Bibliografias temáticas / Competitive algorithms

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Literatura científica selecionada sobre o tema "Competitive algorithms"

Autor: Grafiati

Publicado: 25 de maio de 2024

Última modificação: 31 de julho de 2025

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Artigos de revistas sobre o assunto "Competitive algorithms"

Im, Sungjin, Janardhan Kulkarni, and Kamesh Munagala. "Competitive Algorithms from Competitive Equilibria." Journal of the ACM 65, no. 1 (2018): 1–33. http://dx.doi.org/10.1145/3136754.

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Bender, Michael A., Jeremy T. Fineman, Mahnush Movahedi, et al. "Resource-Competitive Algorithms." ACM SIGACT News 46, no. 3 (2015): 57–71. http://dx.doi.org/10.1145/2818936.2818949.

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Fiat, 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 (1991): 685–99. http://dx.doi.org/10.1016/0196-6774(91)90041-v.

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Budura, 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.

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This paper presents and discusses some competitive learning algorithms for data clustering. A new competitive learning algorithm, named the dynamically penalized rival competitive learning algorithm (DPRCL), is introduced and studied. It is a variant of the rival penalized competitive algorithm [1] and it performs appropriate clustering without knowing the clusters number, by automatically driving the extra seed points far away from the input data set. It does not have the 'dead units' problem. Simulations results, performed in different conditions, are presented showing that the performance o

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LIU, ZHI-QIANG, and YAJUN ZHANG. "COMPENSATION COMPETITIVE LEARNING." International Journal of Computational Intelligence and Applications 01, no. 03 (2001): 303–22. http://dx.doi.org/10.1142/s1469026801000263.

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In general, in competitive learning the requirement for the initial number of prototypes is a difficult task, as we do not usually know the number of clusters in the input data a priori. The behavior and performance of the competitive algorithms are very sensitive to the initial locations and number of the prototypes. In this paper after investigating several important competitive learning paradigms, we present compensation techniques for overcoming the problems in competitive learning. Our experimental results show that competition with compensation can improve the performance of the learning

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Wu, 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 (2011): 1199–202. http://dx.doi.org/10.20965/jaciii.2011.p1199.

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Traveling Salesman Problem (TSP) which is proved as an NP-Complete problem is solved by many algorithms. In this paper, we propose online TSP which is based on general discrete metric space. A Waiting-If-Necessary (WIN) algorithm is proposed that involves with increasing cost caused by zealous algorithms and unnecessary waiting caused by cautious algorithms. We measure the performance of the WIN algorithm using competitive analysis and found that it is a 2-competitive algorithm. The competitive ratio of theWIN algorithm can be improved by setting parameterT0.

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Fiat, Amos, Yuval Rabani, and Yiftach Ravid. "Competitive k-server algorithms." Journal of Computer and System Sciences 48, no. 3 (1994): 410–28. http://dx.doi.org/10.1016/s0022-0000(05)80060-1.

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Majd, 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 (2018): e4393. http://dx.doi.org/10.1002/cpe.4393.

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Osman, Hossam, and Moustafa M. Fahmy. "Probabilistic Winner-Take-All Learning Algorithm for Radial-Basis-Function Neural Classifiers." Neural Computation 6, no. 5 (1994): 927–43. http://dx.doi.org/10.1162/neco.1994.6.5.927.

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This paper proposes a new adaptive competitive learning algorithm called “the probabilistic winner-take-all.” The algorithm is based on a learning scheme developed by Agrawala within the statistical pattern recognition literature (Agrawala 1970). Its name stems from the fact that for a given input pattern once each competitor computes the probability of being the one that generated this pattern, the computed probabilities are utilized to probabilistically choose a winner. Then, only this winner is permitted to learn. The learning rule of the algorithm is derived for three different cases. Its

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Mohapatra, 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 (2020): 114–29. http://dx.doi.org/10.4018/ijamc.2020100106.

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In this article, a new algorithm, namely the multi-objective competitive swarm optimizer (MOCSO), is introduced to handle multi-objective problems. The algorithm has been principally motivated from the competitive swarm optimizer (CSO) and the NSGA-II algorithm. In MOCSO, a pair wise competitive scenario is presented to achieve the dominance relationship between two particles in the population. In each pair wise competition, the particle that dominates the other particle is considered the winner and the other is consigned as the loser. The loser particles learn from the respective winner parti

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Teses / dissertações sobre o assunto "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.

