Relevant bibliographies by topics / Semismooth

Contents

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

Academic literature on the topic 'Semismooth'

Author: Grafiati
Published: 24 April 2022

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Journal articles on the topic "Semismooth"

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Sun, Defeng, and Jie Sun. "Semismooth Matrix-Valued Functions." Mathematics of Operations Research 27, no. 1 (February 2002): 150–69. http://dx.doi.org/10.1287/moor.27.1.150.342.

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Farrell, Patrick E., Matteo Croci, and Thomas M. Surowiec. "Deflation for semismooth equations." Optimization Methods and Software 35, no. 6 (May 16, 2019): 1248–71. http://dx.doi.org/10.1080/10556788.2019.1613655.

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Bolte, Jérôme, Aris Daniilidis, and Adrian Lewis. "Tame functions are semismooth." Mathematical Programming 117, no. 1-2 (July 21, 2007): 5–19. http://dx.doi.org/10.1007/s10107-007-0166-9.

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Yang, Y. F. "A new trust region method for nonsmooth equations." ANZIAM Journal 44, no. 4 (April 2003): 595–607. http://dx.doi.org/10.1017/s1446181100012967.

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AbstractWe propose a new trust region algorithm for solving the system of nonsmooth equations F(x) = 0 by using a smooth function satisfying the Jacobian consistency property to approximate the nonsmooth function F(x). Compared with existing trust region methods for systems of nonsmooth equations, the proposed algorithm possesses some nice convergence properties. Global convergence is established and, in particular, locally superlinear or quadratical convergence is obtained if F is semismooth or strongly semismooth at the solution.
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Izmailov, Alexey F., Alexey S. Kurennoy, and Mikhail V. Solodov. "The Josephy–Newton Method for Semismooth Generalized Equations and Semismooth SQP for Optimization." Set-Valued and Variational Analysis 21, no. 1 (July 18, 2012): 17–45. http://dx.doi.org/10.1007/s11228-012-0218-z.

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Zhou, Shui-sheng, Hong-wei Liu, Li-hua Zhou, and Feng Ye. "Semismooth Newton support vector machine." Pattern Recognition Letters 28, no. 15 (November 2007): 2054–62. http://dx.doi.org/10.1016/j.patrec.2007.06.010.

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Pickl, Stefan. "Solving the semismooth equivalence problem." European Journal of Operational Research 157, no. 1 (August 2004): 68–73. http://dx.doi.org/10.1016/j.ejor.2003.05.003.

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Potra, Florian A., Liqun Qi, and Defeng Sun. "Secant methods for semismooth equations." Numerische Mathematik 80, no. 2 (August 1, 1998): 305–24. http://dx.doi.org/10.1007/s002110050369.

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Bonettini, Silvia, and Federica Tinti. "A nonmonotone semismooth inexact Newton method." Optimization Methods and Software 22, no. 4 (August 2007): 637–57. http://dx.doi.org/10.1080/10556780601079258.

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Movahedian, Nooshin. "Nonsmooth Calculus of Semismooth Functions and Maps." Journal of Optimization Theory and Applications 160, no. 2 (September 5, 2013): 415–38. http://dx.doi.org/10.1007/s10957-013-0407-4.

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Dissertations / Theses on the topic "Semismooth"

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Petra, Stefania. "Semismooth least squares methods for complementarity problems." Doctoral thesis, [S.l.] : [s.n.], 2006. http://deposit.ddb.de/cgi-bin/dokserv?idn=98174558X.

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Tezel, Ozturan Aysun. "A Semismooth Newton Method For Generalized Semi-infinite Programming Problems." Phd thesis, METU, 2010. http://etd.lib.metu.edu.tr/upload/3/12612130/index.pdf.

