Gotowe bibliografie tematyczne / Second-Order Cone Programming

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Gotowa bibliografia na temat „Second-Order Cone Programming”

Autor: Grafiati
Data publikacji: 4 czerwca 2021
Data aktualizacji: 26 stycznia 2023

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Artykuły w czasopismach na temat "Second-Order Cone Programming"

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Alizadeh, F., and D. Goldfarb. "Second-order cone programming." Mathematical Programming 95, no. 1 (January 1, 2003): 3–51. http://dx.doi.org/10.1007/s10107-002-0339-5.

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Kobayashi, Kazuhiro, Sunyoung Kim, and Masakazu Kojima. "SPARSE SECOND ORDER CONE PROGRAMMING FORMULATIONS FOR CONVEX OPTIMIZATION PROBLEMS." Journal of the Operations Research Society of Japan 51, no. 3 (2008): 241–64. http://dx.doi.org/10.15807/jorsj.51.241.

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Hang, Nguyen T. V., Boris S. Mordukhovich, and M. Ebrahim Sarabi. "Second-order variational analysis in second-order cone programming." Mathematical Programming 180, no. 1-2 (November 3, 2018): 75–116. http://dx.doi.org/10.1007/s10107-018-1345-6.

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Xia, Yu. "Two-dimensional Second-Order Cone Programming." International Journal of Operational Research 5, no. 4 (2009): 468. http://dx.doi.org/10.1504/ijor.2009.025704.

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Lobo, Miguel Sousa, Lieven Vandenberghe, Stephen Boyd, and Hervé Lebret. "Applications of second-order cone programming." Linear Algebra and its Applications 284, no. 1-3 (November 1998): 193–228. http://dx.doi.org/10.1016/s0024-3795(98)10032-0.

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Averbakh, I., and Y. B. Zhao. "Relaxed robust second-order-cone programming." Applied Mathematics and Computation 210, no. 2 (April 2009): 387–97. http://dx.doi.org/10.1016/j.amc.2009.01.019.

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Wang, Jiani, and Liwei Zhang. "Statistical Inference of Second-Order Cone Programming." Asia-Pacific Journal of Operational Research 35, no. 06 (December 2018): 1850044. http://dx.doi.org/10.1142/s0217595918500446.

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The randomness of the second-order cone programming problems is mainly reflected in the objective function and the constraints both having random vectors. In this paper, we discuss the statistical properties of estimates of the respective optimal value and optimal solutions when the random vectors are estimated by their sample both in the objective function and the constraints, which are based on perturbation analysis theory of second-order cone programming. As an example we consider the problem of minimizing a sum of norms with weights.
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Zhang, Liwei, Shengzhe Gao, and Saoyan Guo. "Statistical Inference of Second-Order Cone Programming." Asia-Pacific Journal of Operational Research 36, no. 02 (April 2019): 1940003. http://dx.doi.org/10.1142/s0217595919400037.

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In this paper, we study the stability of stochastic second-order programming when the probability measure is perturbed. Under the Lipschitz continuity of the objective function and metric regularity of the feasible set-valued mapping, the outer semicontinuity of the optimal solution set and Lipschitz continuity of optimal values are demonstrated. Moreover, we prove that, if the constraint non-degeneracy condition and strong second-order sufficient condition hold at a local minimum point of the original problem, there exists a Lipschitz continuous solution path satisfying the Karush–Kuhn–Tucker
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Liang, Zhizheng. "Feature Scaling via Second-Order Cone Programming." Mathematical Problems in Engineering 2016 (2016): 1–7. http://dx.doi.org/10.1155/2016/7347986.

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Feature scaling has attracted considerable attention during the past several decades because of its important role in feature selection. In this paper, a novel algorithm for learning scaling factors of features is proposed. It first assigns a nonnegative scaling factor to each feature of data and then adopts a generalized performance measure to learn the optimal scaling factors. It is of interest to note that the proposed model can be transformed into a convex optimization problem: second-order cone programming (SOCP). Thus the scaling factors of features in our method are globally optimal in
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Alzalg, Baha M. "Stochastic second-order cone programming: Applications models." Applied Mathematical Modelling 36, no. 10 (October 2012): 5122–34. http://dx.doi.org/10.1016/j.apm.2011.12.053.

