Academic literature on the topic 'Competitive algorithms'
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Journal articles on the topic "Competitive algorithms"
Im, Sungjin, Janardhan Kulkarni, and Kamesh Munagala. "Competitive Algorithms from Competitive Equilibria." Journal of the ACM 65, no. 1 (January 24, 2018): 1–33. http://dx.doi.org/10.1145/3136754.
Full textBender, Michael A., Jeremy T. Fineman, Mahnush Movahedi, Jared Saia, Varsha Dani, Seth Gilbert, Seth Pettie, and Maxwell Young. "Resource-Competitive Algorithms." ACM SIGACT News 46, no. 3 (September 2015): 57–71. http://dx.doi.org/10.1145/2818936.2818949.
Full textFiat, Amos, Richard M. Karp, Michael Luby, Lyle A. McGeoch, Daniel D. Sleator, and Neal E. Young. "Competitive paging algorithms." Journal of Algorithms 12, no. 4 (December 1991): 685–99. http://dx.doi.org/10.1016/0196-6774(91)90041-v.
Full textBudura, Georgeta, Corina Botoca, and Nicolae Miclău. "Competitive learning algorithms for data clustering." Facta universitatis - series: Electronics and Energetics 19, no. 2 (2006): 261–69. http://dx.doi.org/10.2298/fuee0602261b.
Full textLIU, ZHI-QIANG, and YAJUN ZHANG. "COMPENSATION COMPETITIVE LEARNING." International Journal of Computational Intelligence and Applications 01, no. 03 (September 2001): 303–22. http://dx.doi.org/10.1142/s1469026801000263.
Full textFiat, Amos, Yuval Rabani, and Yiftach Ravid. "Competitive k-server algorithms." Journal of Computer and System Sciences 48, no. 3 (June 1994): 410–28. http://dx.doi.org/10.1016/s0022-0000(05)80060-1.
Full textMajd, Amin, Golnaz Sahebi, Masoud Daneshtalab, Juha Plosila, Shahriar Lotfi, and Hannu Tenhunen. "Parallel imperialist competitive algorithms." Concurrency and Computation: Practice and Experience 30, no. 7 (January 16, 2018): e4393. http://dx.doi.org/10.1002/cpe.4393.
Full textWu, Yonghua, Guohun Zhu, Huaying Chen, and Jucun Qin. "WIN Algorithm for Discrete Online TSP." Journal of Advanced Computational Intelligence and Intelligent Informatics 15, no. 9 (November 20, 2011): 1199–202. http://dx.doi.org/10.20965/jaciii.2011.p1199.
Full textOsman, Hossam, and Moustafa M. Fahmy. "Probabilistic Winner-Take-All Learning Algorithm for Radial-Basis-Function Neural Classifiers." Neural Computation 6, no. 5 (September 1994): 927–43. http://dx.doi.org/10.1162/neco.1994.6.5.927.
Full textMohapatra, Prabhujit, Kedar Nath Das, Santanu Roy, Ram Kumar, and Nilanjan Dey. "A Novel Multi-Objective Competitive Swarm Optimization Algorithm." International Journal of Applied Metaheuristic Computing 11, no. 4 (October 2020): 114–29. http://dx.doi.org/10.4018/ijamc.2020100106.
Full textDissertations / Theses on the topic "Competitive algorithms"
Li, Rongbin, and 李榕滨. "New competitive algorithms for online job scheduling." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2014. http://hdl.handle.net/10722/197555.
Full textpublished_or_final_version
Computer Science
Doctoral
Doctor of Philosophy
Wong, Chiu Wai M. Eng Massachusetts Institute of Technology. "Competitive algorithms for online matching and vertex cover problems." Thesis, Massachusetts Institute of Technology, 2013. http://hdl.handle.net/1721.1/85521.
Full textCataloged from PDF version of thesis.
Includes bibliographical references (pages 73-75).
