Relevant bibliographies by topics / Smoothing Newton method

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'Smoothing Newton method'

Author: Grafiati
Published: 18 January 2023
Last updated: 31 July 2025

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Journal articles on the topic "Smoothing Newton method"

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Liu, Xiangjing, and Jianke Zhang. "Strong Convergence of a Two-Step Modified Newton Method for Weighted Complementarity Problems." Axioms 12, no. 8 (2023): 742. http://dx.doi.org/10.3390/axioms12080742.

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This paper focuses on the weighted complementarity problem (WCP), which is widely used in the fields of economics, sciences and engineering. Not least because of its local superlinear convergence rate, smoothing Newton methods have widespread application in solving various optimization problems. A two-step smoothing Newton method with strong convergence is proposed. With a smoothing complementary function, the WCP is reformulated as a smoothing set of equations and solved by the proposed two-step smoothing Newton method. In each iteration, the new method computes the Newton equation twice, but
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Zhu, Jianguang, and Binbin Hao. "A new smoothing method for solving nonlinear complementarity problems." Open Mathematics 17, no. 1 (2019): 104–19. http://dx.doi.org/10.1515/math-2019-0011.

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Abstract In this paper, a new improved smoothing Newton algorithm for the nonlinear complementarity problem was proposed. This method has two-fold advantages. First, compared with the classical smoothing Newton method, our proposed method needn’t nonsingular of the smoothing approximation function; second, the method also inherits the advantage of the classical smoothing Newton method, it only needs to solve one linear system of equations at each iteration. Without the need of strict complementarity conditions and the assumption of P0 property, we get the global and local quadratic convergence
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WU, CAIYING, and GUOQING CHEN. "PREDICTOR–CORRECTOR SMOOTHING NEWTON METHOD FOR SOLVING SEMIDEFINITE PROGRAMMING." Bulletin of the Australian Mathematical Society 79, no. 3 (2009): 367–76. http://dx.doi.org/10.1017/s0004972708001214.

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AbstractThere has been much interest recently in smoothing methods for solving semidefinite programming (SDP). In this paper, based on the equivalent transformation for the optimality conditions of SDP, we present a predictor–corrector smoothing Newton algorithm for SDP. Issues such as the existence of Newton directions, boundedness of iterates, global convergence, and local superlinear convergence of our algorithm are studied under suitable assumptions.
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Yin, Hongxia. "An Adaptive Smoothing Method for Continuous Minimax Problems." Asia-Pacific Journal of Operational Research 32, no. 01 (2015): 1540001. http://dx.doi.org/10.1142/s0217595915400011.

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A simple and implementable two-loop smoothing method for semi-infinite minimax problem is given with the discretization parameter and the smoothing parameter being updated adaptively. We prove the global convergence of the algorithm when the steepest descent method or a BFGS type quasi-Newton method is applied to the smooth subproblems. The strategy for updating the smoothing parameter can not only guarantee the convergence of the algorithm but also considerably reduce the ill-conditioning caused by increasing the value of the smoothing parameter. Numerical tests show that the algorithm is rob
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Li, Meixia, and Haitao Che. "A Smoothing Inexact Newton Method for Generalized Nonlinear Complementarity Problem." Mathematical Problems in Engineering 2012 (2012): 1–17. http://dx.doi.org/10.1155/2012/401835.

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Based on the smoothing function of penalized Fischer-Burmeister NCP-function, we propose a new smoothing inexact Newton algorithm with non-monotone line search for solving the generalized nonlinear complementarity problem. We view the smoothing parameter as an independent variable. Under suitable conditions, we show that any accumulation point of the generated sequence is a solution of the generalized nonlinear complementarity problem. We also establish the local superlinear (quadratic) convergence of the proposed algorithm under the BD-regular assumption. Preliminary numerical experiments ind
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Feng, Ning, Zhi Yuan Tian, and Xin Lei Qu. "A Smoothing Newton Method for Nonlinear Complementarity Problems." Applied Mechanics and Materials 475-476 (December 2013): 1090–93. http://dx.doi.org/10.4028/www.scientific.net/amm.475-476.1090.

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A new FB-function based on the P0 function is given in this paper. The nonlinear complementarity problem is reformulated to solve equivalent equations based on the FB-function. A modified smooth Newton method is proposed for nonlinear complementarity problem. Under mild conditions, the global convergence of the algorithm is proved. The numerical experiment shows that the algorithm is potentially efficient.
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Yong, Longquan. "A Smoothing Newton Method for Absolute Value Equation." International Journal of Control and Automation 9, no. 2 (2016): 119–32. http://dx.doi.org/10.14257/ijca.2016.9.2.12.

