Relevant bibliographies by topics / Scheduling objectives

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

Academic literature on the topic 'Scheduling objectives'

Author: Grafiati
Published: 4 June 2021
Last updated: 16 February 2022

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Journal articles on the topic "Scheduling objectives"

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Castillo, Ignacio, Tarja Joro, and Yong Yue Li. "Workforce scheduling with multiple objectives." European Journal of Operational Research 196, no. 1 (2009): 162–70. http://dx.doi.org/10.1016/j.ejor.2008.02.038.

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Epstein, Sheldon, Yonah Wilamowsky, and Bernard Dickman. "Deterministic multiprocessor scheduling with multiple objectives." Computers & Operations Research 19, no. 8 (1992): 743–49. http://dx.doi.org/10.1016/0305-0548(92)90013-u.

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Franke, Carsten, Joachim Lepping, and Uwe Schwiegelshohn. "Greedy scheduling with custom-made objectives." Annals of Operations Research 180, no. 1 (2008): 145–64. http://dx.doi.org/10.1007/s10479-008-0491-2.

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Važan, Pavel, Michal Škamla, Dominika Jurovatá, and Vladimír Ľupták. "Effect of Selected Priority Rules on Manufacturing Objectives in Scheduling." Advanced Materials Research 488-489 (March 2012): 1125–29. http://dx.doi.org/10.4028/www.scientific.net/amr.488-489.1125.

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In this paper, the effect of selected priority rules of scheduling is presented. This effect has been studied for chosen scheduling objectives by simulation method. The authors used the simulator Witness to experimentation with priority rules in a designed manufacturing system. The results of experiments have been processed into the synthesis of knowledge. The implementation of scheduling procedure is described in this paper.
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Brezoňáková, Andrea. "Realistic scheduling agreement: Defining principles and objectives." Transportation Research Procedia 43 (2019): 156–64. http://dx.doi.org/10.1016/j.trpro.2019.12.030.

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Monteiro, Thibaud, Nadine Meskens, and Tao Wang. "Surgical scheduling with antagonistic human resource objectives." International Journal of Production Research 53, no. 24 (2015): 7434–49. http://dx.doi.org/10.1080/00207543.2015.1082040.

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Ozturkoglu, Yucel. "An efficient time algorithm for makespan objectives." An International Journal of Optimization and Control: Theories & Applications (IJOCTA) 5, no. 2 (2015): 75–80. http://dx.doi.org/10.11121/ijocta.01.2015.00260.

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This paper focuses on a single machine scheduling subject to machine deterioration with rate-modifying activities (RMA). The motivation for this study stems from the automatic-production line problem with one machine. The main question is to find the sequence in which jobs should be scheduled, how many maintenance activity (RMA) to use, if any, and where to insert them in the schedule during the time interval with optimal makespan objective. This problem is known to be NP-hard and we give concise analyses of the problem and provide polynomial time algorithms to solve the makespan problem. We a
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Bhattacharyya, Siddhartha, and Gary J. Koehler. "Learning by Objectives for Adaptive Shop-Floor Scheduling." Decision Sciences 29, no. 2 (1998): 347–75. http://dx.doi.org/10.1111/j.1540-5915.1998.tb01580.x.

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Salman, Saad Mohsin. "Scheduling Critical Activities on Multi-objectives Stochastic Projects." Journal of Al-Nahrain University Science 16, no. 3 (2013): 246–51. http://dx.doi.org/10.22401/jnus.16.3.34.

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Hellerstein, J. L. "Achieving service rate objectives with decay usage scheduling." IEEE Transactions on Software Engineering 19, no. 8 (1993): 813–25. http://dx.doi.org/10.1109/32.238584.

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Dissertations / Theses on the topic "Scheduling objectives"

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Yang, Jaehwan. "Scheduling with batch objectives /." The Ohio State University, 1998. http://rave.ohiolink.edu/etdc/view?acc_num=osu1487952208107258.

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Huaccho, Huatuco Luisa Delfa. "The role of rescheduling in managing manufacturing systems' complexity." Thesis, University of Oxford, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.275307.

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Mundt, Andreas, and Thomas Wich. "Single Machine Scheduling with Tardiness Involved Objectives : A Survey." Thesis, Linköping University, Department of Mathematics, 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-8628.

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<p>This thesis contributes to theoretical and quantitative aspects of machine scheduling. In fact, it is dedicated to the issue of scheduling n jobs on one single machine. The scope is limited to deterministic problems - i.e. those with all data available and known with certainty in advance - with tardiness involved objectives; hence, the common denominator of all problems addressed are jobs with a predetermined due date assigned to. A job is finished on time as long as it is completed before its due date, otherwise it is said to be tardy. Since the single machine utilized is assumed to be res
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Berry, Pauline M. "A predictive model for satisfying conflicting objectives in scheduling problems." Thesis, University of Strathclyde, 1991. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.332064.