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Semi-infinite programming problems is a class of optimization problems in finite dimensional variables which are subject to infinitely many inequality constraints. If the infinite index of inequality constraints depends on the decision variable, then the problem is called generalized semi-infinite programming problem (GSIP). If the infinite index set is fixed, then the problem is called standard semi-infinite programming problem (SIP). In this thesis, convergence of a semismooth Newton method for generalized semi-infinite programming problems with convex lower level problems is investigated. In this method, using nonlinear complementarity problem functions the upper and lower level Karush-Kuhn-Tucker conditions of the optimization problem are reformulated as a semismooth system of equations. A possible violation of strict complementary slackness causes nonsmoothness. In this study, we show that the standard regularity condition for convergence of the semismooth Newton method is satisfied under natural assumptions for semi-infinite programs. In fact, under the Reduction Ansatz in the lower level problem and strong stability in the reduced upper level problem this regularity condition is satisfied. In particular, we do not have to assume strict complementary slackness in the upper level. Furthermore, in this thesis we neither assume strict complementary slackness in the upper nor in the lower level. In the case of violation of strict complementary slackness in the lower level, the auxiliary functions of the locally reduced problem are not necessarily twice continuously differentiable. But still, we can show that a standard regularity condition for quadratic convergence of the semismooth Newton method holds under a natural assumption for semi-infinite programs. Numerical examples from, among others, design centering and robust optimization illustrate the performance of the method.
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Hans, Esther [Verfasser]. "Globally convergent B-semismooth Newton methods for l1-Tikhonov regularization / Esther Hans." Mainz : Universitätsbibliothek Mainz, 2017. http://d-nb.info/1131905032/34.

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Buchholzer, Hannes [Verfasser], and Christian [Akademischer Betreuer] Kanzow. "The Semismooth Newton Method for the Solution of Reactive Transport Problems Including Mineral Precipitation-Dissolution Reactions / Hannes Buchholzer. Betreuer: Christian Kanzow." Würzburg : Universitätsbibliothek der Universität Würzburg, 2011. http://d-nb.info/1015734359/34.

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Sabit, Souhila. "Les méthodes numériques de transport réactif." Phd thesis, Université Rennes 1, 2014. http://tel.archives-ouvertes.fr/tel-01057870.

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La modélisation du transport réactif du contaminant en milieu poreux est un problème complexe cumulant les difficultés de la modélisation du transport avec celles de la modélisation de la chimie et surtout du couplage entre les deux. Cette modélisation conduit à un système d'équations aux dérivées partielles et algébriques dont les inconnues sont les quantités d'espèces chimiques. Une approche possible, déjà utilisée par ailleurs, est de choisir la méthode globale DAE : l'utilisation d'une méthode de lignes, correspondant à la discrétisation en espace seulement, conduit à un système différentiel algébrique (DAE) qui doit être résolu par un solveur adapté. Dans notre cas, on utilise le solveur IDA de Sundials qui s'appuie sur une méthode implicite, à ordre et pas variables, et qui requiert à chaque pas de temps la résolution d'un grand système non linéaire associé à une matrice jacobienne. Cette méthode est implémentée dans un logiciel qui s'appelle GRT3D (Transport Réactif Global en 3D). Le présent travail présente une amélioration de la méthode GDAE, du point de vue de la performance, de la stabilité et de la robustesse. Nous avons ainsi enrichi les possibilités de GRT3D, par la prise en compte complète des équations de précipitation-dissolution permettant l'apparition ou la disparition d'une espèce précipitée. En complément de l'étude de la méthode GDAE, nous présentons aussi une méthode séquentielle non itérative (SNIA), qui est une méthode basée sur le schéma d'Euler explicite : à chaque pas de temps, on résout explicitement l'équation de transport et on utilise ces calculs comme données pour le système chimique, résolu dans chaque maille de façon indépendante. Nous présentons aussi une comparaison entre cette méthode et l'approche GDAE. Des résultats numériques pour deux cas tests, celui proposé par l'ANDRA (cas-test 2D) d'une part, celui proposé par le groupe MoMas (Benchmark "easy case") d'autre part, sont enfin présentés, commentés et analysés.
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Fukuda, Ellen Hidemi. "Tópicos em penalidades exatas diferenciáveis." Universidade de São Paulo, 2011. http://www.teses.usp.br/teses/disponiveis/45/45132/tde-04052011-114740/.