The past decade has witnessed an explosion of research on the online bipartite matching problem. Surprisingly, its dual problem, online bipartite vertex cover, has never been explicitly studied before. One of the motivation for studying this problem is that it significantly generalizes the classical ski rental problem. An instance of such problems specifies a bipartite graph G = (L, R, E) whose left vertices L are offline and right vertices arrive online one at a time. An algorithm must maintain a valid vertex cover from which no vertex can ever be removed. The objective is to minimize the size of the cover. In this thesis, we introduce a charging-based algorithmic framework for this problem as well as its generalizations. One immediate outcome is a simple analysis of an optimal 1/1-1/e- competitive algorithm for online bipartite vertex cover. By extending the charging-based analysis in various nontrivial ways, we also obtain optimal l_1 e-competitive algorithms for the edge-weighted and submodular versions of online bipartite vertex cover, which all match the best performance of ski rental. As an application, we show that by analyzing our algorithm in the primal-dual framework, our result on submodular vertex cover implies an optimal (1/1-1/e)-competitive algorithm for its dual, online bipartite submodular matching. This problem is a generalization of online bipartite matching and may have applications in display ad allocation. We consider also the more general scenario where all the vertices are online and the graph is not necessarily bipartite, which is known as the online fractional vertex cover and matching problems. Our contribution in this direction is a primal-dual 1.901-competitive (or 1/1.901 ~~ 0.526) algorithm for these problems. Previously, it was only known that they admit a simple well-known 2-competitive (or 1/2) greedy algorithm. Our result is the first successful attempt to beat the greedy algorithm for these two problems. Moreover, our algorithm for the online matching problem significantly generalizes the traditional online bipartite graph matching problem, where vertices from only one side of the bipartite graph arrive online. In particular, our algorithm improves upon the result of the fractional version of the online edge-selection problem in Blum et. al. (JACM '06). Finally, on the hardness side, we show that no randomized online algorithm can achieve a competitive ratio better than 1.753 and 0.625 for the online fractional vertex cover problem and the online fractional matching problem respectively, even for bipartite graphs.
by Chiu Wai Wong.
M. Eng.
Chan, Sze-hang, and 陳思行. "Competitive online job scheduling algorithms under different energy management models." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2013. http://hdl.handle.net/10722/206690.
Full textpublished_or_final_version
Computer Science
Doctoral
Doctor of Philosophy
McNeill, Dean K. "Adaptive visual representations for autonomous mobile robots using competitive learning algorithms." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp02/NQ35045.pdf.
Full textZhang, Kening. "A COMPETITIVE RECONFIGURATION APPROACH TO AUTONOMOUS FAULT HANDLING USING GENETIC ALGORITHMS." Doctoral diss., University of Central Florida, 2008. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/2319.
Full textPh.D.
School of Electrical Engineering and Computer Science
Engineering and Computer Science
Computer Engineering PhD
Premkumar, Aravind Preshant. "Competitive Algorithms and System for Multi-Robot Exploration of Unknown Environments." Thesis, Virginia Tech, 2017. http://hdl.handle.net/10919/78847.
Full textMaster of Science
Lorenz, Julian Michael. "Optimal trading algorithms : portfolio transactions, multiperiod portfolio selection, and competitive online search /." Zürich : ETH, 2008. http://e-collection.ethbib.ethz.ch/show?type=diss&nr=17746.
Full textLiu, Ming. "Design and Evaluation of Algorithms for Online Machine Scheduling Problems." Phd thesis, Ecole Centrale Paris, 2009. http://tel.archives-ouvertes.fr/tel-00453316.
Full textTsai, Carol Leanne. "Heuristic Algorithms for Agnostically Identifying the Globally Stable and Competitive Metastable Morphologies of Block Copolymer Melts." Thesis, University of California, Santa Barbara, 2019. http://pqdtopen.proquest.com/#viewpdf?dispub=13423067.
Full textBlock copolymers are composed of chemically distinct polymer chains that can be covalently linked in a variety of sequences and architectures. They are ubiquitous as ingredients of consumer products and also have applications in advanced plastics, drug delivery, advanced membranes, and next generation nano-lithographic patterning. The wide spectrum of possible block copolymer applications is a consequence of block copolymer self-assembly into periodic, meso-scale morphologies as a function of varying block composition and architecture in both melt and solution states, and the broad spectrum of physical properties that such mesophases afford.
