling only considered the surgery process in operating room and ignored other stages which should not be left out in real situations. The surgical scheduling problem is regarded as the hybrid flow-shop scheduling problem in this study. Each elective surgery which need local anesthesia has to go through a two-stage surgery procedure. Beds and operating rooms are represented as parallel machines. A mathematical model for such surgical scheduling problem is proposed and solved by LINGO. A case study with its optimal solution is also presented to verify the model.

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32

Şenyiğit, Ercan. "Ergo-Scheduling." New Trends and Issues Proceedings on Humanities and Social Sciences 4, no. 10 (January 12, 2018): 208–17. http://dx.doi.org/10.18844/prosoc.v4i10.3079.

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In this paper we consider scheduling problem under ergonomic risk factors. We recruit OCRA index to control musculoskeletal disorder along schedule. Modern manufacturing systems competition power depends on cost, time and flexibility level. Despite of high level automation in manufacturing system, flexibility depends on human workforce. From this perspective, for gaining high rate production, workforces have to endure high frequency manual job. This case causes musculoskeletal disorder. Musculoskeletal disorder which had to be control is one of the most important ergonomic risks in work environment. We used OCRA index mean value for ergonomic risk assessment. We also named this new type of scheduling as Ergo-Scheduling. Keywords: Ergonomic risk assessment, scheduling, single machine scheduling, deterioration, OCRA Index;

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Middleton, Townsend. "Scheduling tribes." Focaal 2013, no. 65 (March 1, 2013): 13–22. http://dx.doi.org/10.3167/fcl.2013.650102.

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Venturing into an ethnography of government anthropologists themselves, this article interrogates the bureaucratic inner workings and actual agents of today's “ethnographic state." By engaging with the civil servants who verify India's Scheduled Tribes, I explore the politics of “tribal“ recognition from the inside out. This perspective lends timely insight into the logistical, political, and epistemological difficulties integral to the functioning-and current crisis-of India's affirmative action system. Weighing the demands of “tribal“ recognition through those that arguably know them best-government anthropologists themselves- this study examines the human dimension (and dilemmas) of the Indian state and its affirmative action system for Scheduled Tribes.

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34

Veselý, Pavel. "Packet Scheduling." ACM SIGACT News 52, no. 2 (June 14, 2021): 72–84. http://dx.doi.org/10.1145/3471469.3471481.

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Online packet scheduling with deadlines is one of the fundamental models in buffer management. Recently, the author together with Chrobak, Jez, and Sgall (SODA 2019) designed an optimal ϕ-competitive algorithm for this problem, where ϕ ≈1.618 is the golden ratio. In this column, we sketch ideas that led us to the development of this algorithm and outline the concepts in its analysis. We also highlight open questions in packet scheduling.

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35

Dieffenbach, Robert M. "Combinatorial Scheduling." Mathematics Teacher 83, no. 4 (April 1990): 269–73. http://dx.doi.org/10.5951/mt.83.4.0269.

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Small projects like putting up a swing set and big projects like building a house all consist of interrelated tasks. Some of these tasks must be done in sequence, but often several tasks can be going on at once.

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36

Maggio, Martina, Federico Terraneo, and Alberto Leva. "Task scheduling." ACM Transactions on Embedded Computing Systems 13, no. 4 (December 5, 2014): 1–22. http://dx.doi.org/10.1145/2560015.

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37

Johns, Stuart, and Peter Brucker. "Scheduling Algorithms." Journal of the Operational Research Society 47, no. 8 (August 1996): 1077. http://dx.doi.org/10.2307/3010416.

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38

Aubin, Jean. "Scheduling Ambulances." Interfaces 22, no. 2 (April 1992): 1–10. http://dx.doi.org/10.1287/inte.22.2.1.

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Mahlke, Scott A., William Y. Chen, Roger A. Bringmann, Richard E. Hank, Wen-Mei W. Hwu, B. Ramakrishna Rau, and Michael S. Schlansker. "Sentinel scheduling." ACM Transactions on Computer Systems 11, no. 4 (November 1993): 376–408. http://dx.doi.org/10.1145/161541.159765.

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40

GUPTA, S. M., and K. N. TALEB. "Scheduling disassembly." International Journal of Production Research 32, no. 8 (August 1994): 1857–66. http://dx.doi.org/10.1080/00207549408957046.

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41

Xia, Feng, Guosong Tian, and Youxian Sun. "Feedback scheduling." ACM SIGPLAN Notices 42, no. 12 (December 2007): 7–14. http://dx.doi.org/10.1145/1341752.1341753.

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42

Hwang, C. T., and Y. C. Hsu. "Zone scheduling." IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems 12, no. 7 (July 1993): 926–34. http://dx.doi.org/10.1109/43.238029.

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43

Lee, Min, and Karsten Schwan. "Region scheduling." ACM SIGARCH Computer Architecture News 40, no. 1 (April 18, 2012): 451–62. http://dx.doi.org/10.1145/2189750.2151023.

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FENWICK, RUDY, and MARK TAUSIG. "Scheduling Stress." American Behavioral Scientist 44, no. 7 (March 2001): 1179–98. http://dx.doi.org/10.1177/00027640121956719.

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Kerns, Daniel R., and Susan J. Eggers. "Balanced scheduling." ACM SIGPLAN Notices 28, no. 6 (June 1993): 278–89. http://dx.doi.org/10.1145/173262.155117.

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Lehner, Vanessa, and David S. Smith. "Wave Scheduling." Journal of Physician Assistant Education 27, no. 4 (December 2016): 200–202. http://dx.doi.org/10.1097/jpa.0000000000000094.

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Chang, Jessica, Thomas Erlebach, Renars Gailis, and Samir Khuller. "Broadcast scheduling." ACM Transactions on Algorithms 7, no. 4 (September 2011): 1–14. http://dx.doi.org/10.1145/2000807.2000815.

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Drouin, Robin, and Mertie Potter. "Flexible Scheduling." AJN, American Journal of Nursing 105, no. 11 (November 2005): 72E—72F. http://dx.doi.org/10.1097/00000446-200511000-00045.

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Iyer, Sitaram, and Peter Druschel. "Anticipatory scheduling." ACM SIGOPS Operating Systems Review 35, no. 5 (December 2001): 117–30. http://dx.doi.org/10.1145/502059.502046.

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BELTZHOOVER, MARIANNE. "Self-Scheduling." Nursing Management (Springhouse) 25, no. 4 (April 1994): 81???83. http://dx.doi.org/10.1097/00006247-199404000-00015.

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