Relevant bibliographies by topics / Cardinality constrained optimization

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  2. Dissertations / Theses
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Academic literature on the topic 'Cardinality constrained optimization'

Author: Grafiati
Published: 10 March 2023
Last updated: 31 July 2025

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Journal articles on the topic "Cardinality constrained optimization"

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Kanzow, Christian, Andreas B. Raharja, and Alexandra Schwartz. "An Augmented Lagrangian Method for Cardinality-Constrained Optimization Problems." Journal of Optimization Theory and Applications 189, no. 3 (2021): 793–813. http://dx.doi.org/10.1007/s10957-021-01854-7.

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AbstractA reformulation of cardinality-constrained optimization problems into continuous nonlinear optimization problems with an orthogonality-type constraint has gained some popularity during the last few years. Due to the special structure of the constraints, the reformulation violates many standard assumptions and therefore is often solved using specialized algorithms. In contrast to this, we investigate the viability of using a standard safeguarded multiplier penalty method without any problem-tailored modifications to solve the reformulated problem. We prove global convergence towards an
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Bertsimas, Dimitris, and Romy Shioda. "Algorithm for cardinality-constrained quadratic optimization." Computational Optimization and Applications 43, no. 1 (2007): 1–22. http://dx.doi.org/10.1007/s10589-007-9126-9.

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Kanzow, Christian, Andreas B. Raharja, and Alexandra Schwartz. "Sequential optimality conditions for cardinality-constrained optimization problems with applications." Computational Optimization and Applications 80, no. 1 (2021): 185–211. http://dx.doi.org/10.1007/s10589-021-00298-z.

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AbstractRecently, a new approach to tackle cardinality-constrained optimization problems based on a continuous reformulation of the problem was proposed. Following this approach, we derive a problem-tailored sequential optimality condition, which is satisfied at every local minimizer without requiring any constraint qualification. We relate this condition to an existing M-type stationary concept by introducing a weak sequential constraint qualification based on a cone-continuity property. Finally, we present two algorithmic applications: We improve existing results for a known regularization m
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Stephan, Rüdiger. "Cardinality constrained combinatorial optimization: Complexity and polyhedra." Discrete Optimization 7, no. 3 (2010): 99–113. http://dx.doi.org/10.1016/j.disopt.2010.03.002.

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Cai, L. "Parameterized Complexity of Cardinality Constrained Optimization Problems." Computer Journal 51, no. 1 (2007): 102–21. http://dx.doi.org/10.1093/comjnl/bxm086.

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Bacanin, Nebojsa, and Milan Tuba. "Firefly Algorithm for Cardinality Constrained Mean-Variance Portfolio Optimization Problem with Entropy Diversity Constraint." Scientific World Journal 2014 (2014): 1–16. http://dx.doi.org/10.1155/2014/721521.

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Portfolio optimization (selection) problem is an important and hard optimization problem that, with the addition of necessary realistic constraints, becomes computationally intractable. Nature-inspired metaheuristics are appropriate for solving such problems; however, literature review shows that there are very few applications of nature-inspired metaheuristics to portfolio optimization problem. This is especially true for swarm intelligence algorithms which represent the newer branch of nature-inspired algorithms. No application of any swarm intelligence metaheuristics to cardinality constrai
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Xu, Fengmin, Yuhong Dai, Zhihu Zhao, and Zongben Xu. "Efficient projected gradient methods for cardinality constrained optimization." Science China Mathematics 62, no. 2 (2018): 245–68. http://dx.doi.org/10.1007/s11425-016-9124-0.

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Sadjadi, Seyed Jafar, Mohsen Gharakhani, and Ehram Safari. "Robust optimization framework for cardinality constrained portfolio problem." Applied Soft Computing 12, no. 1 (2012): 91–99. http://dx.doi.org/10.1016/j.asoc.2011.09.006.

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Shaw, Dong X., Shucheng Liu, and Leonid Kopman. "Lagrangian relaxation procedure for cardinality-constrained portfolio optimization." Optimization Methods and Software 23, no. 3 (2008): 411–20. http://dx.doi.org/10.1080/10556780701722542.

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Febrianti, Werry, Kuntjoro Adji Sidarto, and Novriana Sumarti. "Solving Constrained Mean-Variance Portfolio Optimization Problems Using Spiral Optimization Algorithm." International Journal of Financial Studies 11, no. 1 (2022): 1. http://dx.doi.org/10.3390/ijfs11010001.

