Gotowe bibliografie tematyczne / Resource allocation

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Gotowa bibliografia na temat „Resource allocation”

Autor: Grafiati

Data publikacji: 4 czerwca 2021

Data aktualizacji: 25 lipca 2025

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Artykuły w czasopismach na temat "Resource allocation"

Edavalath, Sheena, and Manikandasaran S. Sundaram. "Cost-based resource allocation method for efficient allocation of resources in a heterogeneous cloud environment." Scientific Temper 14, no. 04 (2023): 1339–44. http://dx.doi.org/10.58414/scientifictemper.2023.14.4.41.

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Cloud computing is appealing due to features like adaptability, portability, utility service and on-demand service. Cloud resource providers are a source of computing, and each provider delivers different types of resources. In an active cloud environment, timely resource allocation is more important. In order to increase the effectiveness and user-friendliness of resource allocation in the heterogeneous cloud, the paper suggests an efficient cost-based resource allocation (ECRA) method and framework. In the heterogeneous cloud, there is no centralized resource allocation manager (CRAM) to get

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Zheng, Junjun. "Optimization of Resource Allocation of University Innovation and Entrepreneurship Education Based on Collaborative Filtering Algorithm." Journal of Electrical Systems 20, no. 3s (2024): 1853–62. http://dx.doi.org/10.52783/jes.1724.

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Entrepreneurship education resource allocation involves the strategic distribution of resources to support programs and initiatives aimed at fostering entrepreneurial skills and mindset among students. These resources can include funding, faculty support, curriculum development, mentorship opportunities, and access to networks and facilities. Effective resource allocation ensures that entrepreneurship education programs are adequately equipped to provide students with the knowledge, skills, and support needed to succeed as entrepreneurs. By prioritizing resource allocation to areas such as exp

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1Wang, Xiaojing *2 Tong Wei 1Ren Jia 1Ding Linjie 2. Liu Jingning. "WEIGHTED FAIRNESS RESOURCE ALLOCATION OF DISKS IN XEN." International Journal on Cloud Computing: Services and Architecture(IJCCSA) 2, June (2018): 01–10. https://doi.org/10.5281/zenodo.1438577.

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Virtualization improves the utilization ratio of resource, saving considerable amount of equipment, energy, management, etc. However, the benefits of virtualization are at the penalty of fairness but inefficient resource sharing. Various tasks in virtual domains often have different demands of resources. Therefore, allocation of resource and scheduling function are particularly important. A weighted max-min fairness allocation of disk resources is proposed in virtual platform. We focus on properties of sharing incentive, initial irrelevant and Pareto efficiency while designing the allocation a

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Edavalath, Sheena, and Manikandasaran S. Sundaram. "MARCR: Method of allocating resources based on cost of the resources in a heterogeneous cloud environment." Scientific Temper 14, no. 03 (2023): 576–81. http://dx.doi.org/10.58414/scientifictemper.2023.14.3.03.

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The cloud is an intelligent technology that provides requested services to users. It offers unlimited services for the users. Many small and medium-scale industries are startup their businesses to the next level using cloud computing. The services have been provided to the users by allocating the requested resources. Allocating resources without waste and with the finest allocation is a critical task in the cloud. This paper proposes a method for allocating resources using the cost of the resource. Resource allocation follows a priority system when allocating resources. The proposed method giv

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M, Sumathi, Niranjana B, Akshaya C, Ajitha M, and Bhavadharanee M. "Round Robin Based Efficient Resource Allocation and Utilization in an Organization." International Research Journal of Multidisciplinary Technovation 2, no. 2 (2020): 16–22. http://dx.doi.org/10.34256/irjmt2023.

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In an organization, resource allocation to a request is a complex task. Traditionally, resource allocation is done through manually with high time consumption. Similarly, collision is occurring for allocating a single resource to multiple requests. Thus, leads to complex problems and slow-down the working process. The existing resource allocation technique, allocate resources continuously to a specific request and omit another request. This kind of allocation technique also leads to lots of critical issues. That is the non-allocated process never gets a resource. To overcome these issues, the

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Sathish, Kuppani, and A. Rama Mohan Reddy. "Resource Allocation Mechanism with New Models for Grid Environment." International Journal of Grid and High Performance Computing 5, no. 2 (2013): 1–26. http://dx.doi.org/10.4018/jghpc.2013040101.

