Academic literature on the topic 'Binary quadratic programming'

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Journal articles on the topic "Binary quadratic programming"

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MU, XUEWEN, SANYANG LID, and YALING ZHANG. "A SUCCESSIVE QUADRATIC PROGRAMMING ALGORITHM FOR SDP RELAXATION OF THE BINARY QUADRATIC PROGRAMMING." Bulletin of the Korean Mathematical Society 42, no. 4 (2005): 837–49. http://dx.doi.org/10.4134/bkms.2005.42.4.837.

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Mu, Xuewen, and Yaling Zhang. "A Rank-Two Feasible Direction Algorithm for the Binary Quadratic Programming." Journal of Applied Mathematics 2013 (2013): 1–7. http://dx.doi.org/10.1155/2013/963563.

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Based on the semidefinite programming relaxation of the binary quadratic programming, a rank-two feasible direction algorithm is presented. The proposed algorithm restricts the rank of matrix variable to be two in the semidefinite programming relaxation and yields a quadratic objective function with simple quadratic constraints. A feasible direction algorithm is used to solve the nonlinear programming. The convergent analysis and time complexity of the method is given. Coupled with randomized algorithm, a suboptimal solution is obtained for the binary quadratic programming. At last, we report
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Wang, Yang, Zhipeng Lü, Fred Glover, and Jin-Kao Hao. "Path relinking for unconstrained binary quadratic programming." European Journal of Operational Research 223, no. 3 (2012): 595–604. http://dx.doi.org/10.1016/j.ejor.2012.07.012.

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Sun, X. L., C. L. Liu, D. Li, and J. J. Gao. "On duality gap in binary quadratic programming." Journal of Global Optimization 53, no. 2 (2011): 255–69. http://dx.doi.org/10.1007/s10898-011-9683-4.

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Kochenberger, Gary, Jin-Kao Hao, Fred Glover, et al. "The unconstrained binary quadratic programming problem: a survey." Journal of Combinatorial Optimization 28, no. 1 (2014): 58–81. http://dx.doi.org/10.1007/s10878-014-9734-0.

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Glover, Fred, and Jin-Kao Hao. "f-Flip strategies for unconstrained binary quadratic programming." Annals of Operations Research 238, no. 1-2 (2015): 651–57. http://dx.doi.org/10.1007/s10479-015-2076-1.

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Ronagh, Pooya, Brad Woods, and Ehsan Iranmanesh. "Solving constrained quadratic binary problems via quantum adiabatic evolution." Quantum Information and Computation 16, no. 11&12 (2016): 1029–47. http://dx.doi.org/10.26421/qic16.11-12-6.

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Quantum adiabatic evolution is perceived as useful for binary quadratic programming problems that are a priori unconstrained. For constrained problems, it is a common practice to relax linear equality constraints as penalty terms in the objective function. However, there has not yet been proposed a method for efficiently dealing with inequality constraints using the quantum adiabatic approach. In this paper, we give a method for solving the Lagrangian dual of a binary quadratic programming (BQP) problem in the presence of inequality constraints and employ this procedure within a branch-and-bou
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Recht, Peter. "Characterization of optimal points in binary convex quadratic programming." Optimization 56, no. 1-2 (2007): 39–47. http://dx.doi.org/10.1080/02331930600815801.

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Merz, Peter, and Kengo Katayama. "Memetic algorithms for the unconstrained binary quadratic programming problem." Biosystems 78, no. 1-3 (2004): 99–118. http://dx.doi.org/10.1016/j.biosystems.2004.08.002.

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Liefooghe, Arnaud, Sébastien Verel, and Jin-Kao Hao. "A hybrid metaheuristic for multiobjective unconstrained binary quadratic programming." Applied Soft Computing 16 (March 2014): 10–19. http://dx.doi.org/10.1016/j.asoc.2013.11.008.

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Dissertations / Theses on the topic "Binary quadratic programming"

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Bettiol, Enrico. "Column generation methods for quadratic mixed binary programming." Thesis, Paris 13, 2019. http://www.theses.fr/2019PA131073.