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Job scheduling, which greatly impacts on the system performance, is a fundamental problem in computer science. In this thesis, we study three kinds of scheduling problems, that is, deadline scheduling, due date scheduling, and flow time scheduling. Traditionally, the major concern for scheduling problems is the system performance, i.e. the “Quality of Service" (QoS). Different scheduling problems use different QoS measurements. For deadline scheduling, the most common QoS to optimize is the throughput; for due date scheduling, it is the total quoted lead time; and for flow time scheduling, it

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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.

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Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2013.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (pages 73-75).<br>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 =

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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.

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Online flow-time scheduling is a fundamental problem in computer science and has been extensively studied for years. It is about how to design a scheduler to serve computer jobs with unpredictable arrival times and varying sizes and priorities so as to minimize the total flow time (better understood as response time) of jobs. It has many applications, most notable in the operating of server farms. As energy has become an important issue, the design of scheduler also has to take power management into consideration, for example, how to scale the speed of the processors dynamically. The objective

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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.

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Zhang, 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.

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In this dissertation, a novel self-repair approach based on Consensus Based Evaluation (CBE) for autonomous repair of SRAM-based Field Programmable Gate Arrays (FPGAs) is developed, evaluated, and refined. An initial population of functionally identical (same input-output behavior), yet physically distinct (alternative design or place-and-route realization) FPGA configurations is produced at design time. During run-time, the CBE approach ranks these alternative configurations after evaluating their discrepancy relative to the consensus formed by the population. Through runtime competition, fau

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Premkumar, Aravind Preshant. "Competitive Algorithms and System for Multi-Robot Exploration of Unknown Environments." Thesis, Virginia Tech, 2017. http://hdl.handle.net/10919/78847.

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We present an algorithm to explore an orthogonal polygon using a team of p robots. This algorithm combines ideas from information-theoretic exploration algorithms and computational geometry based exploration algorithms. The algorithm is based on a single-robot polygon exploration algorithm and a tree exploration algorithm. We show that the exploration time of our algorithm is competitive (as a function of p) with respect to the offline optimal exploration algorithm. We discuss how this strategy can be adapted to real-world settings to deal with noisy sensors. In addition to theoretical analysi

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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.

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Liu, Ming. "Design and Evaluation of Algorithms for Online Machine Scheduling Problems." Phd thesis, Ecole Centrale Paris, 2009. http://tel.archives-ouvertes.fr/tel-00453316.

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Dans cette thèse, nous proposons et évaluons des algorithmes pour résoudre des problèmes d'ordonnancement en ligne. Pendant des décennies, les études en ordonnancement considèrent des modèles déterministes où toutes les informations nécessaires pour la définition du problème sont supposées connues à l'avance. Cette hypothèse n'est généralement pas réaliste. Ceci a motivé les études sur l'ordonnancement en ligne. Dans un problème d'ordonnancement en ligne, un algorithme doit prendre des décisions sans connaissance du futur. L'analyse compétitive est généralement la méthode utilisée pour évaluer

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Tsai, 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.

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<p> Block 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 spectru

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Nayyar, Krati. "Input Sensitive Analysis of a Minimum Metric Bipartite Matching Algorithm." Thesis, Virginia Tech, 2017. http://hdl.handle.net/10919/86518.

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In various business and military settings, there is an expectation of on-demand delivery of supplies and services. Typically, several delivery vehicles (also called servers) carry these supplies. Requests arrive one at a time and when a request arrives, a server is assigned to this request at a cost that is proportional to the distance between the server and the request. Bad assignments will not only lead to larger costs but will also create bottlenecks by increasing delivery time. There is, therefore, a need to design decision-making algorithms that produce cost-effective assignments of serve

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Livros sobre o assunto "Competitive algorithms"

Kothari, Ravi. A competitive genetic algorithm for single row facility layout. Indian Institute of Management, 2012.

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Borodin, Allan. Online computation and competitive analysis. Cambridge University Press, 1998.

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Kravets, O. Ya. Information systems competitive development: Algorithms and software for intranet interfaces. Science Book Publishing House, 2013.

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Koren, Gilad. An optimal scheduling algorithm with a competitive factor for real-time systems. Courant Institute of Mathematical Sciences, New York University, 1991.