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Resource allocation is playing a vital role in grid environment because of the dynamic and heterogeneous nature of grid resources. Literature offers numerous studies and techniques to solve the grid resource allocation problem. Some of the drawbacks occur during grid resource allocation are low utilization, less economic reliability and increased waiting time of the jobs. These problems were occurred because of the inconsiderable level in the code of allocating right resources to right jobs, poor economic model and lack of provision to minimize the waiting time of jobs to get their resources.

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Artiushenko, Bohdan. "A Nucleolus-Based Approach for Cloud Resource Allocation." NaUKMA Research Papers. Computer Science 7 (May 12, 2025): 25–30. https://doi.org/10.18523/2617-3808.2024.7.25-30.

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Cloud computing has transformed organizational operations by enabling flexible resource allocation and reducing upfront hardware investments. However, the growing complexity of resource management, particularly for computing instances, has led to challenges in cost control and resource allocation. Fair allocation policies, such as max-min fairness and Dominant Resource Fairness, aim to distribute resources fairly among users. In recent years, the FinOps framework has emerged to address cloud cost management, empowering teams to manage their own resource usage and budgets. The allocation of res

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Lei, Xiaoli. "Resource Sharing Algorithm of Ideological and Political Course Based on Random Forest." Mathematical Problems in Engineering 2022 (May 21, 2022): 1–8. http://dx.doi.org/10.1155/2022/8765166.

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Three aspects of the system’s online resource distribution and application are built around subject, object, and intermediary resources. The invention relates to a method for allocating resources based on the random forest algorithm. The resource allocation process entails the following steps: constructing a mathematical model of the resource allocation process, defining a mathematical model of the resource allocation process for the target object, and designing the cost function. The training data set for random forest is constructed using the classification concept. It is based on the mathem

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Othmen, Salwa, Wahida Mansouri, and Radhia Khdhir. "Applying Artificial Intelligence Techniques For Resource Management in the Internet of Things (IoT)." International journal of electrical and computer engineering systems 16, no. 2 (2025): 183–94. https://doi.org/10.32985/ijeces.16.2.1.

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Internet of Things (IoT) applications in smart cities (SCs) rely on free-flow services streamlined by artificial intelligence (AI) paradigms. However, the nature of resource constraint prevails due to external infrastructure costs and energy-based allocations. Existing approaches to smart city resource distribution rely on static thresholds or reactive responses, which are not always sufficient. These approaches may limit system performance and scalability in dynamic IoT environments owing to increased energy consumption, postponed resource allocation, and frequent device failures. This articl

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Willmott, Yvonne. "Resource allocation." Nursing Standard 4, no. 28 (1990): 46. http://dx.doi.org/10.7748/ns.4.28.46.s51.

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Rozprawy doktorskie na temat "Resource allocation"

AuYoung, Alvin. "Practical market-based resource allocation." Diss., [La Jolla] : University of California, San Diego, 2010. http://wwwlib.umi.com/cr/ucsd/fullcit?p3397175.

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Thesis (Ph. D.)--University of California, San Diego, 2010. Title from first page of PDF file (viewed March 29, 2010). Available via ProQuest Digital Dissertations. Vita. Includes bibliographical references (p. 146-155).

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Choueiry, Berthe Y. Choueiry Berthe Yazid. "Abstraction methods for resource allocation /." [S.l.] : [s.n.], 1994. http://library.epfl.ch/theses/?nr=1292.

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Muñoz, i. Solà Víctor. "Robustness on resource allocation problems." Doctoral thesis, Universitat de Girona, 2011. http://hdl.handle.net/10803/7753.