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Portfolio optimization is an activity for balancing return and risk. In this paper, we used mean-variance (M-V) portfolio models with buy-in threshold and cardinality constraints. This model can be formulated as a mixed integer nonlinear programming (MINLP) problem. To solve this constrained mean-variance portfolio optimization problem, we propose the use of a modified spiral optimization algorithm (SOA). Then, we use Bartholomew-Biggs and Kane’s data to validate our proposed algorithm. The results show that our proposed algorithm can be an efficient tool for solving this portfolio optimizatio
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Dissertations / Theses on the topic "Cardinality constrained optimization"

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Aslan, Murat. "The Cardinality Constrained Multiple Knapsack Problem." Master's thesis, METU, 2008. http://etd.lib.metu.edu.tr/upload/12610131/index.pdf.

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The classical multiple knapsack problem selects a set of items and assigns each to one of the knapsacks so as to maximize the total profit. The knapsacks have limited capacities. The cardinality constrained multiple knapsack problem assumes limits on the number of items that are to be put in each knapsack, as well. Despite many efforts on the classical multiple knapsack problem, the research on the cardinality constrained multiple knapsack problem is scarce. In this study we consider the cardinality constrained multiple knapsack problem. We propose heuristic and optimization procedures tha
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Li, Yibo. "Solving cardinality constrained portfolio optimisation problem using genetic algorithms and ant colony optimisation." Thesis, Brunel University, 2015. http://bura.brunel.ac.uk/handle/2438/10867.

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In this thesis we consider solution approaches for the index tacking problem, in which we aim to reproduces the performance of a market index without purchasing all of the stocks that constitute the index. We solve the problem using three different solution approaches: Mixed Integer Programming (MIP), Genetic Algorithms (GAs), and Ant-colony Optimization (ACO) Algorithm by limiting the number of stocks that can be held. Each index is also assigned with different cardinalities to examine the change to the solution values. All of the solution approaches are tested by considering eight market ind
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Bucher, Max [Verfasser], Alexandra [Akademischer Betreuer] Schwartz, and Christian [Akademischer Betreuer] Kanzow. "Optimality Conditions and Numerical Methods for a Continuous Reformulation of Cardinality Constrained Optimization Problems / Max Bucher ; Alexandra Schwartz, Christian Kanzow." Darmstadt : Universitäts- und Landesbibliothek Darmstadt, 2018. http://d-nb.info/1167926323/34.

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Kreber, Dennis [Verfasser], Sven de [Akademischer Betreuer] Vries, Jan Pablo [Akademischer Betreuer] Burgard, Sven de [Gutachter] Vries, Jan Pablo [Gutachter] Burgard, and Christoph [Gutachter] Buchheim. "Cardinality-Constrained Discrete Optimization for Regression / Dennis Kreber ; Gutachter: Sven de Vries, Jan Pablo Burgard, Christoph Buchheim ; Sven de Vries, Jan Pablo Burgard." Trier : Universität Trier, 2019. http://d-nb.info/1197809198/34.

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Dias, Carlos Henrique. "Um novo algoritmo genetico para a otimização de carteiras de investimento com restrições de cardinalidade." [s.n.], 2008. http://repositorio.unicamp.br/jspui/handle/REPOSIP/307124.

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Orientador: Francisco de Assis Magalhães Gomes Neto<br>Dissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Matematica, Estatistica e Computação Cientifica<br>Made available in DSpace on 2018-08-10T22:50:20Z (GMT). No. of bitstreams: 1 Dias_CarlosHenrique_M.pdf: 2721795 bytes, checksum: 57d6019ecabf33034889a64675ccf707 (MD5) Previous issue date: 2008<br>Resumo: Este trabalho tem por finalidade a determinação da fronteira eficiente de investimento através da otimização do modelo de média-variância com restrições de cardinalidade e limite inferior de investimento. Por trat
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Lasluisa, Daniel. "Contributions to optimization in energy : from bilevel optimization to optimal design of renewable energy plant." Electronic Thesis or Diss., Perpignan, 2024. http://www.theses.fr/2024PERP0009.