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Koren, Gilad. An optimal scheduling algorithm with a competitive factor for real-time systems. Courant Institute of Mathematical Sciences, New York University, 1991.

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Valdez, Fevrier, Juan Barraza, and Patricia Melin. Hybrid Competitive Learning Method Using the Fireworks Algorithm and Artificial Neural Networks. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-47712-6.

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Leal, Juan Ruiz, and David Esparza Alba. Algorithms: For Competitive Programming. Independently Published, 2021.

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Laaksonen, Antti. Guide to Competitive Programming: Learning and Improving Algorithms Through Contests. Springer, 2020.

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Buchbinder, Niv, and Joseph (Seffi) Naor. Design of Competitive Online Algorithms Via a Primal-Dual Approach. Now Publishers, 2009.

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Guide to Competitive Programming: Learning and Improving Algorithms Through Contests. Springer International Publishing AG, 2024.

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Capítulos de livros sobre o assunto "Competitive algorithms"

Bu, Tian-Ming. "Competitive Auction." In Encyclopedia of Algorithms. Springer New York, 2016. http://dx.doi.org/10.1007/978-1-4939-2864-4_78.

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Bu, Tian-Ming. "Competitive Auction." In Encyclopedia of Algorithms. Springer Berlin Heidelberg, 2015. http://dx.doi.org/10.1007/978-3-642-27848-8_78-2.

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Bu, Tian-Ming. "Competitive Auction." In Encyclopedia of Algorithms. Springer US, 2008. http://dx.doi.org/10.1007/978-0-387-30162-4_78.

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Fiat, Amos, and Gerhard J. Woeginger. "Competitive analysis of algorithms." In Online Algorithms. Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/bfb0029562.

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Irani, Sandy. "Competitive analysis of paging." In Online Algorithms. Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/bfb0029564.

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Fiat, Amos, and Gerhard J. Woeginger. "Competitive odds and ends." In Online Algorithms. Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/bfb0029578.

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Aspnes, James. "Competitive analysis of distributed algorithms." In Online Algorithms. Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/bfb0029567.

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Deshmukh, Kaustubh, Andrew V. Goldberg, Jason D. Hartline, and Anna R. Karlin. "Truthful and Competitive Double Auctions." In Algorithms — ESA 2002. Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/3-540-45749-6_34.

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Bose, Prosenjit, Rolf Fagerberg, André van Renssen, and Sander Verdonschot. "Competitive Local Routing with Constraints." In Algorithms and Computation. Springer Berlin Heidelberg, 2015. http://dx.doi.org/10.1007/978-3-662-48971-0_3.

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Harks, Tobias, Stefan Heinz, and Marc E. Pfetsch. "Competitive Online Multicommodity Routing." In Approximation and Online Algorithms. Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/11970125_19.

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Trabalhos de conferências sobre o assunto "Competitive algorithms"

Dasgupta, Anubhab, Vedant Zope, and Asrul Harun Ismail. "Implementation of the Bees Algorithm for UAV Mission Plan." In 14th International Seminar on Industrial Engineering and Management. Trans Tech Publications Ltd, 2025. https://doi.org/10.4028/p-nad6qa.

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The increasing use of Unmanned Aerial Vehicles (UAVs) in various applications, such as military operations and civilian tasks, has created a demand for efficient algorithms to plan their mission. This study explores the use of the Bees Algorithm (BA), a nature-inspired optimisation method, to solve two main problems in UAV mission planning: the UAV collision avoidance problem (UCAP) and the Asymmetric TSP (ATSP). Results of comparison between the proposed algorithm and other metaheuristic algorithms indicate that BA can produce competitive solutions. However, the study also found that the BA h

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Im, Sungjin, Janardhan Kulkarni, and Kamesh Munagala. "Competitive algorithms from competitive equilibria." In STOC '14: Symposium on Theory of Computing. ACM, 2014. http://dx.doi.org/10.1145/2591796.2591814.

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Paiton, Dylan M., Steven Shepard, Kwan Ho Ryan Chan, and Bruno A. Olshausen. "Subspace Locally Competitive Algorithms." In NICE '20: Neuro-inspired Computational Elements Workshop. ACM, 2020. http://dx.doi.org/10.1145/3381755.3381765.

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Coester, 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. ACM, 2022. http://dx.doi.org/10.1145/3490148.3538567.