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Li, Dong-Hui, Liqun Qi, Judy Tam, and Soon-Yi Wu. "A Smoothing Newton Method for Semi-Infinite Programming." Journal of Global Optimization 30, no. 2-3 (2004): 169–94. http://dx.doi.org/10.1007/s10898-004-8266-z.

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Tang, Jingyong, Li Dong, Jinchuan Zhou, and Liang Fang. "A smoothing Newton method for nonlinear complementarity problems." Computational and Applied Mathematics 32, no. 1 (2013): 107–18. http://dx.doi.org/10.1007/s40314-013-0015-9.

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Qi, L., and D. Sun. "Smoothing Functions and Smoothing Newton Method for Complementarity and Variational Inequality Problems." Journal of Optimization Theory and Applications 113, no. 1 (2002): 121–47. http://dx.doi.org/10.1023/a:1014861331301.

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Dissertations / Theses on the topic "Smoothing Newton method"

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Ferzly, Joëlle. "Adaptive inexact smoothing Newton method for nonlinear systems with complementarity constraints. Application to a compositional multiphase flow in porous media." Thesis, Sorbonne université, 2022. http://www.theses.fr/2022SORUS376.

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Nous considérons des inégalités variationnelles écrites sous forme d'équations aux dérivées partielles avec contraintes de complémentarité non linéaires. La discrétisation de tels problèmes conduit à des systèmes discrets non linéaires et non différentiables qui peuvent être résolus en employant une méthode de linéarisation itérative de type semi-lisse. Notre objectif est de concevoir une approche de régularisation qui approxime le problème par un système d'équations non linéaires différentiables. Une application directe des méthodes classiques de type Newton est ainsi possible. Nous construis
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Lin, Tzu-Ching, and 林子靖. "A smoothing Newton method based on the generalized Fischer-Burmeister function for MCPs." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/hg76p7.

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碩士<br>國立臺灣師範大學<br>數學系<br>97<br>We present a smooth approximation for the generalized Fischer-Burmeister function where the 2-norm in the FB function is relaxed to a general p-norm (p > 1), and establish some favorable properties for it, for example, the Jacobian consistency. With the smoothing function, we transform the mixed complementarity problem (MCP) into solving a sequence of smooth system of equations.
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Books on the topic "Smoothing Newton method"

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Ulbrich, Michael, Liqun Qi, and Defeng Sun. Semismooth and Smoothing Newton Methods. Springer, 2021.

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Book chapters on the topic "Smoothing Newton method"

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Zhang, Jie, and Shao-Ping Rui. "Globally Convergent Inexact Smoothing Newton Method for SOCCP." In Advances in Intelligent and Soft Computing. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-22833-9_52.

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Solodov, Michael V., and Benav F. Svaiter. "A Globally Convergent Inexact Newton Method for Systems of Monotone Equations." In Reformulation: Nonsmooth, Piecewise Smooth, Semismooth and Smoothing Methods. Springer US, 1998. http://dx.doi.org/10.1007/978-1-4757-6388-1_18.

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Liu, Lixia, and Sanyang Liu. "A New Smoothing Newton Method for Symmetric Cone Complementarity Problems." In Algorithmic Aspects in Information and Management. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-14355-7_21.

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Chen, Weibing, Hongxia Yin, and Yingjie Tian. "Smoothing Newton Method for L 1 Soft Margin Data Classification Problem." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-01973-9_61.

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Qi, L., and G. Zhou. "A Smoothing Newton Method for Ball Constrained Variational Inequalities with Applications." In Topics in Numerical Analysis. Springer Vienna, 2001. http://dx.doi.org/10.1007/978-3-7091-6217-0_16.

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Fang, Liang, Xianming Kong, Xiaoyan Ma, Han Li, and Wei Zhang. "A One-Step Smoothing Newton Method Based on a New Class of One-Parametric Nonlinear Complementarity Functions for P 0-NCP." In Advances in Neural Networks - ISNN 2010. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-13278-0_15.

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Chen, Xiaojun, Nami Matsunaga, and Tetsuro Yamamoto. "Smoothing Newton Methods for Nonsmooth Dirichlet Problems." In Reformulation: Nonsmooth, Piecewise Smooth, Semismooth and Smoothing Methods. Springer US, 1998. http://dx.doi.org/10.1007/978-1-4757-6388-1_4.