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Rozprawy doktorskie na temat "Second-Order Cone Programming"

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Okuno, Takayuki. "Studies on Algorithms for Solving Generalized Second-Order Cone Programming Problems." 京都大学 (Kyoto University), 2013. http://hdl.handle.net/2433/174846.

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Chen, Jein-Shan. "Merit functions and nonsmooth functions for the second-order cone complementarity problem /." Thesis, Connect to this title online; UW restricted, 2004. http://hdl.handle.net/1773/5782.

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CAMARGO, JULIA DE TOLEDO. "THREE DIMENSIONAL LIMIT ANALYSIS USING SECOND ORDER CONE PROGRAMMING APPLIED TO SLOPE STABILITY." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2015. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=26876@1.

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PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO<br>CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO<br>FUNDAÇÃO DE APOIO À PESQUISA DO ESTADO DO RIO DE JANEIRO<br>Visando avaliar uma ferramenta numérica efetiva para resolução de problemas de estabilidade tridimensionais, a análise limite numérica foi estudada neste trabalho. Sua abordagem numérica requer o uso tanto do método dos elementos finitos quanto de programação matemática. Isto porque os teoremas da plasticidade, base da análise limite, podem ser colocados como problemas de otimização. No teorema do limite inferior, por
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Ciria, Suárez Héctor 1979. "Computation of upper and lower bounds in limit analysis using second-order cone programming and mesh adaptivity." Thesis, Massachusetts Institute of Technology, 2004. http://hdl.handle.net/1721.1/16655.

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Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2004.<br>Includes bibliographical references (p. 109-111).<br>This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.<br>Limit analysis is relevant in many practical engineering areas such as the design of mechanical structures or the analysis of soil mechanics. Assuming a rigid, perfectly-plastic solid subject to a static load distribution, the problem of limit analysis consists of finding the minimum multiple o
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Mohammad, Salimian. "A Mixed Integer Second Order Cone Programming Reformulation For A Congested Location And Capacity Allocation Problem On A Supply Chain Network." Master's thesis, METU, 2013. http://etd.lib.metu.edu.tr/upload/12615407/index.pdf.

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Supply chain network design involves location decisions for production facilities and distribution centers. We consider a make-to-order supply chain environment where distribution centers serve as crossdocking terminals. Long waiting times may occur at a cross-docking terminal, unless sucient handling capacity is installed. In this study, we deal with a facility location problem with congestion eects at distribution centers. Along with location decisions, we make capacity allocation (service rate) and demand allocation decisions so that the total cost, including facility opening, transportatio
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Bornhorst, Nils [Verfasser], Marius [Akademischer Betreuer] Pesavento, Martin [Akademischer Betreuer] Haardt, Anja [Akademischer Betreuer] Klein, and Sebastian [Akademischer Betreuer] Schöps. "Energy-Efficient Distributed Multicast Beamforming Using Iterative Second-Order Cone Programming / Nils Bornhorst. Betreuer: Marius Pesavento ; Martin Haardt ; Anja Klein ; Sebastian Schöps." Darmstadt : Universitäts- und Landesbibliothek Darmstadt, 2015. http://d-nb.info/1110980922/34.

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Chen, Jieqiu. "Convex relaxations in nonconvex and applied optimization." Diss., University of Iowa, 2010. https://ir.uiowa.edu/etd/654.

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Traditionally, linear programming (LP) has been used to construct convex relaxations in the context of branch and bound for determining global optimal solutions to nonconvex optimization problems. As second-order cone programming (SOCP) and semidefinite programming (SDP) become better understood by optimization researchers, they become alternative choices for obtaining convex relaxations and producing bounds on the optimal values. In this thesis, we study the use of these convex optimization tools in constructing strong relaxations for several nonconvex problems, including 0-1 integer programm
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Kim, Jae-Hak, and Jae-Hak Kim@anu edu au. "Camera Motion Estimation for Multi-Camera Systems." The Australian National University. Research School of Information Sciences and Engineering, 2008. http://thesis.anu.edu.au./public/adt-ANU20081211.011120.