Materials exploration and discovery has traditionally been pursued through an iterative process between experimental and theoretical/computational collaborations. This process is often implemented in a trial-and-error fashion, and from the computational perspective of generating phase diagrams, usually requires some existing knowledge about the competitive phases for a given system. Self-Consistent Field Theory (SCFT) simulations have proven to be both qualitatively and quantitatively accurate in the determination, or forward mapping, of block copolymer phases of a given system. However, it is possible to miss candidates. This is because SCFT simulations are highly dependent on their initial configurations, and the ability to map phase diagrams requires a priori knowledge of what the competing candidate morphologies are. The unguided search for the stable phase of a block copolymer of a given composition and architecture is a problem of global optimization. SCFT by itself is a local optimization method, so we can combine it with population-based heuristic algorithms geared at global optimization to facilitate forward mapping. In this dissertation, we discuss the development of two such methods: Genetic Algorithm + SCFT (GA-SCFT) and Particle Swarm Optimization + SCFT (PSO-SCFT). Both methods allow a population of configurations to explore the space associated with the numerous states accessible to a block copolymer of a given composition and architecture.
GA-SCFT is a real-space method in which a population of SCFT field configurations “evolves” over time. This is achieved by initializing the population randomly, allowing the configurations to relax to local basins of attraction using SCFT simulations, then selecting fit members (lower free energy structures) to recombine their fields and undergo mutations to generate a new “generation” of structures that iterate through this process. We present results from benchmark testing of this GA-SCFT technique on the canonical AB diblock copolymer melt, for which the theoretical phase diagram has long been established. The GA-SCFT algorithm successfully predicts many of the conventional mesophases from random initial conditions in large, 3-dimensional simulation cells, including hexagonally-packed cylinders, BCC-packed spheres, and lamellae, over a broad composition range and weak to moderate segregation strength. However, the GA-SCFT method is currently not effective at discovery of network phases, such as the Double-Gyroid (GYR) structure.
PSO-SCFT is a reciprocal space approach in which Fourier components of SCFT fields near the principal shell are manipulated. Effectively, PSO-SCFT facilitates the search through a space of reciprocal-space SCFT seeds which yield a variety of morphologies. Using intensive free energy as a fitness metric by which to compare these morphologies, the PSO-SCFT methodology allows us to agnostically identify low-lying competitive and stable morphologies. We present results for applying PSO-SCFT to conformationally symmetric diblock copolymers and a miktoarm star polymer, AB4, which offers a rich variety of competing sphere structures. Unlike the GA-SCFT method we previously presented, PSO-SCFT successfully predicts the double gyroid morphology in the AB-diblock. Furthermore, PSO-SCFT successfully recovers the A 15 morphology at a composition where it is expected to be stable in the miktoarm system, as well as several competitive metastable candidates, and a new sphere morphology belonging to the hexagonal space group 191, which has not been seen before in polymer systems. Thus, we believe the PSO-SCFT method provides a promising platform for screening for competitive structures in a given block copolymer system.
Nayyar, Krati. "Input Sensitive Analysis of a Minimum Metric Bipartite Matching Algorithm." Thesis, Virginia Tech, 2017. http://hdl.handle.net/10919/86518.
Full textMaster of Science
Books on the topic "Competitive algorithms"
Kothari, Ravi. A competitive genetic algorithm for single row facility layout. Ahmedabad: Indian Institute of Management, 2012.
Find full textBorodin, Allan. Online computation and competitive analysis. Cambridge, [Eng.]: Cambridge University Press, 1998.
Find full textKravets, O. Ya. Information systems competitive development: Algorithms and software for intranet interfaces. Yelm, WA: Science Book Publishing House, 2013.
Find full textKoren, Gilad. An optimal scheduling algorithm with a competitive factor for real-time systems. New York: Courant Institute of Mathematical Sciences, New York University, 1991.
Find full textKoren, Gilad. An optimal scheduling algorithm with a competitive factor for real-time systems. New York: Courant Institute of Mathematical Sciences, New York University, 1991.
Find full textValdez, Fevrier, Juan Barraza, and Patricia Melin. Hybrid Competitive Learning Method Using the Fireworks Algorithm and Artificial Neural Networks. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-47712-6.
Full textOnline Computation and Competitive Analysis. Cambridge University Press, 2005.
Find full textLaaksonen, Antti. Guide to Competitive Programming: Learning and Improving Algorithms Through Contests. Springer, 2020.
Find full textBuchbinder, Niv, and Joseph (Seffi) Naor. Design of Competitive Online Algorithms Via a Primal-Dual Approach. Now Publishers, 2009.
