Academic literature on the topic 'Max-min Algorithm'

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Journal articles on the topic "Max-min Algorithm"

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Tawanda, Trust, Philimon Nyamugure, Elias Munapo, and Santosh Kumar. "Extreme Min – Cut Max – Flow Algorithm." International Journal of Applied Metaheuristic Computing 14, no. 1 (2023): 1–16. http://dx.doi.org/10.4018/ijamc.322436.

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In this article, the authors propose a maximum flow algorithm based on flow matrix. The algorithm only requires the effort to reduce the capacity of the underutilized arcs to that of the respective flow. The optimality of the algorithm is proved by the max-flow min-cut theorem. The algorithm is table-based, thus avoiding augmenting path and residual network concepts. The authors used numerical examples and computational comparisons to demonstrate the efficiency of the algorithm. These examples and comparisons revealed that the proposed algorithm is capable of computing exact solutions while us
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Wang, Zhenlin, and Jonathan Scarlett. "Max-Min Grouped Bandits." Proceedings of the AAAI Conference on Artificial Intelligence 36, no. 8 (2022): 8603–11. http://dx.doi.org/10.1609/aaai.v36i8.20838.

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In this paper, we introduce a multi-armed bandit problem termed max-min grouped bandits, in which the arms are arranged in possibly-overlapping groups, and the goal is to find a group whose worst arm has the highest mean reward. This problem is of interest in applications such as recommendation systems, and is also closely related to widely-studied robust optimization problems. We present two algorithms based successive elimination and robust optimization, and derive upper bounds on the number of samples to guarantee finding a max-min optimal or near-optimal group, as well as an algorithm-inde
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Ibrahim, A. Thiyeb, and Sharaf A. Alhomdy Dr. "HAMM: A Hybrid Algorithm of Min-Min and Max-Min Task Scheduling Algorithms in Cloud Computing." International Journal of Recent Technology and Engineering (IJRTE) 9, no. 4 (2020): 209–18. https://doi.org/10.35940/ijrte.D4874.119420.

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Nowadays, with the huge development of information and computing technologies, the cloud computing is becoming the highly scalable and widely computing technology used in the world that bases on pay-per-use, remotely access, Internet-based and on-demand concepts in which providing customers with a shared of configurable resources. But, with the highly incoming user’s requests, the task scheduling and resource allocation are becoming major requirements for efficient and effective load balancing of a workload among cloud resources to enhance the overall cloud system performance. For these
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Tsoukalas, Angelos, Panos Parpas, and Berç Rustem. "A smoothing algorithm for finite min–max–min problems." Optimization Letters 3, no. 1 (2008): 49–62. http://dx.doi.org/10.1007/s11590-008-0090-9.

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Feng, Qigao, Hongwei Jiao, Hanping Mao, and Yongqiang Chen. "A Deterministic Algorithm for Min-max and Max-min Linear Fractional Programming Problems." International Journal of Computational Intelligence Systems 4, no. 2 (2011): 134. http://dx.doi.org/10.2991/ijcis.2011.4.2.2.

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Feng, Qigao, Hongwei Jiao, Hanping Mao, and Yongqiang Chen. "A Deterministic Algorithm for Min-max and Max-min Linear Fractional Programming Problems." International Journal of Computational Intelligence Systems 4, no. 2 (2011): 134–41. http://dx.doi.org/10.1080/18756891.2011.9727770.

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Li, Ran Ran, Lei Li, and Xiao Hui Li. "An Improved Localization Algorithm in Wireless Sensor Networks." Advanced Materials Research 1049-1050 (October 2014): 2144–48. http://dx.doi.org/10.4028/www.scientific.net/amr.1049-1050.2144.

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Min-Max localization algorithm is usually used to acquire the position of a sensor node in wireless sensor networks by the reason of its simpleness and low complexity. However, Min-Max algorithm provides a coarse position estimation. In order to increase its accuracy, an Extended Min-Max (E-Min-Max) algorithm has been proposed. In this paper we focus on this algorithm and propose an improved E-Min-Max algorithm to enhance its accuracy further. Simulations show that the improved E-Min-Max algorithm outperforms its original version in localization.
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M.Elzeki, O., M. Z. Reshad, and M. A. Elsoud. "Improved Max-Min Algorithm in Cloud Computing." International Journal of Computer Applications 50, no. 12 (2012): 22–27. http://dx.doi.org/10.5120/7823-1009.