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En problemes d'assignació de recursos, normalment s'han de tenir en compte les incerteses que poden provocar canvis en les dades inicials. Aquests canvis dificulten l'aplicabilitat de les planificacions que s'hagin fet inicialment. Aquesta tesi se centra en l'elaboració de tècniques que consideren la incertesa alhora de cercar solucions robustes, és a dir solucions que puguin continuar essent vàlides encara que hi hagi canvis en l'entorn. Particularment, introduïm el concepte de robustesa basat en reparabilitat, on una solució robusta és una que pot ser reparada fàcilment en cas que hi hag

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Tureli, Didem Kivanc. "Resource allocation for multicarrier communications /." Thesis, Connect to this title online; UW restricted, 2005. http://hdl.handle.net/1773/6068.

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Lai, John Kwang. "Truthful and Fair Resource Allocation." Thesis, Harvard University, 2013. http://dissertations.umi.com/gsas.harvard:10928.

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How should we divide a good or set of goods among a set of agents? There are various constraints that we can consider. We consider two particular constraints. The first is fairness - how can we find fair allocations? The second is truthfulness - what if we do not know agents valuations for the goods being allocated? What if these valuations need to be elicited, and agents will misreport their valuations if it is beneficial? Can we design procedures that elicit agents' true valuations while preserving the quality of the allocation? We consider truthful and fair resource allocation procedures th

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Reid, Jane Margaret. "Resource allocation during avian incubation." Thesis, University of Glasgow, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.392460.

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Owen, Robert Wyn. "Strategies for stochastic resource allocation." Thesis, University of Newcastle Upon Tyne, 1991. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.315563.

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Robinson, Edward Robert. "Resource allocation via competing marketplaces." Thesis, University of Birmingham, 2011. http://etheses.bham.ac.uk//id/eprint/1647/.

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This thesis proposes a novel method for allocating multi-attribute computational resources via competing marketplaces. Trading agents, working on behalf of resource consumers and providers, choose to trade in resource markets where the resources being traded best align with their preferences and constraints. Market-exchange agents, in competition with each other, attempt to provide resource markets that attract traders, with the goal of maximising their profit. Because exchanges can only partially observe global supply and demand schedules, novel strategies are required to automate their searc

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Nguyen, Quang (Quang Duc) 1972. "Optimizing engineering analysis resource allocation." Thesis, Massachusetts Institute of Technology, 2001. http://hdl.handle.net/1721.1/84521.

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Thesis (M.B.A.)--Massachusetts Institute of Technology, Sloan School of Management; and, (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering; in conjunction with the Leaders for Manufacturing Program at MIT, 2001. Includes bibliographical references (p. 72-73). by Quang Nguyen. S.M. M.B.A.

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Lien, Yuan-Chuan. "Resource allocation in matching markets /." May be available electronically:, 2007. http://proquest.umi.com/login?COPT=REJTPTU1MTUmSU5UPTAmVkVSPTI=&clientId=12498.

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Książki na temat "Resource allocation"

Ushakov, Igor A., ed. Optimal Resource Allocation. John Wiley & Sons, Inc., 2013. http://dx.doi.org/10.1002/9781118400715.

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Luss, Hanan. Equitable Resource Allocation. John Wiley & Sons, Inc., 2012. http://dx.doi.org/10.1002/9781118449189.

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Langholtz, Harvey J., Antoinette T. Marty, Christopher T. Ball, and Eric C. Nolan. Resource-Allocation Behavior. Springer US, 2003. http://dx.doi.org/10.1007/978-1-4615-1131-1.

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1948-, Langholtz Harvey J., ed. Resource-allocation behavior. Kluwer Academic Publishers, 2003.

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A, Bazzaz F., and Grace J. 1945-, eds. Plant resource allocation. Academic Press, 1997.

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United States. General Accounting Office. RCED. BLM resource allocation. The Office, 1992.

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United States. General Accounting Office. RCED., ed. BLM resource allocation. The Office, 1992.

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Resources, Great Britain National Assembly for Wales National Steering Group on the Allocation of NHS. NHS resource allocation review. National Assembly for Wales = Cynulliad Cenedlaethol Cymru, 2001.

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Chuku, Dike. Resource allocation in education. Andisen Nigeria, 1987.

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Great Britain. National Assembly for Wales. National Steering Group on the Allocation of NHS Resources. NHS resource allocation review. National Assembly for Wales = Cynulliad Cenedlaethol Cymru, 2001.