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Durante as décadas de 70 e 80, desenvolveram-se métodos baseados em penalidades exatas diferenciáveis para resolver problemas de otimização não linear com restrições. Uma desvantagem dessas penalidades é que seus gradientes contêm termos de segunda ordem em suas fórmulas, o que impede a utilização de métodos do tipo Newton para resolver o problema. Para contornar essa dificuldade, utilizamos uma ideia de construção de penalidade exata para desigualdades variacionais, introduzida recentemente por André e Silva. Essa construção consiste em incorporar um estimador de multiplicadores, proposto por Glad e Polak, no lagrangiano aumentado para desigualdades variacionais. Nesse trabalho, estendemos o estimador de multiplicadores para restrições gerais de igualdade e desigualdade, e enfraquecemos a hipótese de regularidade. Como resultado, obtemos uma função penalidade exata continuamente diferenciável e uma nova reformulação do sistema KKT associado a problemas não lineares. A estrutura dessa reformulação permite a utilização do método de Newton semi-suave, e a taxa de convergência local superlinear pode ser provada. Além disso, verificamos que a penalidade exata construída pode ser usada para globalizar o método, levando a uma abordagem do tipo Gauss-Newton. Por fim, realizamos experimentos numéricos baseando-se na coleção CUTE de problemas de teste.
During the 1970\'s and 1980\'s, methods based on differentiable exact penalty functions were developed to solve constrained optimization problems. One drawback of these functions is that they contain second-order terms in their gradient\'s formula, which do not allow the use of Newton-type methods. To overcome such difficulty, we use an idea for construction of exact penalties for variational inequalities, introduced recently by André and Silva. This construction consists on incorporating a multipliers estimate, proposed by Glad and Polak, in the augmented Lagrangian function for variational inequalities. In this work, we extend the multipliers estimate to deal with both equality and inequality constraints and we weaken the regularity assumption. As a result, we obtain a continuous differentiable exact penalty function and a new equation reformulation of the KKT system associated to nonlinear problems. The formula of such reformulation allows the use of semismooth Newton method, and the local superlinear convergence rate can be also proved. Besides, we note that the exact penalty function can be used to globalize the method, resulting in a Gauss-Newton-type approach. We conclude with some numerical experiments using the collection of test problems CUTE.
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Sanja, Rapajić. "Iterativni postupci sa regularizacijom za rešavanje nelinearnih komplementarnih problema." Phd thesis, Univerzitet u Novom Sadu, Prirodno-matematički fakultet u Novom Sadu, 2005. https://www.cris.uns.ac.rs/record.jsf?recordId=6022&source=NDLTD&language=en.

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U doktorskoj disertaciji razmatrani su iterativni postupci za rešavanje nelinearnih komplementarnih problema (NCP). Problemi ovakvog tipa javljaju se u teoriji optimizacije, inženjerstvu i ekonomiji. Matematički modeli mnogih prirodnih, društvenih i tehničkih procesa svode se takođe na ove probleme. Zbog izuzetno velike zastupljenosti NCP problema, njihovo rešavanje je veoma aktuelno. Među mnogobrojnim numeričkim postupcima koji se koriste u tu svrhu, u ovoj disertaciji posebna pažnja posvećena jegeneralizovanim postupcima Njutnovog tipa i iterativnim postupcima sa re-gularizacijom matrice jakobijana. Definisani su novi postupci za rešavanje NCP i dokazana je njihova lokalna ili globalna konvergencija. Dobijeni teorijski rezultati testirani su na relevantnim numeričkim primerima.
Iterative methods for nonlinear complementarity problems (NCP) are con-sidered in this doctoral dissertation. NCP problems appear in many math-ematical models from economy, engineering and optimization theory. Solv-ing NCP is very atractive in recent years. Among many numerical methods for NCP, we are interested in generalized Newton-type methods and Jaco-bian smoothing methođs. Several new methods for NCP are defined in this dissertation and their local or global convergence is proved. Theoretical results are tested on relevant numerical examples.
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Rösel, Simon. "Approximation of nonsmooth optimization problems and elliptic variational inequalities with applications to elasto-plasticity." Doctoral thesis, Humboldt-Universität zu Berlin, Mathematisch-Naturwissenschaftliche Fakultät, 2017. http://dx.doi.org/10.18452/17778.