Find full textCompetitive Programming in Python: 128 Algorithms to Develop Your Coding Skills. University of Cambridge ESOL Examinations, 2020.
Find full textBook chapters on the topic "Competitive algorithms"
Bu, Tian-Ming. "Competitive Auction." In Encyclopedia of Algorithms, 364–66. New York, NY: Springer New York, 2016. http://dx.doi.org/10.1007/978-1-4939-2864-4_78.
Full textBu, Tian-Ming. "Competitive Auction." In Encyclopedia of Algorithms, 1–4. Berlin, Heidelberg: Springer Berlin Heidelberg, 2015. http://dx.doi.org/10.1007/978-3-642-27848-8_78-2.
Full textBu, Tian-Ming. "Competitive Auction." In Encyclopedia of Algorithms, 165–66. Boston, MA: Springer US, 2008. http://dx.doi.org/10.1007/978-0-387-30162-4_78.
Full textFiat, Amos, and Gerhard J. Woeginger. "Competitive analysis of algorithms." In Online Algorithms, 1–12. Berlin, Heidelberg: Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/bfb0029562.
Full textIrani, Sandy. "Competitive analysis of paging." In Online Algorithms, 52–73. Berlin, Heidelberg: Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/bfb0029564.
Full textFiat, Amos, and Gerhard J. Woeginger. "Competitive odds and ends." In Online Algorithms, 385–94. Berlin, Heidelberg: Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/bfb0029578.
Full textAspnes, James. "Competitive analysis of distributed algorithms." In Online Algorithms, 118–46. Berlin, Heidelberg: Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/bfb0029567.
Full textDeshmukh, Kaustubh, Andrew V. Goldberg, Jason D. Hartline, and Anna R. Karlin. "Truthful and Competitive Double Auctions." In Algorithms — ESA 2002, 361–73. Berlin, Heidelberg: Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/3-540-45749-6_34.
Full textBose, Prosenjit, Rolf Fagerberg, André van Renssen, and Sander Verdonschot. "Competitive Local Routing with Constraints." In Algorithms and Computation, 23–34. Berlin, Heidelberg: Springer Berlin Heidelberg, 2015. http://dx.doi.org/10.1007/978-3-662-48971-0_3.
Full textHarks, Tobias, Stefan Heinz, and Marc E. Pfetsch. "Competitive Online Multicommodity Routing." In Approximation and Online Algorithms, 240–52. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/11970125_19.
Full textConference papers on the topic "Competitive algorithms"
Im, Sungjin, Janardhan Kulkarni, and Kamesh Munagala. "Competitive algorithms from competitive equilibria." In STOC '14: Symposium on Theory of Computing. New York, NY, USA: ACM, 2014. http://dx.doi.org/10.1145/2591796.2591814.
Full textPaiton, Dylan M., Steven Shepard, Kwan Ho Ryan Chan, and Bruno A. Olshausen. "Subspace Locally Competitive Algorithms." In NICE '20: Neuro-inspired Computational Elements Workshop. New York, NY, USA: ACM, 2020. http://dx.doi.org/10.1145/3381755.3381765.
Full textCoester, Christian, Roie Levin, Joseph (Seffi) Naor, and Ohad Talmon. "Competitive Algorithms for Block-Aware Caching." In SPAA '22: 34th ACM Symposium on Parallelism in Algorithms and Architectures. New York, NY, USA: ACM, 2022. http://dx.doi.org/10.1145/3490148.3538567.
Full textKamali, Shahin, and Helen Xu. "Multicore Paging Algorithms Cannot Be Competitive." In SPAA '20: 32nd ACM Symposium on Parallelism in Algorithms and Architectures. New York, NY, USA: ACM, 2020. http://dx.doi.org/10.1145/3350755.3400270.
Full textBuchbinder, Niv, Shahar Chen, and Joseph (Seffi) Naor. "Competitive Analysis via Regularization." In Proceedings of the Twenty-Fifth Annual ACM-SIAM Symposium on Discrete Algorithms. Philadelphia, PA: Society for Industrial and Applied Mathematics, 2013. http://dx.doi.org/10.1137/1.9781611973402.32.