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Dans ce travail de thèse, nous développons et appliquons des techniques d'optimisation dans la conception et la gestion de l'énergie. Tout d'abord, nous nous concentrons sur l'optimisation bi-niveaux et développons une nouvelle analyse théorique pour les jeux à un seul meneur et plusieurs suiveurs avec des contraintes de cardinalité. Cette analyse est ensuite appliquée à la localisation optimale des stations de recharge pour véhicules électriques. La deuxième partie est consacrée à l'optimisation économique, à long terme et à court terme, des centrales solaires à concentration. Une approche in
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Villela, Pedro Ferraz 1982. "Um algoritmo exato para a otimização de carteiras de investimento com restrições de cardinalidade." [s.n.], 2008. http://repositorio.unicamp.br/jspui/handle/REPOSIP/307123.

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Orientador: Francisco de Assis Magalhães Gomes Neto<br>Dissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Matematica, Estatistica e Computação Cientifica<br>Made available in DSpace on 2018-08-12T16:09:04Z (GMT). No. of bitstreams: 1 Villela_PedroFerraz_M.pdf: 727069 bytes, checksum: d87d64ae49bfc1a53017a463cf10b453 (MD5) Previous issue date: 2008<br>Resumo: Neste trabalho, propomos um método exato para a resolução de problemas de programação quadrática que envolvem restrições de cardinalidade. Como aplicação, empregamos o método para a obtenção da fronteira eficiente d
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"On cardinality constrained optimization." Thesis, 2009. http://library.cuhk.edu.hk/record=b6074943.

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Although cardinality constraints naturally arise in many applications, e.g., in portfolio selection problems of choosing small number of assets from a large pool of stocks or dynamic portfolio selection problems with limited trading dates within a given time horizon and in subset selection of the regression analysis, the state-of-the-art in cardinality constrained optimization has been stagnant up to this stage, largely due to the inherent combinatorial nature of such hard problems. We focus in this research on developing efficient and implementable solution algorithms for cardinality constrai
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"Cardinality constrained portfolio selection using clustering methodology." 2011. http://library.cuhk.edu.hk/record=b5894828.

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Jiang, Kening.<br>"August 2011."<br>Thesis (M.Phil.)--Chinese University of Hong Kong, 2011.<br>Includes bibliographical references (p. 90-93).<br>Abstracts in English and Chinese.<br>Chapter 1 --- Introduction --- p.1<br>Chapter 2 --- Portfolio Selection Using Clustering Methodology --- p.7<br>Chapter 2.1 --- Heuristic algorithm --- p.8<br>Chapter 2.1.1 --- Step 1: Security transformation by factor model --- p.8<br>Chapter 2.1.2 --- Step 2: Clustering algorithm --- p.10<br>Chapter 2.1.3 --- Step 3: Representative selection by t he Sliarpe ratio --- p.16<br>Chapter 2.2 --- Numerical resu
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"Cardinality constrained discrete-time linear-quadratic control." 2005. http://library.cuhk.edu.hk/record=b5892706.

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Gao Jianjun.<br>Thesis (M.Phil.)--Chinese University of Hong Kong, 2005.<br>Includes bibliographical references (leaves 75-76).<br>Abstracts in English and Chinese.<br>Chapter 1 --- Introduction --- p.1<br>Chapter 2 --- Solution Framework Using Dynamic Programming --- p.7<br>Chapter 2.1 --- Difficulty of using dynamic programming --- p.8<br>Chapter 2.2 --- Scalar-state problems --- p.12<br>Chapter 2.3 --- Time-invariant system --- p.17<br>Chapter 2.4 --- Illustrative example of a scalar-state problem --- p.21<br>Chapter 3 --- Cardinality Constrained Quadratic Optimization --- p.26<br>Ch
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Book chapters on the topic "Cardinality constrained optimization"

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Leung, Man-Fai, and Jun Wang. "Neurodynamic Approaches to Cardinality-Constrained Portfolio Optimization." In Intelligent Systems Reference Library. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-61037-0_3.

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de Farias, Ismael R., and George L. Nemhauser. "A Polyhedral Study of the Cardinality Constrained Knapsack Problem." In Integer Programming and Combinatorial Optimization. Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/3-540-47867-1_21.

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Khokhar, Mulazim-Ali, Kris Boudt, and Chunlin Wan. "Cardinality-Constrained Higher-Order Moment Portfolios Using Particle Swarm Optimization." In Applying Particle Swarm Optimization. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-70281-6_10.

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Streichert, Felix, Holger Ulmer, and Andreas Zell. "Evolutionary Algorithms and the Cardinality Constrained Portfolio Optimization Problem." In Operations Research Proceedings. Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-642-17022-5_33.