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Części książek na temat "Resource allocation"

Huo, Jiazhen, and Zhisheng Hong. "Resource Allocation." In Service Science in China. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-34497-8_6.

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Trsek, Henning. "Resource Allocation." In Isochronous Wireless Network for Real-time Communication in Industrial Automation. Springer Berlin Heidelberg, 2016. http://dx.doi.org/10.1007/978-3-662-49158-4_6.

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Srikant, R. "Resource Allocation." In Systems & Control: Foundations & Applications. Birkhäuser Boston, 2004. http://dx.doi.org/10.1007/978-0-8176-8216-3_2.

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Gillman, Richard Alan, and David Housman. "Resource Allocation." In Game Theory. Chapman and Hall/CRC, 2019. http://dx.doi.org/10.1201/9781315156880-9.

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Bland, Lucie M., Christine Li, Tom Kompas, Long Chu, Hoa-Thi-Minh Nguyen, and Susan M. Hester. "Resource Allocation." In Biosecurity. CRC Press, 2024. http://dx.doi.org/10.1201/9781003253204-13.

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Weik, Martin H. "resource allocation." In Computer Science and Communications Dictionary. Springer US, 2000. http://dx.doi.org/10.1007/1-4020-0613-6_16223.

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ten Have, Henk, and Maria do Céu Patrão Neves. "Resource Allocation." In Dictionary of Global Bioethics. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-54161-3_449.

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Andrade, Gabriel. "Resource allocation." In Medical Ethics and Moral Psychology. Routledge, 2025. https://doi.org/10.4324/9781003541653-6.

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Zili, He. "Resource Allocation." In Dictionary of Contemporary Chinese Economics. Springer Nature Singapore, 2025. https://doi.org/10.1007/978-981-97-4036-9_27.

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Langholtz, Harvey J., Antoinette T. Marty, Christopher T. Ball, and Eric C. Nolan. "An Introduction to Resource-Allocation Behavior." In Resource-Allocation Behavior. Springer US, 2003. http://dx.doi.org/10.1007/978-1-4615-1131-1_1.

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Streszczenia konferencji na temat "Resource allocation"

Chen, Shenghui, Yagiz Savas, Mustafa O. Karabag, Brian M. Sadler, and Ufuk Topcu. "Deceptive Planning for Resource Allocation." In 2024 American Control Conference (ACC). IEEE, 2024. http://dx.doi.org/10.23919/acc60939.2024.10644373.

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Kyropoulou, Maria, Warut Suksompong, and Alexandros A. Voudouris. "Almost Envy-Freeness in Group Resource Allocation." In Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/57.

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We study the problem of fairly allocating indivisible goods between groups of agents using the recently introduced relaxations of envy-freeness. We consider the existence of fair allocations under different assumptions on the valuations of the agents. In particular, our results cover cases of arbitrary monotonic, responsive, and additive valuations, while for the case of binary valuations we fully characterize the cardinalities of two groups of agents for which a fair allocation can be guaranteed with respect to both envy-freeness up to one good (EF1) and envy-freeness up to any good (EFX). Mo

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Bott, Terry F., and Stephen W. Eisenhawer. "A Structured Approach to Resource Allocation." In ASME/JSME 2004 Pressure Vessels and Piping Conference. ASMEDC, 2004. http://dx.doi.org/10.1115/pvp2004-2998.

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Allocating limited resources among competing candidates is an important problem in management. In this paper, we describe a structured and flexible approach to resource allocation using logic-evolved decision (LED) analysis. LED analysis uses logic models to generate an exhaustive set of competing alternatives and the inferential model that is used for preference ordering of these alternatives. The inferential models can use data in numerical, linguistic, or mixed forms; uncertainty in the evaluation results can be expressed using probabilistic- or linguistic-based methods. We illustrate the u

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Bei, Xiaohui, Alexander Lam, Xinhang Lu, and Warut Suksompong. "Welfare Loss in Connected Resource Allocation." In Thirty-Third International Joint Conference on Artificial Intelligence {IJCAI-24}. International Joint Conferences on Artificial Intelligence Organization, 2024. http://dx.doi.org/10.24963/ijcai.2024/294.