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Christensen, Peter W., and Jong-Shi Pang. "Frictional Contact Algorithms Based on Semismooth Newton Methods." In Reformulation: Nonsmooth, Piecewise Smooth, Semismooth and Smoothing Methods. Springer US, 1998. http://dx.doi.org/10.1007/978-1-4757-6388-1_5.

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Li, Wu, and John Swetits. "Regularized Newton Methods for Minimization of Convex Quadratic Splines with Singular Hessians." In Reformulation: Nonsmooth, Piecewise Smooth, Semismooth and Smoothing Methods. Springer US, 1998. http://dx.doi.org/10.1007/978-1-4757-6388-1_12.

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Qi, L., and D. Sun. "A Survey of Some Nonsmooth Equations and Smoothing Newton Methods." In Applied Optimization. Springer US, 1999. http://dx.doi.org/10.1007/978-1-4613-3285-5_7.

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Conference papers on the topic "Smoothing Newton method"

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Yu, Haodong. "A Smoothing Active-Set Newton Method for Constrained Optimization." In 2012 Fifth International Joint Conference on Computational Sciences and Optimization (CSO). IEEE, 2012. http://dx.doi.org/10.1109/cso.2012.95.

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Jiang, Xiaoqin. "A Smoothing Newton Method for Solving Absolute Value Equations." In 2nd International Conference On Systems Engineering and Modeling. Atlantis Press, 2013. http://dx.doi.org/10.2991/icsem.2013.94.

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Chi, Xiaoni, and Xiaoyong Liao. "A Squared Smoothing Newton Method for Second-Order Cone Programming." In 2010 Third International Conference on Information and Computing Science (ICIC). IEEE, 2010. http://dx.doi.org/10.1109/icic.2010.185.

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Su, Ke, and Xiaoli Lu. "A New Smoothing Inexact Newton Method for Generalized Nonlinear Complementarity Problem." In 2013 Sixth International Conference on Business Intelligence and Financial Engineering (BIFE). IEEE, 2013. http://dx.doi.org/10.1109/bife.2013.130.

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Yaghoobi, Fatemeh, Hany Abdulsamad, and Simo Särkkä. "A Recursive Newton Method for Smoothing in Nonlinear State Space Models." In 2023 31st European Signal Processing Conference (EUSIPCO). IEEE, 2023. http://dx.doi.org/10.23919/eusipco58844.2023.10290119.

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Yousefian, Farzad, Angelia Nedic, and Uday V. Shanbhag. "A smoothing stochastic quasi-newton method for non-lipschitzian stochastic optimization problems." In 2017 Winter Simulation Conference (WSC). IEEE, 2017. http://dx.doi.org/10.1109/wsc.2017.8247960.

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Zhao, Huali, and Hongwei Liu. "Predictor-Corrector Smoothing Newton Method for Solving the Second-Order Cone Complementarity." In 2010 International Conference on Intelligent Computation Technology and Automation (ICICTA). IEEE, 2010. http://dx.doi.org/10.1109/icicta.2010.590.

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He, Yanling, and Chunyan Liu. "Sub-quadratic convergence of a smoothing Newton method for symmetric cone complementarity problems." In 2015 27th Chinese Control and Decision Conference (CCDC). IEEE, 2015. http://dx.doi.org/10.1109/ccdc.2015.7162450.

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Zhao, Hua-Li, and Hong-Wei Liu. "A Predictor-corrector Smoothing Newton Method for Solving the Second-order Cone Complementarity." In 2010 International Conference on Computational Aspects of Social Networks (CASoN 2010). IEEE, 2010. http://dx.doi.org/10.1109/cason.2010.66.

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Eltahan, Esmail, Faruk Omer Alpak, and Kamy Sepehrnoori. "A Quasi-Newton Method for Well Location Optimization Under Uncertainty." In SPE Reservoir Simulation Conference. SPE, 2023. http://dx.doi.org/10.2118/212212-ms.

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Abstract Subsurface development involves well-placement decisions considering the highly uncertain understanding of the reservoir in the subsurface. The simultaneous optimization of a large number of well locations is a challenging problem. Conventional gradient-based methods are known to perform efficiently for well-placement optimization problems when such problems are translated into real-valued representations, and special noisy objective function handling protocols are implemented. However, applying such methods to large-scale problems may still be impractical because the gradients of the
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