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Optimierungsprobleme und Variationsungleichungen über Banach-Räumen stellen Themen von substantiellem Interesse dar, da beide Problemklassen einen abstrakten Rahmen für zahlreiche Anwendungen aus verschiedenen Fachgebieten stellen. Nach einer Einführung in Teil I werden im zweiten Teil allgemeine Approximationsmethoden, einschließlich verschiedener Diskretisierungs- und Regularisierungsansätze, zur Lösung von nichtglatten Variationsungleichungen und Optimierungsproblemen unter konvexen Restriktionen vorgestellt. In diesem allgemeinen Rahmen stellen sich gewisse Dichtheitseigenschaften der konvexen zulässigen Menge als wichtige Voraussetzungen für die Konsistenz einer abstrakten Klasse von Störungen heraus. Im Folgenden behandeln wir vor allem Restriktionsmengen in Sobolev-Räumen, die durch eine punktweise Beschränkung an den Funktionswert definiert werden. Für diesen Restriktionstyp werden verschiedene Dichtheitsresultate bewiesen. In Teil III widmen wir uns einem quasi-statischen Kontaktproblem der Elastoplastizität mit Härtung. Das entsprechende zeit-diskretisierte Problem kann als nichtglattes, restringiertes Minimierungsproblem betrachtet werden. Zur Lösung wird eine Pfadverfolgungsmethode auf Basis des verallgemeinerten Newton-Verfahrens entwickelt, dessen Teilprobleme lokal superlinear und gitterunabhängig lösbar sind. Teil III schließt mit verschiedenen numerischen Beispielen. Der letzte Teil der Arbeit ist der quasi-statischen, perfekten Plastizität gewidmet. Auf Basis des primalen Problems der perfekten Plastizität leiten wir eine reduzierte Formulierung her, die es erlaubt, das primale Problem als Fenchel-dualisierte Form des klassischen zeit-diskretisierten Spannungsproblems zu verstehen. Auf diese Weise werden auch neue Optimalitätsbedingungen hergeleitet. Zur Lösung des Problems stellen wir eine modifizierte Form der viskoplastischen Regularisierung vor und beweisen die Konvergenz dieses neuen Regularisierungsverfahrens.
Optimization problems and variational inequalities over Banach spaces are subjects of paramount interest since these mathematical problem classes serve as abstract frameworks for numerous applications. Solutions to these problems usually cannot be determined directly. Following an introduction, part II presents several approximation methods for convex-constrained nonsmooth variational inequality and optimization problems, including discretization and regularization approaches. We prove the consistency of a general class of perturbations under certain density requirements with respect to the convex constraint set. We proceed with the study of pointwise constraint sets in Sobolev spaces, and several density results are proven. The quasi-static contact problem of associative elasto-plasticity with hardening at small strains is considered in part III. The corresponding time-incremental problem can be equivalently formulated as a nonsmooth, constrained minimization problem, or, as a mixed variational inequality problem over the convex constraint. We propose an infinite-dimensional path-following semismooth Newton method for the solution of the time-discrete plastic contact problem, where each path-problem can be solved locally at a superlinear rate of convergence with contraction rates independent of the discretization. Several numerical examples support the theoretical results. The last part is devoted to the quasi-static problem of perfect (Prandtl-Reuss) plasticity. Building upon recent developments in the study of the (incremental) primal problem, we establish a reduced formulation which is shown to be a Fenchel predual problem of the corresponding stress problem. This allows to derive new primal-dual optimality conditions. In order to solve the time-discrete problem, a modified visco-plastic regularization is proposed, and we prove the convergence of this new approximation scheme.
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Calatroni, Luca. "New PDE models for imaging problems and applications." Thesis, University of Cambridge, 2016. https://www.repository.cam.ac.uk/handle/1810/256139.