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Aguilar-Soto, Armando. "Fixed-priority scheduling algorithms with multiple objectives in hard real-time systems." Thesis, University of York, 2006. http://etheses.whiterose.ac.uk/11057/.

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In the context ofFixed-Priority Scheduling in Real-Time Systems, we investigate scheduling mechanisms for supporting systems where, in addition to timing constraints, their performance with respect to additional QoS requirements must be improved. This'type of situation may occur when the worst-case res~urce requirements of all or some running tasks cannot be simultaneously met due to task contention. . Solutions to these problems have been proposed in the context of both fixed-priority and dynamic-priority scheduling. In fixed-priority scheduling, the typical approach is to artificially modify
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Xie, Wenbin. "Metaheuristics for single and multiple objectives production scheduling for the capital goods industry." Thesis, University of Newcastle Upon Tyne, 2011. http://hdl.handle.net/10443/1261.

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In the capital goods industry, companies produce plant and machinery that is used to produce consumer products or commodities such as electricity or gas. Typical products produced in these companies include steam turbines, large boilers and oil rigs. Scheduling of these products is difficult due to the complexity of the product structure, which involves many levels of assembly and long complex routings of many operations which are operated in multiple machines. There are also many scheduling constraints such as machine capacity as well as operation and assembly precedence relationships. Produc
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Gama, Pinheiro Vinicius. "The management of multiple submissions in parallel systems : the fair scheduling approach." Thesis, Grenoble, 2014. http://www.theses.fr/2014GRENM042/document.

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Le problème étudié est celui de l'ordonnancement d'applications dans lessystèmes parallèles et distribués avec plusieurs utilisateurs. Les nouvellesplates-formes de calcul parallèle et distribué offrent des puissances trèsgrandes qui permettent d'envisager la résolution d'applications complexesinteractives. Aujourd'hui, il reste encore difficile d'utiliser efficacementcette puissance par manque d'outils de gestion de ressources. Le travaileffectué dans cette thèse se place dans cette perspective d'analyser etdévelopper des algorithmes efficaces pour gérer efficacement des ressources decalcul p
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Trivedi, Manas. "Multi-objective generation scheduling with hybrid energy resources." Connect to this title online, 2007. http://etd.lib.clemson.edu/documents/1202498690/.

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Shaw, Katherine Jane. "Using genetic algorithms for practical multi-objective production schedule optimisation." Thesis, University of Sheffield, 1997. http://etheses.whiterose.ac.uk/14767/.

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Production scheduling is a notoriously difficult problem. Manufacturing environments contain complex, time-critical processes, which create highly constrained scheduling problems. Genetic algorithms (GAs) are optimisation tools based on the principles of evolution. They can tackle problems that are mathematically complex, or even impossible to solve by traditional methods. They allow problem-specific implementation, so that the user can develop a technique that suits the situation, whilst still providing satisfactory schedule optimisation performance. This work tests GA optimisation on a real-
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Metta, Haritha. "ADAPTIVE, MULTI-OBJECTIVE JOB SHOP SCHEDULING USING GENETIC ALGORITHMS." UKnowledge, 2008. http://uknowledge.uky.edu/gradschool_theses/518.

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This research proposes a method to solve the adaptive, multi-objective job shop scheduling problem. Adaptive scheduling is necessary to deal with internal and external disruptions faced in real life manufacturing environments. Minimizing the mean tardiness for jobs to effectively meet customer due date requirements and minimizing mean flow time to reduce the lead time jobs spend in the system are optimized simultaneously. An asexual reproduction genetic algorithm with multiple mutation strategies is developed to solve the multi-objective optimization problem. The model is tested for single day
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Books on the topic "Scheduling objectives"

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Mathematical programming and financial objectives for scheduling projects. Kluwer Academic Publishers, 2001.

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Kimms, Alf. Mathematical Programming and Financial Objectives for Scheduling Projects. Springer US, 2001. http://dx.doi.org/10.1007/978-1-4615-1453-4.

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Kimms, Alf. Mathematical Programming and Financial Objectives for Scheduling Projects. Springer US, 2001.

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Miller, Dennis P. Building a project work breakdown structure: Visualizing objectives, deliverables, activities, and schedules. Auerbach Publications, 2008.

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1968-, Schwindt Christoph, and Zimmermann Jürgen 1963-, eds. Project scheduling with time windows and scarce resources: Temporal and resource-constrained project scheduling with regular and nonregular objective functions. Springer, 2002.

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Garbett, K. S. Multi-objective scheduling and control of a nonlinear automotive powertrain. typescript, 1991.

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Shaw, Katharine Jane. Initial study of multi-objective genetic algorithms for scheduling the production of chilled ready meals. University of Sheffield, Dept. of Automatic Control and Systems Engineering, 1996.