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Cui, Min, Donglei Du, Ling Gai, and Ruiqi Yang. "A Linear-Time Streaming Algorithm for Cardinality-Constrained Maximizing Monotone Non-submodular Set Functions." In Combinatorial Optimization and Applications. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-92681-6_9.

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Ahmad, Faisal, Faraz Hasan, Mohammad Shahid, Jahangir Chauhan, and Mohammad Imran. "Cardinality Constrained Portfolio Selection Strategy Based on Hybrid Metaheuristic Optimization Algorithm." In Proceedings of International Conference on Data Science and Applications. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-6631-6_59.

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Pleshakov, Michael, Sergei Sidorov, and Kirill Spiridonov. "Convergence Analysis of Penalty Decomposition Algorithm for Cardinality Constrained Convex Optimization in Hilbert Spaces." In Mathematical Optimization Theory and Operations Research. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-49988-4_10.

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Mayambala, Fred, Elina Rönnberg, and Torbjörn Larsson. "Tight Upper Bounds on the Cardinality Constrained Mean-Variance Portfolio Optimization Problem Using Truncated Eigendecomposition." In Operations Research Proceedings. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-28697-6_54.

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Ruiz-Torrubiano, Rubén, Sergio García-Moratilla, and Alberto Suárez. "Optimization Problems with Cardinality Constraints." In Computational Intelligence in Optimization. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-12775-5_5.

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Régin, Jean-Charles. "Combination of Among and Cardinality Constraints." In Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems. Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11493853_22.

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Conference papers on the topic "Cardinality constrained optimization"

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Li, Yiran, Nanjiang Du, Xingke Song, et al. "Cardinality and Bounding Constrained Portfolio Optimization Using Safe Reinforcement Learning." In 2024 International Joint Conference on Neural Networks (IJCNN). IEEE, 2024. http://dx.doi.org/10.1109/ijcnn60899.2024.10651491.

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Friedrich, Tobias, Timo Kötzing, Aishwarya Radhakrishnan, et al. "Crossover for cardinality constrained optimization." In GECCO '22: Genetic and Evolutionary Computation Conference. ACM, 2022. http://dx.doi.org/10.1145/3512290.3528713.

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Cheng, Runze, and Jianjun Gao. "On cardinality constrained mean-CVaR portfolio optimization." In 2015 27th Chinese Control and Decision Conference (CCDC). IEEE, 2015. http://dx.doi.org/10.1109/ccdc.2015.7162076.

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Gomez, Miguel A., Carmen X. Flores, and Maria A. Osorio. "Hybrid search for cardinality constrained portfolio optimization." In the 8th annual conference. ACM Press, 2006. http://dx.doi.org/10.1145/1143997.1144302.

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Parizy, Matthieu, Przemyslaw Sadowski, and Nozomu Togawa. "Cardinality Constrained Portfolio Optimization on an Ising Machine." In 2022 IEEE 35th International System-on-Chip Conference (SOCC). IEEE, 2022. http://dx.doi.org/10.1109/socc56010.2022.9908082.

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Zhang, Jize, Tim Leung, and Aleksandr Aravkin. "A Relaxed Optimization Approach for Cardinality-Constrained Portfolios." In 2019 18th European Control Conference (ECC). IEEE, 2019. http://dx.doi.org/10.23919/ecc.2019.8796164.

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Cui, Tianxiang, Shi Cheng, and Ruibin Bai. "A combinatorial algorithm for the cardinality constrained portfolio optimization problem." In 2014 IEEE Congress on Evolutionary Computation (CEC). IEEE, 2014. http://dx.doi.org/10.1109/cec.2014.6900357.

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McCarthy, Philip James, Christopher Nielsen, and Stephen L. Smith. "Cardinality constrained robust optimization applied to a class of interval observers." In 2014 American Control Conference - ACC 2014. IEEE, 2014. http://dx.doi.org/10.1109/acc.2014.6859149.

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Chen, Angela H. L., Yun-Chia Liang, and Chia-Chien Liu. "An artificial bee colony algorithm for the cardinality-constrained portfolio optimization problems." In 2012 IEEE Congress on Evolutionary Computation (CEC). IEEE, 2012. http://dx.doi.org/10.1109/cec.2012.6252920.

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Suthiwong, Dit, and Maleerat Sodanil. "Cardinality-constrained Portfolio optimization using an improved quick Artificial Bee Colony Algorithm." In 2016 International Computer Science and Engineering Conference (ICSEC). IEEE, 2016. http://dx.doi.org/10.1109/icsec.2016.7859943.

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