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Variational methods and Partial Differential Equations (PDEs) have been extensively employed for the mathematical formulation of a myriad of problems describing physical phenomena such as heat propagation, thermodynamic transformations and many more. In imaging, PDEs following variational principles are often considered. In their general form these models combine a regularisation and a data fitting term, balancing one against the other appropriately. Total variation (TV) regularisation is often used due to its edgepreserving and smoothing properties. In this thesis, we focus on the design of TV-based models for several different applications. We start considering PDE models encoding higher-order derivatives to overcome wellknown TV reconstruction drawbacks. Due to their high differential order and nonlinear nature, the computation of the numerical solution of these equations is often challenging. In this thesis, we propose directional splitting techniques and use Newton-type methods that despite these numerical hurdles render reliable and efficient computational schemes. Next, we discuss the problem of choosing the appropriate data fitting term in the case when multiple noise statistics in the data are present due, for instance, to different acquisition and transmission problems. We propose a novel variational model which encodes appropriately and consistently the different noise distributions in this case. Balancing the effect of the regularisation against the data fitting is also crucial. For this sake, we consider a learning approach which estimates the optimal ratio between the two by using training sets of examples via bilevel optimisation. Numerically, we use a combination of SemiSmooth (SSN) and quasi-Newton methods to solve the problem efficiently. Finally, we consider TV-based models in the framework of graphs for image segmentation problems. Here, spectral properties combined with matrix completion techniques are needed to overcome the computational limitations due to the large amount of image data. Further, a semi-supervised technique for the measurement of the segmented region by means of the Hough transform is proposed.
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Petra, Stefania [Verfasser]. "Semismooth least squares methods for complementarity problems / vorgelegt von Stefania Petra." 2006. http://d-nb.info/98174558X/34.

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Books on the topic "Semismooth"

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Fukushima, Masao, and Liqun Qi, eds. Reformulation: Nonsmooth, Piecewise Smooth, Semismooth and Smoothing Methods. Boston, MA: Springer US, 1999. http://dx.doi.org/10.1007/978-1-4757-6388-1.

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Fukushima, Masao. Reformulation: Nonsmooth, Piecewise Smooth, Semismooth and Smoothing Methods. Boston, MA: Springer US, 1999.

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Semismooth Newton methods for variational inequalities and constrained optimization problems in function spaces. Philadelphia: Society for Industrial and Applied Mathematics, 2011.

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

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Masao, Fukushima, and Qi Liqun, eds. Reformulation: Nonsmooth, piecewise smooth, semismooth, and smoothing methods. Dordrecht: Kluwer, 1999.

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(Editor), Masao Fukushima, and Liqun Qi (Editor), eds. Reformulation: Nonsmooth, Piecewise Smooth, Semismooth and Smoothing Methods (Applied Optimization). Springer, 1998.

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Book chapters on the topic "Semismooth"

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Shui-Sheng, Zhou, Liu Hong-Wei, Cui Jiang-Tao, and Zhou Li-Hua. "Exact Semismooth Newton SVM." In Lecture Notes in Computer Science, 139–42. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11881070_23.

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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, 81–116. Boston, MA: Springer US, 1998. http://dx.doi.org/10.1007/978-1-4757-6388-1_5.

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Tseng, Paul. "Analysis of a Non-Interior Continuation Method Based on Chen-Mangasarian Smoothing Functions for Complementarity Problems." In Reformulation: Nonsmooth, Piecewise Smooth, Semismooth and Smoothing Methods, 381–404. Boston, MA: Springer US, 1998. http://dx.doi.org/10.1007/978-1-4757-6388-1_20.

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Andreani, Roberto, and José Mario Martínez. "Solving Complementarity Problems by Means of a New Smooth Constrained Nonlinear Solver." In Reformulation: Nonsmooth, Piecewise Smooth, Semismooth and Smoothing Methods, 1–24. Boston, MA: Springer US, 1998. http://dx.doi.org/10.1007/978-1-4757-6388-1_1.

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Jiang, Houyuan, and Daniel Ralph. "Global and Local Superlinear Convergence Analysis of Newton-Type Methods for Semismooth Equations with Smooth Least Squares." In Reformulation: Nonsmooth, Piecewise Smooth, Semismooth and Smoothing Methods, 181–209. Boston, MA: Springer US, 1998. http://dx.doi.org/10.1007/978-1-4757-6388-1_10.

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Kanzow, Christian, and Martin Zupke. "Inexact Trust-Region Methods for Nonlinear Complementarity Problems." In Reformulation: Nonsmooth, Piecewise Smooth, Semismooth and Smoothing Methods, 211–33. Boston, MA: Springer US, 1998. http://dx.doi.org/10.1007/978-1-4757-6388-1_11.

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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, 235–57. Boston, MA: Springer US, 1998. http://dx.doi.org/10.1007/978-1-4757-6388-1_12.