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Polak, E., D. Q. Mayne, and J. E. Higgins. "Superlinearly convergent algorithm for min-max problems." Journal of Optimization Theory and Applications 69, no. 3 (1991): 407–39. http://dx.doi.org/10.1007/bf00940683.

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SMYK, Robert. "New alpha max and beta min algorithm." PRZEGLĄD ELEKTROTECHNICZNY 1, no. 1 (2025): 47–49. https://doi.org/10.15199/48.2025.01.09.

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Dissertations / Theses on the topic "Max-min Algorithm"

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Smith, Andrea Marie. "A dual algorithm for the weighted Euclidean distance min-max location problem in R² and R³." Connect to this title online, 2009. http://etd.lib.clemson.edu/documents/1246559571/.

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Korgo, Jakub. "Nové aplikace mravenčích algoritmů." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2018. http://www.nusl.cz/ntk/nusl-385942.

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Ant algorithms have been used for a variety of combinatorial optimization problems. One of these problems, where ant algorithms haven't been used, is the design of transition rules for cellular automata (CA). Which is a problem that this master's thesis is focused on. This work begins with an introduction into ant algorithms and a overview of its applications, followed by an introduction into CA. In the next part the author proposes a way how to encode rules of CA into a graph which is used in ant algorithms. The last part of this thesis contains an application of encoded graph on elitist ant
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Phan, Tran Duc Minh. "Une méthode de dualité pour des problèmes non convexes du Calcul des Variations." Thesis, Toulon, 2018. http://www.theses.fr/2018TOUL0006/document.

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Dans cette thèse, nous étudions un principe général de convexification permettant de traiter certainsproblèmes variationnels non convexes sur Rd. Grâce à ce principe nous pouvons mettre en oeuvre lespuissantes techniques de dualité et ramener de tels problèmes à des formulations de type primal–dualdans Rd+1, rendant ainsi efficace la recherche numérique de minima globaux. Une théorie de ladualité et des champs de calibration est reformulée dans le cas de fonctionnelles à croissance linéaire.Sous certaines hypothèses, cela nous permet de généraliser un principe d’exclusion découvert parVisintin
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Xie, Qing Yan. "K-Centers Dynamic Clustering Algorithms and Applications." University of Cincinnati / OhioLINK, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1384427644.

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Phan, Tran Duc Minh. "Une méthode de dualité pour des problèmes non convexes du Calcul des Variations." Electronic Thesis or Diss., Toulon, 2018. http://www.theses.fr/2018TOUL0006.

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Dans cette thèse, nous étudions un principe général de convexification permettant de traiter certainsproblèmes variationnels non convexes sur Rd. Grâce à ce principe nous pouvons mettre en oeuvre lespuissantes techniques de dualité et ramener de tels problèmes à des formulations de type primal–dualdans Rd+1, rendant ainsi efficace la recherche numérique de minima globaux. Une théorie de ladualité et des champs de calibration est reformulée dans le cas de fonctionnelles à croissance linéaire.Sous certaines hypothèses, cela nous permet de généraliser un principe d’exclusion découvert parVisintin
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Lee, ChuanChe. "Parallel programming on General Block Min Max Criterion." CSUSB ScholarWorks, 2006. https://scholarworks.lib.csusb.edu/etd-project/3065.

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The purpose of the thesis is to develop a parallel implementation of the General Block Min Max Criterion (GBMM). This thesis deals with two kinds of parallel overheads: Redundant Calculations Parallel Overhead (RCPO) and Communication Parallel Overhead (CPO).
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Pee, Eng Yau. "On algorithms for nonlinear minimax and min-max-min problems and their efficiency." Monterey, California. Naval Postgraduate School, 2011. http://hdl.handle.net/10945/10782.

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This dissertation approaches the solution of optimization models with uncertain parameters by considering the worst-case value of the uncertain parameters during optimization. We consider three problems resulting from this approach: a finite minimax problem (FMX), a semi-infinite minimax problem (SMX), and a semi-infinite minmax-min problem (MXM). In all problems, we consider nonlinear functions with continuous variables. We find that smoothing algorithms for (FMX) may only have sublinear rates of convergence, but their complexity in the number of functions is competitive with other algorithms
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Costa, da Silva Marco Aurelio. "Applications and algorithms for two-stage robust linear optimization." Thesis, Avignon, 2018. http://www.theses.fr/2018AVIG0229/document.