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Building a Project Work Breakdown Structure: Visualizing Objectives, Deliverables, Activities, and Schedules. AUERBACH, 2008.

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Kimms, Alf. Mathematical Programming and Financial Objectives for Scheduling Products (International Series in Operations Research and Management Science, Volume 38) ... in Operations Research & Management Science). Springer, 2001.

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Project Scheduling with Time Windows and Scarce Resources: Temporal and Resource-Constrained Project Scheduling with Regular and Nonregular Objective Functions. 2nd ed. Springer, 2003.

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Book chapters on the topic "Scheduling objectives"

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Framinan, Jose M., Rainer Leisten, and Rubén Ruiz García. "Objectives." In Manufacturing Scheduling Systems. Springer London, 2014. http://dx.doi.org/10.1007/978-1-4471-6272-8_5.

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Hapke, Maciej, Andrzej Jaszkiewicz, and Roman Słowiński. "Fuzzy Multi-Mode Resource-Constrained Project Scheduling with multiple Objectives." In Project Scheduling. Springer US, 1999. http://dx.doi.org/10.1007/978-1-4615-5533-9_16.

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Topcuoglu, Haluk, and Can Sevilmis. "Task Scheduling with Conflicting Objectives." In Advances in Information Systems. Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/3-540-36077-8_36.

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Pan, Hongqi, and Chung-Hsing Yeh. "Fuzzy Project Scheduling with Multiple Objectives." In PRICAI 2004: Trends in Artificial Intelligence. Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-28633-2_139.

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Menouer, Tarek, Christophe Cérin, and Étienne Leclercq. "New Multi-objectives Scheduling Strategies in Docker SwarmKit." In Algorithms and Architectures for Parallel Processing. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-05057-3_8.

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Kendall, Graham, Barry McCollum, Frederico R. B. Cruz, Paul McMullan, and Lyndon While. "Scheduling English Football Fixtures: Consideration of Two Conflicting Objectives." In Hybrid Metaheuristics. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-30671-6_14.

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Wang, Binggang, Yunqing Rao, Xinyu Shao, and Mengchang Wang. "Scheduling Mixed-Model Assembly Lines with Cost Objectives by a Hybrid Algorithm." In Intelligent Robotics and Applications. Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-88518-4_41.

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Yu, Calvin K., and Pei-Fang Lee. "A Weighting Approach for Scheduling Multi-Product Assembly Line with Multiple Objectives." In Proceedings of the Institute of Industrial Engineers Asian Conference 2013. Springer Singapore, 2013. http://dx.doi.org/10.1007/978-981-4451-98-7_50.

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Albers, Susanne, and Alexander Eckl. "Explorable Uncertainty in Scheduling with Non-uniform Testing Times." In Approximation and Online Algorithms. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-80879-2_9.

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AbstractThe problem of scheduling with testing in the framework of explorable uncertainty models environments where some preliminary action can influence the duration of a task. In the model, each job has an unknown processing time that can be revealed by running a test. Alternatively, jobs may be run untested for the duration of a given upper limit. Recently, Dürr et al. [4] have studied the setting where all testing times are of unit size and have given lower and upper bounds for the objectives of minimizing the sum of completion times and the makespan on a single machine. In this paper, we extend the problem to non-uniform testing times and present the first competitive algorithms. The general setting is motivated for example by online user surveys for market prediction or querying centralized databases in distributed computing. Introducing general testing times gives the problem a new flavor and requires updated methods with new techniques in the analysis. We present constant competitive ratios for the objective of minimizing the sum of completion times in the deterministic case, both in the non-preemptive and preemptive setting. For the preemptive setting, we additionally give a first lower bound. We also present a randomized algorithm with improved competitive ratio. Furthermore, we give tight competitive ratios for the objective of minimizing the makespan, both in the deterministic and the randomized setting.
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Hammami, Hayfa, and Thomas Stützle. "A Computational Study of Neighborhood Operators for Job-Shop Scheduling Problems with Regular Objectives." In Evolutionary Computation in Combinatorial Optimization. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-55453-2_1.

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Conference papers on the topic "Scheduling objectives"

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Shafransky, Yakov M., T.-C. Edwin Cheng, and C.-T. Daniel Ng. "An approach for proving the NP-hardness of optimization problems with hard computable objectives." In Workshop on dynamic scheduling problems. Polish Mathematical Society, 2016. http://dx.doi.org/10.14708/isbn.978-83-937220-7-5p75-78.

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Maigha and Mariesa L. Crow. "Multi-objective electric vehicle scheduling considering customer and system objectives." In 2017 IEEE Manchester PowerTech. IEEE, 2017. http://dx.doi.org/10.1109/ptc.2017.7981275.