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La programmation non linéaire mixte peut modéliser un grand nombre de problèmes réels. Cependant, ces problèmes peuvent contenir de nombreuses variables ou contraintes, il convient donc de proposer des méthodes de décomposition afin de les résoudre efficacement. Parmi ces techniques on peut citer la génération de colonnes et notamment la décomposition de Dantzig-Wolfe. Il s’agit d’une reformulation du problème original, qui permet de générer une séquence de sous-problèmes plus simples, appelés maître etpricing, pour obtenir la valeur optimale. Développée d’abord pour les problèmes linéaires, l
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Battikh, Rabih. "La résοlutiοn de prοblème quadratique binaire par des méthοdes d'οptimisatiοn exactes et apprοchées". Electronic Thesis or Diss., Normandie, 2024. http://www.theses.fr/2024NORMLH20.

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Dans cette thèse, nous avons présenté un nouvel algorithme hybride (HA) pour la résolution du problème (UQP). Cet algorithme est basé sur la combinaison d'un bloc de cinq procédures spéciales et de la méthode du recuit simulé. Nos procédures sont très efficaces et rapides, mais malheureusement, parfois elles sont bloquées par un minimum local. Pour surmonter cet inconvénient, nous les avons combinées avec un algorithme de recuit simulé. Ensuite, nous avons répété ces procédures plusieurs fois pour obtenir la meilleure solution en utilisant notre algorithme hybride.Nous avons remarqué que l'éca
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Silva, Pedro Miguel Dias da. "Quantum Computing for Optimizing Power Flow in Energy Grids." Master's thesis, 2021. http://hdl.handle.net/10316/98073.

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Dissertação de Mestrado em Engenharia Informática apresentada à Faculdade de Ciências e Tecnologia<br>Quantum Computing is beginning to gather even more attention at a time where efforts are being made into familiarizing younger audiences into not only learning programming on a classical computer, but also on a quantum one.This new paradigm of computation is set to revolutionize several industries as the hardware keeps developing, with the potential to solve problems that a classical computer would consider intangible, as well as giving some specific problems a so sought after speed-up. This i
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Books on the topic "Binary quadratic programming"

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Li, Jian, Antonio De Maio, Guolong Cui, and Alfonso Farina. Radar Waveform Design Based on Optimization Theory. Institution of Engineering & Technology, 2020.

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Radar Waveform Design Based on Optimization Theory. Institution of Engineering & Technology, 2020.

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Book chapters on the topic "Binary quadratic programming"

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Punnen, Abraham P., and Renata Sotirov. "Mathematical Programming Models and Exact Algorithms." In The Quadratic Unconstrained Binary Optimization Problem. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-04520-2_6.

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Cifuentes, Diego, Santanu S. Dey, and Jingye Xu. "Sensitivity Analysis for Mixed Binary Quadratic Programming." In Integer Programming and Combinatorial Optimization. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-59835-7_33.

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Buchheim, Christoph, and Emiliano Traversi. "Separable Non-convex Underestimators for Binary Quadratic Programming." In Experimental Algorithms. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-38527-8_22.

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Dong, Hongbo, and Jeff Linderoth. "On Valid Inequalities for Quadratic Programming with Continuous Variables and Binary Indicators." In Integer Programming and Combinatorial Optimization. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-36694-9_15.

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Borndörfer, Ralf, and Carlos Cardonha. "A Binary Quadratic Programming Approach to the Vehicle Positioning Problem." In Modeling, Simulation and Optimization of Complex Processes. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-25707-0_4.

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Wang, Yang, Zhipeng Lü, Fred Glover, and Jin-Kao Hao. "Effective Variable Fixing and Scoring Strategies for Binary Quadratic Programming." In Evolutionary Computation in Combinatorial Optimization. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-20364-0_7.

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Wang, Yang, Zhipeng Lü, Fred Glover, and Jin-Kao Hao. "A Multilevel Algorithm for Large Unconstrained Binary Quadratic Optimization." In Integration of AI and OR Techniques in Contraint Programming for Combinatorial Optimzation Problems. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-29828-8_26.

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Liefooghe, Arnaud, Sébastien Verel, Luís Paquete, and Jin-Kao Hao. "Experiments on Local Search for Bi-objective Unconstrained Binary Quadratic Programming." In Lecture Notes in Computer Science. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-15934-8_12.

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Zhou, Ying, Lingjing Kong, Lijun Yan, Shaopeng Liu, and Jiaming Hong. "A Multiobjective Memetic Algorithm for Multiobjective Unconstrained Binary Quadratic Programming Problem." In Lecture Notes in Computer Science. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-78811-7_3.