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The estimation of motion of multi-camera systems is one of the most important tasks in computer vision research. Recently, some issues have been raised about general camera models and multi-camera systems. Using many cameras as a single camera is studied [60], and the epipolar geometry constraints of general camera models is theoretically derived. Methods for calibration, including a self-calibration method for general camera models, are studied [78, 62]. Multi-camera systems are an example of practically implementable general camera models and they are widely used in many applications nowaday
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Terrade, Benjamin. "Evaluation structurale des murs de soutènement en maçonnerie." Thesis, Paris Est, 2017. http://www.theses.fr/2017PESC1203/document.

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Partout où la pierre est facilement disponible, on trouve des constructions en maçonnerie de pierre. Suivant les coutumes et les usages, les blocs de pierres sont assemblés bruts, simplement ébauchés ou parfaitement taillés, avec ou sans l'ajout d'un liant. Supplantée par le béton dans les constructions neuves depuis le milieu du XX} siècle, les ouvrages en maçonnerie demeurent majoritaires dans le patrimoine bâti français, un patrimoine qu'il convient d'entretenir rationnellement. L'objectif de ce travail de thèse est de poursuivre l'élaboration d'un cadre scientifique rigoureux et opérationn
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Coutinho, Walton Pereira. "Um algoritmo branch-and-bound para o problema do caixeiro viajante suficientemente próximo." Universidade Federal da Paraí­ba, 2014. http://tede.biblioteca.ufpb.br:8080/handle/tede/5268.

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Made available in DSpace on 2015-05-08T14:53:38Z (GMT). No. of bitstreams: 1 arquivototal.pdf: 7900350 bytes, checksum: fbca2db827307d8c3ed2a1c15067d0da (MD5) Previous issue date: 2014-02-13<br>Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES<br>This research deals with the Close-Enough Traveling Salesman Problem, a variant of the Traveling Salesman Problem wich has several applicatios in logistics. In the Close-Enough Traveling Salesman Problem, rather than visiting the vertex (customer) itself, the salesman must visit a specific region containing such vertex. To sol
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Książki na temat "Second-Order Cone Programming"

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Prusty, Narayan, and Mehul Mohan. Learn ECMAScript - Second Edition: Discover the latest ECMAScript features in order to write cleaner code and learn the fundamentals of JavaScript. Packt Publishing - ebooks Account, 2018.

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Części książek na temat "Second-Order Cone Programming"

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Antoniou, Andreas, and Wu-Sheng Lu. "Quadratic, Semidefinite, and Second-Order Cone Programming." In Texts in Computer Science, 425–81. New York, NY: Springer US, 2021. http://dx.doi.org/10.1007/978-1-0716-0843-2_13.

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Kılınç-Karzan, Fatma, and Sercan Yıldız. "Two-Term Disjunctions on the Second-Order Cone." In Integer Programming and Combinatorial Optimization, 345–56. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-07557-0_29.

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Tsang, Ivor W., and James T. Kwok. "Efficient Hyperkernel Learning Using Second-Order Cone Programming." In Machine Learning: ECML 2004, 453–64. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-30115-8_42.

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Yang, Min. "Estimating the Fundamental Matrix Using Second-Order Cone Programming." In Artificial Intelligence and Computational Intelligence, 581–86. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-23896-3_72.

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Chi, Xiaoni, and Jin Peng. "A Combined Newton Method for Second-Order Cone Programming." In Advances in Soft Computing, 605–12. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-01216-7_64.

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Zhadan, Vitaly. "Dual Newton’s Methods for Linear Second-Order Cone Programming." In Mathematical Optimization Theory and Operations Research, 19–32. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-49988-4_2.

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Drewes, Sarah, and Stefan Ulbrich. "Subgradient Based Outer Approximation for Mixed Integer Second Order Cone Programming." In Mixed Integer Nonlinear Programming, 41–59. New York, NY: Springer New York, 2011. http://dx.doi.org/10.1007/978-1-4614-1927-3_2.

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Zhadan, Vitaly. "Dual Multiplicative-Barrier Methods for Linear Second-Order Cone Programming." In Communications in Computer and Information Science, 295–310. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-38603-0_22.