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Guo, Chengzhi, Ming Li, and Deming Lei. "Multi-objective flexible job shop scheduling problem with key objectives." In 2019 34rd Youth Academic Annual Conference of Chinese Association of Automation (YAC). IEEE, 2019. http://dx.doi.org/10.1109/yac.2019.8787585.

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Im, Sungjin, and Benjamin Moseley. "Online batch scheduling for flow objectives." In SPAA '13: 25th ACM Symposium on Parallelism in Algorithms and Architectures. ACM, 2013. http://dx.doi.org/10.1145/2486159.2486161.

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Hreinsson, Egill Benedikt. "Efficiencies and objectives in short term hydro scheduling." In 2016 IEEE Power and Energy Society General Meeting (PESGM). IEEE, 2016. http://dx.doi.org/10.1109/pesgm.2016.7741694.

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Xu, Ke, and Souran Manoochehri. "Job Shop Scheduling Optimization Using Genetic Algorithm With Global Criterion Technique." In ASME 2019 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/detc2019-98076.

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Abstract The Job Shop Scheduling Problem (JSSP) is a method which assigns multiple jobs to various machines. The large dimension of JSSP and the dynamic manufacturing environment have always been a difficult problem to optimize due to its size and complexity. In this study, three objective functions are selected namely, minimizing makespan, minimizing total cost and maximizing machine utilization. Genetic Algorithm (GA) is used to solve this scheduling problem. Lot size optimization technique is investigated for the potential of optimizing the makespan, total cost, and machine utilization obje
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Zhang, Heng, and Utpal Roy. "A Semantic Similarity Based Dispatching Rule Selection System for Job Shop Scheduling With Multiple Production Objectives." In ASME 2015 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/detc2015-47822.

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Job shop scheduling is an important activity which properly assigns production jobs to different manufacturing resources before production starts. Compared to other scheduling approaches that use optimal branch and bound algorithms, meta-heuristics, etc., the dispatching rule based approach has been widely used in the industry because it is easier to implement, and it yields reasonable solutions within a very short computation time. The dispatching rule based approach uses a selected single dispatching rule (e.g. Shortest Processing Time or Earliest Due Date) or a rule combination depending on
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Wang, Zuntong, Fei Qiao, and Qidi Wu. "Scheduling Semiconductor Wafer Fabrication with Optimization of Multiple objectives." In 2006 IEEE International Conference on Automation Science and Engineering. IEEE, 2006. http://dx.doi.org/10.1109/coase.2006.326889.

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Nouri, Nouha, and Talel Ladhari. "Minimizing Regular Objectives for Blocking Permutation Flow Shop Scheduling." In GECCO '15: Genetic and Evolutionary Computation Conference. ACM, 2015. http://dx.doi.org/10.1145/2739480.2754638.

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Krompass, Stefan, Harumi Kuno, Kevin Wilkinson, Umeshwar Dayal, and Alfons Kemper. "Adaptive query scheduling for mixed database workloads with multiple objectives." In the Third International Workshop. ACM Press, 2010. http://dx.doi.org/10.1145/1838126.1838127.

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Reports on the topic "Scheduling objectives"

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Bellabai, Robert, Jeen Robert, and Ramasubbu Rajkumar. Multi-objective Optimization Using Hybrid Algorithm and Its Application to Scheduling in Flow Shops. "Prof. Marin Drinov" Publishing House of Bulgarian Academy of Sciences, 2019. http://dx.doi.org/10.7546/crabs.2019.01.14.

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Amela, R., R. Badia, S. Böhm, R. Tosi, C. Soriano, and R. Rossi. D4.2 Profiling report of the partner’s tools, complete with performance suggestions. Scipedia, 2021. http://dx.doi.org/10.23967/exaqute.2021.2.023.

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This deliverable focuses on the proling activities developed in the project with the partner's applications. To perform this proling activities, a couple of benchmarks were dened in collaboration with WP5. The rst benchmark is an embarrassingly parallel benchmark that performs a read and then multiple writes of the same object, with the objective of stressing the memory and storage systems and evaluate the overhead when these reads and writes are performed in parallel. A second benchmark is dened based on the Continuation Multi Level Monte Carlo (C-MLMC) algorithm. While this algorithm is norm
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Brown, Willie, and Jonathan Alt. Investigating the USACE Operational Condition Assessment process current and future. Engineer Research and Development Center (U.S.), 2021. http://dx.doi.org/10.21079/11681/39999.

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The US Army Corps of Engineers operates, maintains, and manages more than $232 billion worth of the Nation’s water resource infrastructure and relies on the Operational Condition Assessment (OCA) process to determine the condition of the assets and their components. The sheer number of components, all of equal OCA scheduling priority, creates challenges in ensuring that assessments are conducted in a timely manner and that data generated are of sufficient quality to inform resource allocation decisions. This research applied methods from systems design to determine the OCA system “as-is” state
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