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de Souza, Marcelo, and Marcus Ritt. "Automatic Grammar-Based Design of Heuristic Algorithms for Unconstrained Binary Quadratic Programming." In Evolutionary Computation in Combinatorial Optimization. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-77449-7_5.

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Conference papers on the topic "Binary quadratic programming"

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Zanotti, Roberto, and Francesco Negro. "An Innovative Binary Quadratic Programming Approach for the Accurate Identification of Discharge Timings of Motor Units From High-Density Surface EMG Signals." In 2024 IEEE International Conference on Metrology for eXtended Reality, Artificial Intelligence and Neural Engineering (MetroXRAINE). IEEE, 2024. https://doi.org/10.1109/metroxraine62247.2024.10795886.

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De Souza, Murilo Zangari, and Aurora Trinidad Ramirez Pozo. "Multiobjective Binary ACO for Unconstrained Binary Quadratic Programming." In 2015 Brazilian Conference on Intelligent Systems (BRACIS). IEEE, 2015. http://dx.doi.org/10.1109/bracis.2015.15.

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Lin, Geng. "Solving unconstrained binary quadratic programming using binary particle swarm optimization." In 2013 International Conference of Information Technology and Industrial Engineering. WIT Press, 2013. http://dx.doi.org/10.2495/itie130311.

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Istrati, Daniela, Vasile Moraru, and Sergiu Zaporojan. "A Method for Binary Quadratic Programming with Circulant Matrix." In 12th International Conference on Electronics, Communications and Computing. Technical University of Moldova, 2022. http://dx.doi.org/10.52326/ic-ecco.2022/cs.01.

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Binary quadratic programming is a classical combinatorial optimization problem that has many real-world applications. This paper presents a method for solving the quadratic programming problem with circulant matrix by reformulating and relaxing it into a separable optimization problem. The proposed method determines local suboptimal solutions. To solve the relaxing problem, the DCA algorithm it is proposed to calculate the solutions, in the general case, only local suboptimal.
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Lee, Gim Hee. "Line Association and Vanishing Point Estimation with Binary Quadratic Programming." In 2017 International Conference on 3D Vision (3DV). IEEE, 2017. http://dx.doi.org/10.1109/3dv.2017.00072.

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Toyama, Fubito, Kenji Shoji, Hiroshi Mori, and Juichi Miyamichi. "An iterated greedy algorithm for the binary quadratic programming problem." In 2012 Joint 6th Intl. Conference on Soft Computing and Intelligent Systems (SCIS) and 13th Intl. Symposium on Advanced Intelligent Systems (ISIS). IEEE, 2012. http://dx.doi.org/10.1109/scis-isis.2012.6505143.

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Mejari, Manas, Vihangkumar V. Naik, Dario Piga, and Alberto Bemporad. "Energy Disaggregation using Piecewise Affine Regression and Binary Quadratic Programming." In 2018 IEEE Conference on Decision and Control (CDC). IEEE, 2018. http://dx.doi.org/10.1109/cdc.2018.8619175.

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Masti, Daniele, and Alberto Bemporad. "Learning binary warm starts for multiparametric mixed-integer quadratic programming." In 2019 18th European Control Conference (ECC). IEEE, 2019. http://dx.doi.org/10.23919/ecc.2019.8795808.

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Olsson, Carl, Anders P. Eriksson, and Fredrik Kahl. "Solving Large Scale Binary Quadratic Problems: Spectral Methods vs. Semidefinite Programming." In 2007 IEEE Conference on Computer Vision and Pattern Recognition. IEEE, 2007. http://dx.doi.org/10.1109/cvpr.2007.383202.

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Jialong Shi, Qingfu Zhang, Bilel Derbel, and Arnaud Liefooghe. "A Parallel Tabu Search for the Unconstrained Binary Quadratic Programming problem." In 2017 IEEE Congress on Evolutionary Computation (CEC). IEEE, 2017. http://dx.doi.org/10.1109/cec.2017.7969360.

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Reports on the topic "Binary quadratic programming"

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Coffrin, Carleton James, Harsha Nagarajan, and Russell Whitford Bent. Challenges and Successes of Solving Binary Quadratic Programming Benchmarks on the DW2X QPU. Office of Scientific and Technical Information (OSTI), 2016. http://dx.doi.org/10.2172/1330084.

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