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Le domaine de recherche de cette thèse est l'optimisation linéaire robuste en deux étapes. Nous sommes intéressés par des algorithmes d'exploration de sa structure et aussi pour ajouter des alternatives afin d'atténuer le conservatisme inhérent à une solution robuste. Nous développons des algorithmes qui incorporent ces alternatives et sont personnalisés pour fonctionner avec des exemples de problèmes à moyenne ou grande échelle. En faisant cela, nous expérimentons une approche holistique du conservatisme en optimisation linéaire robuste et nous rassemblons les dernières avancées dans des doma
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Li, Shimin. "Geometric Algorithms for Intervals and Related Problems." DigitalCommons@USU, 2018. https://digitalcommons.usu.edu/etd/7035.

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In this dissertation, we study several problems related to intervals and develop efficient algorithms for them. Interval problems have many applications in reality because many objects, values, and ranges are intervals in nature, such as time intervals, distances, line segments, probabilities, etc. Problems on intervals are gaining attention also because intervals are among the most basic geometric objects, and for the same reason, computational geometry techniques find useful for attacking these problems. Specifically, the problems we study in this dissertation includes the following: balance
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Amrani-Benhalima, Faïza. "Problèmes de MIN-MAX en variables 0-1 : Algorithmes de résolution exacts et approchés." Valenciennes, 1997. https://ged.uphf.fr/nuxeo/site/esupversions/6fb2c7ce-df58-4bc6-bb55-a1a7c0529fcf.

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Le problème de Minmax en variables continues ou en variables entières a toujours suscité un intérêt croissant d'une part, parce que son champs d'application est vaste. Que ce soit dans le domaine des mathématiques, l'allocation de ressource, l'économie, l'aéronautique et même des jeux. D'autres part, parce que les problèmes traités sont classés en théorie de la complexité comme NP-difficile même quand il s'agit d'un problème de Minmax en variables 0-1 sans contrainte et avec seulement deux objectifs. Cette thèse contribue à l'étude des problèmes en variables bivalentes. Elle propose la résolut
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Book chapters on the topic "Max-min Algorithm"

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Makino, Kazuhisa, Masafumi Yamashita, and Tiko Kameda. "Max- and Min-Neighborhood Monopolies." In Algorithm Theory - SWAT 2000. Springer Berlin Heidelberg, 2000. http://dx.doi.org/10.1007/3-540-44985-x_43.

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Terence Johnson and Santosh Kumar Singh. "Divisive Hierarchical Bisecting Min–Max Clustering Algorithm." In Proceedings of the International Conference on Data Engineering and Communication Technology. Springer Singapore, 2016. http://dx.doi.org/10.1007/978-981-10-1675-2_57.

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Rustem, Berç. "A Discrete Min-Max Algorithm for Inequality Constraints." In Operations Research ’93. Physica-Verlag HD, 1994. http://dx.doi.org/10.1007/978-3-642-46955-8_105.

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Ren, Chunyu. "New Genetic Algorithm for Min-Max Vehicle Routing Problem." In Information and Business Intelligence. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-29087-9_4.

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Fan, Xiaona, and Qinglun Yan. "Interior Point Algorithm for Constrained Sequential Max-Min Problems." In Information Computing and Applications. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-16167-4_53.

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Kim, Kyoung Min, Buhm Lee, Nam Sup Choi, Gwan Hee Kang, Joong Jo Park, and Ching Y. Suen. "Gray-Scale Thinning Algorithm Using Local Min/Max Operations." In Document Analysis Systems VII. Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11669487_6.

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Jansen, Klaus. "Approximation Algorithms for the General Max-min Resource Sharing Problem: Faster and Simpler." In Algorithm Theory - SWAT 2004. Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-27810-8_27.

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Stachurski, Andrzej. "On a feasible descent algorithm for solving min-max problems." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/3-540-62598-4_129.

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Liu, Hai Lin, and Yuping Wang. "A Novel Multiobjective Evolutionary Algorithm Based on Min-Max Strategy." In Intelligent Data Engineering and Automated Learning. Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-540-45080-1_47.

