Academic literature on the topic 'Second-Order Cone Programming'
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Journal articles on the topic "Second-Order Cone Programming"
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.
Full textKobayashi, 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.
Full textHang, 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.
Full textXia, 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.
Full textLobo, 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.
Full textAverbakh, 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.
Full textWang, 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.
Full textZhang, 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.
Full textLiang, Zhizheng. "Feature Scaling via Second-Order Cone Programming." Mathematical Problems in Engineering 2016 (2016): 1–7. http://dx.doi.org/10.1155/2016/7347986.
Full textAlzalg, 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.
Full textDissertations / Theses on the topic "Second-Order Cone Programming"
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.
Full textChen, 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.
Full textCAMARGO, 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.
Full textCONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO
FUNDAÇÃO DE APOIO À PESQUISA DO ESTADO DO RIO DE JANEIRO
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 exemplo, se deseja maximizar o fator de colapso, com o solo sujeito a condições de equilíbrio e ao critério de ruptura. O critério de ruptura utilizado foi o de Drucker-Prager. Neste trabalho, fez-se uso da programação cônica quadrática, conhecida por possibilitar a resolução de problemas de grande escala com muita eficiência. Empregou-se, para tanto, o solver Mosek. Além de ser possível determinar o fator de colapso, também se desenvolveu um método para calcular o fator de segurança da encosta. Ele reduz sucessivamente os parâmetros de resistência do solo, através do método de Newton-Raphson. Em casos de geometrias mais complexas, a formulação do problema teve que ser modificada. Uma força horizontal fictícia foi adicionada na condição de equilíbrio e unicamente ela foi majorada com o fator de colapso. Foi apenas através desta formulação que se pode simular a estabilidade de solos submetidos ao efeito de poropressão. A análise de fluxo foi simulada a parte no programa de elementos finitos desenvolvido por Miqueletto (2007). A resistência do solo depende dos valores de poropressão, que caracterizam os solos como saturados ou não saturados.
Numerical limit analysis was studied in order to evaluate an effective numerical procedure to solve three-dimensional slope stability problems. This numerical approach utilizes finite element method and mathematical programming. Mathematical programming is needed because the plasticity theorems, basic theorems for limit analysis, can be cast as optimization problems. The lower bound theorem consists of finding the maximum collapse multiplier that will lead the soil to the imminence of collapse. The soil will still be restricted to equilibrium conditions and the yield criterion will have to be satisfied everywhere. Drucker- Prager was the yield criterion chosen. In this thesis, the optimization problem is reformulated as a second order cone programming (SOCP). SOCP is known to solve large-scale problems with great computational efficiency and we used the solver Mosek. The model calculates not only the collapse multiplier, but also the safety factor for the slope. A strength reduction scheme was proposed, based on the Newton-Raphson method. For complex geometries cases, a novel formulation was developed. A fictitious horizontal force was added at the equilibrium equation and uniquely this force was increased by the multiplier factor. It was only through this reformulation that it was possible to assess stability of slopes subjected to porepressure effects. The groundwater flow was simulated separately in a finite element program developed by Miqueletto (2007). The soil strength depends on porepressure values, which define soils as saturated or unsaturated.
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.
Full textIncludes bibliographical references (p. 109-111).