Full textPlyasunov, A., and A. Panin. "On three-level problem of competitive pricing." In NUMERICAL COMPUTATIONS: THEORY AND ALGORITHMS (NUMTA–2016): Proceedings of the 2nd International Conference “Numerical Computations: Theory and Algorithms”. Author(s), 2016. http://dx.doi.org/10.1063/1.4965327.
Full textManasse, Mark, Lyle McGeoch, and Daniel Sleator. "Competitive algorithms for on-line problems." In the twentieth annual ACM symposium. New York, New York, USA: ACM Press, 1988. http://dx.doi.org/10.1145/62212.62243.
Full textRozell, Christopher, Don Johnson, Richard Baraniuk, and Bruno Olshausen. "Locally Competitive Algorithms for Sparse Approximation." In 2007 IEEE International Conference on Image Processing. IEEE, 2007. http://dx.doi.org/10.1109/icip.2007.4379981.
Full textJinhong Xu, Weijun Xu, Jinling Li, and Yucheng Dong. "Competitive Algorithms about Online Reverse Auctions." In 2008 IEEE Congress on Evolutionary Computation (CEC). IEEE, 2008. http://dx.doi.org/10.1109/cec.2008.4631185.
Full textLiu, Hui, and David Y. Yun. "Competitive learning algorithms for image coding." In Aerospace Sensing, edited by Steven K. Rogers. SPIE, 1992. http://dx.doi.org/10.1117/12.140018.
Full textReports on the topic "Competitive algorithms"
Marty, Frédéric, and Thierry Warin. Deciphering Algorithmic Collusion: Insights from Bandit Algorithms and Implications for Antitrust Enforcement. CIRANO, December 2023. http://dx.doi.org/10.54932/iwpg7510.
Full textBrown, Zach, and Alexander MacKay. Competition in Pricing Algorithms. Cambridge, MA: National Bureau of Economic Research, May 2021. http://dx.doi.org/10.3386/w28860.
Full textIyer, Ganesh, and T. Tony Ke. Competitive Model Selection in Algorithmic Targeting. Cambridge, MA: National Bureau of Economic Research, March 2023. http://dx.doi.org/10.3386/w31002.
Full textParker, Robert, and Carleton Coffrin. The Grid Optimization Competition Benchmark Algorithm. Office of Scientific and Technical Information (OSTI), October 2023. http://dx.doi.org/10.2172/2202592.
Full textChang, Shu-jen, Ray Perlner, William E. Burr, Meltem Sonmez Turan, John M. Kelsey, Souradyuti Paul, and Lawrence E. Bassham. Third-Round Report of the SHA-3 Cryptographic Hash Algorithm Competition. Gaithersburg, MD: National Institute of Standards and Technology, November 2012. http://dx.doi.org/10.6028/nist.ir.7896.
Full textRegenscheid, Andrew, Ray Perlner, Shu-jen Chang, John Kelsey, Mridul Nandi, and Souradyuti Paul. Status report on the first round of the SHA-3 cryptographic hash algorithm competition. Gaithersburg, MD: National Institute of Standards and Technology, 2009. http://dx.doi.org/10.6028/nist.ir.7620.
Full textTuran, Meltem Sonmez, Ray Perlner, Lawrence E. Bassham, William Burr, Donghoon Chang, Shu-jen Chang, Morris J. Dworkin, John M. Kelsey, Souradyuti Paul, and Rene Peralta. Status report on the second round of the SHA-3 cryptographic hash algorithm competition. Gaithersburg, MD: National Institute of Standards and Technology, 2011. http://dx.doi.org/10.6028/nist.ir.7764.
Full textElacqua, Gregory, Anne Sofie Westh Olsen, and Santiago Velez-Ferro. Open configuration options The Market Design Approach to Teacher Assignment: Evidence from Ecuador. Inter-American Development Bank, September 2021. http://dx.doi.org/10.18235/0003824.
Full textDurovic, Mateja, and Franciszek Lech. A Consumer Law Perspective on the Commercialization of Data. Universitätsbibliothek J. C. Senckenberg, Frankfurt am Main, 2021. http://dx.doi.org/10.21248/gups.64577.
Full textSeginer, Ido, James Jones, Per-Olof Gutman, and Eduardo Vallejos. Optimal Environmental Control for Indeterminate Greenhouse Crops. United States Department of Agriculture, August 1997. http://dx.doi.org/10.32747/1997.7613034.bard.
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