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Viet, Hoang Huu, Nguyen Thi Uyen, Pham Tra My, Son Thanh Cao, and Le Hong Trang. "A Max-Min Conflict Algorithm for the Stable Marriage Problem." In Knowledge Management and Acquisition for Intelligent Systems. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-30639-7_5.

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Conference papers on the topic "Max-min Algorithm"

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Cheraghy, Maryam, Meysam Soltanpour, Belal Abuhaija, Hemn Barzan Abdalla, and Kennedy Ehimwenma. "Game-Theoretic-Based Resource Allocation Algorithm for SCMA Max-Min Problem to Maximize Fairness." In 2024 IEEE 7th International Conference on Electronics and Communication Engineering (ICECE). IEEE, 2024. https://doi.org/10.1109/icece63871.2024.10976939.

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Ranga, Virender, Mayank Dave, and Anil Kumar Verma. "Modified Max-Min Algorithm for Game Theory." In 2015 Fifth International Conference on Advanced Computing & Communication Technologies (ACCT). IEEE, 2015. http://dx.doi.org/10.1109/acct.2015.18.

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Maxim, Anca, Jose M. Maestre, Constantin F. Caruntu, and Corneliu Lazar. "Min-Max Coalitional Model Predictive Control Algorithm." In 2019 22nd International Conference on Control Systems and Computer Science (CSCS). IEEE, 2019. http://dx.doi.org/10.1109/cscs.2019.00012.

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Will, Heiko, Thomas Hillebrandt, Yang Yuan, Zhao Yubin, and Marcel Kyas. "The Membership Degree Min-Max localization algorithm." In 2012 Ubiquitous Positioning Indoor Navigation and Location Based Service (UPINLBS). IEEE, 2012. http://dx.doi.org/10.1109/upinlbs.2012.6409781.

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Annamalai, Chidambaram, Christos Kalaitzis, and Ola Svensson. "Combinatorial Algorithm for Restricted Max-Min Fair Allocation." In Proceedings of the Twenty-Sixth Annual ACM-SIAM Symposium on Discrete Algorithms. Society for Industrial and Applied Mathematics, 2014. http://dx.doi.org/10.1137/1.9781611973730.90.

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Gao, Ang, Aoife Hennessy, and Michel Schellekens. "MOQA min-max heapify: A randomness preserving algorithm." In NUMERICAL ANALYSIS AND APPLIED MATHEMATICS ICNAAM 2012: International Conference of Numerical Analysis and Applied Mathematics. AIP, 2012. http://dx.doi.org/10.1063/1.4756273.

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Zhang, Chi, Xu-Lei Yang, Guanzhou Zhao, and Jie Wan. "Theoretical Derivations of Min-Max Information Clustering Algorithm." In information Services (ICICIS). IEEE, 2011. http://dx.doi.org/10.1109/icicis.2011.38.

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Rizzi, A., M. Panella, F. M. Frattale Mascioli, and G. Martinelli. "A recursive algorithm for fuzzy min-max networks." In Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks. IJCNN 2000. Neural Computing: New Challenges and Perspectives for the New Millennium. IEEE, 2000. http://dx.doi.org/10.1109/ijcnn.2000.859451.

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Wang, Yue. "Analysis of the Max-Min Hill-Climbing Algorithm." In Proceedings of the 2018 International Conference on Transportation & Logistics, Information & Communication, Smart City (TLICSC 2018). Atlantis Press, 2018. http://dx.doi.org/10.2991/tlicsc-18.2018.82.

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Li, Yan, Zhunge Zhu, and Yong Wang. "MIN-Max-Min: A Heuristic Scheduling Algorithm for Jobs across Geo-Distributed Datacenters." In 2018 IEEE 38th International Conference on Distributed Computing Systems (ICDCS). IEEE, 2018. http://dx.doi.org/10.1109/icdcs.2018.00173.

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Reports on the topic "Max-min Algorithm"

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Leighton, Tom, and Satish Rao. An Approximate Max-Flow Min-Cut Theorem for Uniform Multicommodity Flow Problems with Applications to Approximation Algorithms. Defense Technical Information Center, 1989. http://dx.doi.org/10.21236/ada211908.

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