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We study the allocation of indivisible goods that form an undirected graph and investigate the worst-case welfare loss when requiring that each agent must receive a connected subgraph. Our focus is on both egalitarian and utilitarian welfare. Specifically, we introduce the concept of egalitarian (resp., utilitarian) price of connectivity, which captures the worst-case ratio between the optimal egalitarian (resp., utilitarian) welfare among all allocations and that among the connected allocations. We provide tight or asymptotically tight bounds on the price of connectivity for various large cla

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Schubert, Martin, and Holger Boche. "Robust Resource Allocation." In 2006 IEEE Information Theory Workshop. IEEE, 2006. http://dx.doi.org/10.1109/itw.2006.322880.

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Schubert, Martin, and Holger Boche. "Robust Resource Allocation." In 2006 IEEE Information Theory Workshop - ITW '06 Chengdu. IEEE, 2006. http://dx.doi.org/10.1109/itw2.2006.323695.

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Funaro, Liran, Orna Agmon Ben-Yehuda, and Assaf Schuster. "Stochastic resource allocation." In the 15th ACM SIGPLAN/SIGOPS International Conference. ACM Press, 2019. http://dx.doi.org/10.1145/3313808.3313815.

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Patil, Sulakshana, Vijaya Rajeshwarkar, VaIshali Velhal, and Pravin Latne. "Resource allocation management." In 2014 IEEE Global Conference on Wireless Computing and Networking (GCWCN). IEEE, 2014. http://dx.doi.org/10.1109/gcwcn.2014.7030896.

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Ahmed, Rafeeq, Mohammed A. Qadeer, and Musheer Ahmad. "Bandwidth Resource Allocation." In 2009 International Conference on Future Computer and Communication (ICFCC). IEEE, 2009. http://dx.doi.org/10.1109/icfcc.2009.133.

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Sanford, Caitlyn, Sarah Valley, Kaylee Keegan, Reed Foote, and Natalie Cherbaka. "Resource Allocation Playbook." In 2024 Systems and Information Engineering Design Symposium (SIEDS). IEEE, 2024. http://dx.doi.org/10.1109/sieds61124.2024.10534700.

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Raporty organizacyjne na temat "Resource allocation"

Stokes, Brian J., and Gregory S. Parnell. Alternate Resource Allocation Techniques. Defense Technical Information Center, 2002. http://dx.doi.org/10.21236/ada405460.

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Müller, Benito. Performance-based formulaic resource allocation. Oxford Institute for Energy Studies, 2014. http://dx.doi.org/10.26889/9781907555862.

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Hansen, Jeff, Scott Hissam, B. C. Meyers, et al. Resource Allocation in Dynamic Environments. Defense Technical Information Center, 2012. http://dx.doi.org/10.21236/ada609913.

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Keller, William C. The Defense Resource Allocation Process. Defense Technical Information Center, 1997. http://dx.doi.org/10.21236/ada326185.

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Kogan, Leonid, Dimitris Papanikolaou, Amit Seru, and Noah Stoffman. Technological Innovation, Resource Allocation, and Growth. National Bureau of Economic Research, 2012. http://dx.doi.org/10.3386/w17769.

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Leivent, Jonathan I., and Ann M. Wollrath. Resource Allocation in Distributed Memory Multiprocessing. Defense Technical Information Center, 1991. http://dx.doi.org/10.21236/ada243165.

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Kozlowski, Steve W., and Richard P. DeShon. Optimizing Dynamic Resource Allocation in Teamwork. Defense Technical Information Center, 2008. http://dx.doi.org/10.21236/ada478848.

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Yao, Y., T. Edmunds, D. Papageorgiou, and R. Alvarez. Optimal Resource Allocation in Electrical Network Defense. Office of Scientific and Technical Information (OSTI), 2004. http://dx.doi.org/10.2172/15009766.

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Feldstein, Martin. The CEA: From Stabilization to Resource Allocation. National Bureau of Economic Research, 1997. http://dx.doi.org/10.3386/w5908.

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Newes, Emily, Brian Bush, Daniel Inman, et al. Biomass Resource Allocation among Competing End Uses. Office of Scientific and Technical Information (OSTI), 2012. http://dx.doi.org/10.2172/1041351.

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