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Koldovský, Zbyněk, Jiří Málek, and Petr Tichavský. "Improving Relative Transfer Function Estimates Using Second-Order Cone Programming." In Latent Variable Analysis and Signal Separation, 227–34. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-22482-4_26.

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Zhadan, Vitaly. "A Variant of the Simplex Method for Second-Order Cone Programming." In Mathematical Optimization Theory and Operations Research, 115–29. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-22629-9_9.

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Streszczenia konferencji na temat "Second-Order Cone Programming"

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Chu, Eric, Neal Parikh, Alexander Domahidi, and Stephen Boyd. "Code generation for embedded second-order cone programming." In 2013 European Control Conference (ECC). IEEE, 2013. http://dx.doi.org/10.23919/ecc.2013.6669712.

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Malani, Shreya, Dinesh Dileep Gaurav, and Rahul Agrawal. "Link Prediction via Second Order Cone Programming." In the 10th ACM Conference. New York, New York, USA: ACM Press, 2019. http://dx.doi.org/10.1145/3292522.3326053.

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Debnath, R., and H. Takahashi. "SVM Training: Second-Order Cone Programming versus Quadratic Programming." In The 2006 IEEE International Joint Conference on Neural Network Proceedings. IEEE, 2006. http://dx.doi.org/10.1109/ijcnn.2006.246822.

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Raithatha, Ankor, Stephen Duncan, Kathryn Jackson, and Julian Allwood. "Second order cone programming in modeling incremental deformation." In 2007 American Control Conference. IEEE, 2007. http://dx.doi.org/10.1109/acc.2007.4282324.

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Mountcastle, Paul, Tom Henretty, Aale Naqvi, and Richard Lethin. "Embedded second-order cone programming with radar applications." In 2015 IEEE High Performance Extreme Computing Conference (HPEC). IEEE, 2015. http://dx.doi.org/10.1109/hpec.2015.7322454.

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Han, Yang, Chaohuan Hou, and Xiaochuan Ma. "Optimum Beamforming Based on Second Order Cone Programming." In 2008 Congress on Image and Signal Processing. IEEE, 2008. http://dx.doi.org/10.1109/cisp.2008.624.

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Qi, Zhiquan, Yingjie Tian, and Yong Shi. "Regularized multiple-criteria linear programming via second order cone programming formulations." In the Data Mining and Intelligent Knowledge Management Workshop. New York, New York, USA: ACM Press, 2012. http://dx.doi.org/10.1145/2462130.2462134.

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Tang, Maoqin, Qianwei He, Xiaoli Luo, Lei Liu, Yongji Wang, and Zhongtao Cheng. "Reentry Trajectory Optimization Based on Second Order Cone Programming." In 2020 Chinese Control And Decision Conference (CCDC). IEEE, 2020. http://dx.doi.org/10.1109/ccdc49329.2020.9164575.

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Zhong, Kai, Prateek Jain, and Ashish Kapoor. "Fast second-order cone programming for safe mission planning." In 2017 IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2017. http://dx.doi.org/10.1109/icra.2017.7989014.

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Guthrie, James, and Enrique Mallada. "Adversarial Model Predictive Control via Second-Order Cone Programming." In 2019 IEEE 58th Conference on Decision and Control (CDC). IEEE, 2019. http://dx.doi.org/10.1109/cdc40024.2019.9029244.

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Raporty organizacyjne na temat "Second-Order Cone Programming"

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Amela, R., R. Badia, S. Böhm, R. Tosi, C. Soriano, and R. Rossi. D4.2 Profiling report of the partner’s tools, complete with performance suggestions. Scipedia, 2021. http://dx.doi.org/10.23967/exaqute.2021.2.023.

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This deliverable focuses on the proling activities developed in the project with the partner's applications. To perform this proling activities, a couple of benchmarks were dened in collaboration with WP5. The rst benchmark is an embarrassingly parallel benchmark that performs a read and then multiple writes of the same object, with the objective of stressing the memory and storage systems and evaluate the overhead when these reads and writes are performed in parallel. A second benchmark is dened based on the Continuation Multi Level Monte Carlo (C-MLMC) algorithm. While this algorithm is norm
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