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Kamali, Shahin, and Helen Xu. "Multicore Paging Algorithms Cannot Be Competitive." In SPAA '20: 32nd ACM Symposium on Parallelism in Algorithms and Architectures. ACM, 2020. http://dx.doi.org/10.1145/3350755.3400270.

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Buchbinder, Niv, Shahar Chen, and Joseph (Seffi) Naor. "Competitive Analysis via Regularization." In Proceedings of the Twenty-Fifth Annual ACM-SIAM Symposium on Discrete Algorithms. Society for Industrial and Applied Mathematics, 2013. http://dx.doi.org/10.1137/1.9781611973402.32.

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Plyasunov, 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.

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Manasse, Mark, Lyle McGeoch, and Daniel Sleator. "Competitive algorithms for on-line problems." In the twentieth annual ACM symposium. ACM Press, 1988. http://dx.doi.org/10.1145/62212.62243.

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Rozell, 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.

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Jinhong 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.

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Relatórios de organizações sobre o assunto "Competitive algorithms"

Marty, Frédéric, and Thierry Warin. Deciphering Algorithmic Collusion: Insights from Bandit Algorithms and Implications for Antitrust Enforcement. CIRANO, 2023. http://dx.doi.org/10.54932/iwpg7510.

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This paper examines algorithmic collusion from legal and economic perspectives, highlighting the growing role of algorithms in digital markets and their potential for anti-competitive behavior. Using bandit algorithms as a model, traditionally applied in uncertain decision-making contexts, we illuminate the dynamics of implicit collusion without overt communication. Legally, the challenge is discerning and classifying these algorithmic signals, especially as unilateral communications. Economically, distinguishing between rational pricing and collusive patterns becomes intricate with algorithm-

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Brown, Zach, and Alexander MacKay. Competition in Pricing Algorithms. National Bureau of Economic Research, 2021. http://dx.doi.org/10.3386/w28860.

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Iyer, Ganesh, and T. Tony Ke. Competitive Model Selection in Algorithmic Targeting. National Bureau of Economic Research, 2023. http://dx.doi.org/10.3386/w31002.

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Parker, Robert, and Carleton Coffrin. The Grid Optimization Competition Benchmark Algorithm. Office of Scientific and Technical Information (OSTI), 2023. http://dx.doi.org/10.2172/2202592.

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Chang, Shu-jen, Ray Perlner, William E. Burr, et al. Third-Round Report of the SHA-3 Cryptographic Hash Algorithm Competition. National Institute of Standards and Technology, 2012. http://dx.doi.org/10.6028/nist.ir.7896.

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Regenscheid, 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. National Institute of Standards and Technology, 2009. http://dx.doi.org/10.6028/nist.ir.7620.

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Turan, Meltem Sonmez, Ray Perlner, Lawrence E. Bassham, et al. Status report on the second round of the SHA-3 cryptographic hash algorithm competition. National Institute of Standards and Technology, 2011. http://dx.doi.org/10.6028/nist.ir.7764.

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Tarufelli, Brittany, Brent Eldridge, Li He, et al. Energy Storage Participation Algorithm Competition Overview: Market simulation, divisions, stages, storage attributes, and scoring. Office of Scientific and Technical Information (OSTI), 2024. http://dx.doi.org/10.2172/2474989.

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Elacqua, 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, 2021. http://dx.doi.org/10.18235/0003824.

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We study the advantages, trade-offs, and challenges of employing a centralized rule to determine the allocation of teachers to schools. Data come from the centralized teacher assignment program in Ecuador, "Quiero ser Maestro," conducted by the Ministry of Education. Notably, in 2019 the program transitioned from a priority based algorithm to a strategy proof mechanism, similar to the change introduced in Boston in 2005 to assign students to schools. Using the reported preferences, we conduct a counterfactual analysis and nd substantive evidence that the adjustment in algorithm resulted in gre

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Durovic, 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.

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Commercialization of consumers’ personal data in the digital economy poses serious, both conceptual and practical, challenges to the traditional approach of European Union (EU) Consumer Law. This article argues that mass-spread, automated, algorithmic decision-making casts doubt on the foundational paradigm of EU consumer law: consent and autonomy. Moreover, it poses threats of discrimination and under- mining of consumer privacy. It is argued that the recent legislative reaction by the EU Commission, in the form of the ‘New Deal for Consumers’, was a step in the right direction, but fell shor

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