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Mangasarian, Olvi L. "Regularized Linear Programs with Equilibrium Constraints." In Reformulation: Nonsmooth, Piecewise Smooth, Semismooth and Smoothing Methods, 259–68. Boston, MA: Springer US, 1998. http://dx.doi.org/10.1007/978-1-4757-6388-1_13.

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Marcotte, Patrice. "Reformulations of a Bicriterion Equilibrium Model." In Reformulation: Nonsmooth, Piecewise Smooth, Semismooth and Smoothing Methods, 269–91. Boston, MA: Springer US, 1998. http://dx.doi.org/10.1007/978-1-4757-6388-1_14.

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Peng, Ji-Ming. "A Smoothing Function and Its Applications." In Reformulation: Nonsmooth, Piecewise Smooth, Semismooth and Smoothing Methods, 293–316. Boston, MA: Springer US, 1998. http://dx.doi.org/10.1007/978-1-4757-6388-1_15.

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Conference papers on the topic "Semismooth"

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Yunt, Mehmet, and Paul Barton. "Semismooth Hybrid Automata." In 2006 IEEE Conference on Computer-Aided Control Systems Design. IEEE, 2006. http://dx.doi.org/10.1109/cacsd.2006.285489.

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Yunt, Mehmet, and Paul I. Barton. "Semismooth hybrid automata." In 2006 IEEE Conference on Computer Aided Control System Design, 2006 IEEE International Conference on Control Applications, 2006 IEEE International Symposium on Intelligent Control. IEEE, 2006. http://dx.doi.org/10.1109/cacsd-cca-isic.2006.4776872.

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Bach, Eric, and Jonathan P. Sorenson. "Approximately counting semismooth integers." In the 38th international symposium. New York, New York, USA: ACM Press, 2013. http://dx.doi.org/10.1145/2465506.2465933.

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Lijie Bai and Arvind U. Raghunathan. "Semismooth equation approach to Network Utility Maximization (NUM)." In 2013 American Control Conference (ACC). IEEE, 2013. http://dx.doi.org/10.1109/acc.2013.6580580.

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Anyyeva, Serbiniyaz, and Karl Kunisch. "Semismooth Newton method for gradient constrained minimization problem." In FIRST INTERNATIONAL CONFERENCE ON ANALYSIS AND APPLIED MATHEMATICS: ICAAM 2012. AIP, 2012. http://dx.doi.org/10.1063/1.4747684.

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Xiaojiao Tong, Yongping Zhang, and F. F. Wu. "A decoupled semismooth Newton method for optimal power flow." In 2006 IEEE Power Engineering Society General Meeting. IEEE, 2006. http://dx.doi.org/10.1109/pes.2006.1709065.

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He, Suyan, and Yuxi Jiang. "Solving frictional contact problems by a semismooth Newton method." In 2011 International Conference on Consumer Electronics, Communications and Networks (CECNet). IEEE, 2011. http://dx.doi.org/10.1109/cecnet.2011.5769067.

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Shutin, Dmitriy, and Boris Vexler. "A semismooth Newton method for adaptive distributed sparse linear regression." In 2015 IEEE 6th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP). IEEE, 2015. http://dx.doi.org/10.1109/camsap.2015.7383829.

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Liao-McPherson, Dominic, Marco M. Nicotra, and Ilya V. Kolmanovsky. "A Semismooth Predictor Corrector Method for Suboptimal Model Predictive Control." In 2019 18th European Control Conference (ECC). IEEE, 2019. http://dx.doi.org/10.23919/ecc.2019.8796089.

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Cui, Mingzhu, and Liya Fan. "A Novel Semismooth Newton Algorithm for PCA-Twin Support Vector Machine." In AIEE 2022: 2022 The 3rd International Conference on Artificial Intelligence in Electronics Engineering. New York, NY, USA: ACM, 2022. http://dx.doi.org/10.1145/3512826.3512828.

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Reports on the topic "Semismooth"

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Munson, Todd S., Francisco Facchinei, Michael C. Ferris, Andreas Fischer, and Christian Kanzow. The Semismooth Algorithm for Large Scale Complementarity Problems. Fort Belvoir, VA: Defense Technical Information Center, June 1999. http://dx.doi.org/10.21236/ada375452.

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