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
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 of this load distribution that will cause the body to collapse. This collapse multiplier results from solving an infinite dimensional saddle point problem, where the internal work rate is maximized over an admissible set of stresses -defined by a yield condition- and minimized over the linear space of kinematically admissible velocities for which the external work rate equals the unity. When strong duality is applied to this saddle point problem, the well-known convex (and equivalent) static and kinematic principles of limit analysis arise. In this thesis, an efficient procedure to compute strict upper and lower bounds for the exact collapse multiplier is presented, with a formulation that explicitly considers the exact convex yield condition. The approach consists of two main steps. First, the continuous problem, under the form of the static principle, is discretized twice (one per bound) by means of different combinations of finite element spaces for the stresses and velocities. For each discretization, the interpolation spaces are chosen so that the attainment of an upper or a lower bound is guaranteed. The second step consists of solving the resulting discrete nonlinear optimization problems. Towards this end, they are reformulated into the canonical form of Second-order Cone Programs, which allows for the use of primal-dual interior point methods that optimally exploit the convexity and duality properties of the limit analysis
(cont.) model and guarantee global convergence to the optimal solutions. To exploit the fact that collapse mechanisms are typically highly localized, a novel method for adaptive meshing is introduced based on local bound gap measures and not on heuristic estimates. The method decomposes the total bound gap as the sum of positive elemental contributions from each element in the mesh, and refines only those elements which are responsible for the majority of the numerical error. Finally, stand-alone computational certificates that allow the bounds to be verified independently, without recourse to the original computer program, are also provided. This removes the uncertainty about the reliability of the results, which frequently undermines the utility of computational simulations. The efficiency of the methodology proposed is illustrated with several applications in plane stress and plane strain, demonstrating that it can be used in complex, realistic problems as a supplement to other models.
by Héctor Ciria Suárez.
S.M.
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.
Full textBornhorst, 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.
Full textChen, Jieqiu. "Convex relaxations in nonconvex and applied optimization." Diss., University of Iowa, 2010. https://ir.uiowa.edu/etd/654.
Full textKim, 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.
Full textTerrade, Benjamin. "Evaluation structurale des murs de soutènement en maçonnerie." Thesis, Paris Est, 2017. http://www.theses.fr/2017PESC1203/document.
Full textWherever stone is readily available, we encounter stone masonry buildings. Depending on customs or dedicated use, the blocks are used raw, lightly faced or perfectly cut, with or without the use of mortar. Althougth concrete has replaced masonry in new construction for some decades, the better part of the French built heritage is made of masonry, an heritage we are responsible for. This works aims at contributing to create a reliable scientific frame for that purpose. This thesis uses the yield design theory alongside with homogenisation techniques to study the stability of stone masonry earth retaining walls. First, we provide an analytical tool suitable for designing new structures or assessing the stability of existing ones that are still in good shape. Should it be needed, this tools allows for the design of a strengthening solution based on soil-nailing. Then, we implement it in a finite element code to give it the versatility required to study unconventionnal structures or structures badly damaged. We then present several experimental campaigns aiming at validating the proposed tools
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.
Full textCoordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES
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 solve this problem, we propose a simple yet effective exact algorithm, based on Branch-and-Bound and Second Order Cone Programming. The proposed algorithm was tested in 824 instances suggested in the literature. Optimal solutions are obtained for open problems with up to a thousand vertices. We consider both instances in the two- and three-dimensional space.
Esta pesquisa trata do Problema do Caixeiro Viajante Suficientemente Próximo, uma variante do Problema do Caixeiro Viajante que possui diversas aplicações em logística. No Problema do Caixeiro Viajante Suficientemente Próximo, ao invés de visitar o próprio vértice (cliente), o caixeiro deve visitar uma região especifica contendo este vértice. Para resolver este problema, é proposto um algoritmo exato, simples e efetivo, baseado em branch-and-bound e Programação Cônica de Segunda Ordem. O algoritmo proposto foi testado em 824 instâncias sugeridas na literatura. Soluções ótimas foram obtidas para instâncias com até mil vértices. Foram consideradas instâncias nos espaços bi e tridimensional.
Books on the topic "Second-Order Cone Programming"
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.
Find full textBook chapters on the topic "Second-Order Cone Programming"
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.
Full textKılınç-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.
Full textTsang, 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.
Full textYang, 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.
Full textChi, 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.
Full textZhadan, 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.
Full textDrewes, 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.
Full textZhadan, 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.
Full textKoldovský, 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.
Full textZhadan, 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.
Full textConference papers on the topic "Second-Order Cone Programming"
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.
Full textMalani, 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.
Full textDebnath, 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.
Full textRaithatha, 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.
Full textMountcastle, 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.
Full textHan, 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.
Full textQi, 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.
Full textTang, 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.
Full textZhong, 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.
Full textGuthrie, 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.
Full textReports on the topic "Second-Order Cone Programming"
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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