Pennon: A code for convex nonlinear and semidefinite programming We introduce a computer program PENNON for the solution of problems of convex nonlinear and semidefinite programming (NLP-SDP). The algorithm used in PENNON is a generalized version of the augmented Lagrangian method, originally introduced by Ben-Tal and Zibulevsky for convex NLP problems. We present generalization of this algorithm to convex NLP-SDP problems, as implemented in PENNON and details of its implementation. The code can also solve second-order conic programming (SOCP) problems, as well as problems with a mixture of SDP, SOCP and NLP constraints. Results of extensive numerical tests and comparison with other optimization codes are presented. The test examples show that PENNON is particularly suitable for large sparse problems.

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  1. Saldivar, Belem; Mondié, Sabine; Ávila Vilchis, Juan Carlos: The control of drilling vibrations: a coupled PDE-ODE modeling approach (2016)
  2. Zhao, Qi; Chen, Zhongwen: On the superlinear local convergence of a penalty-free method for nonlinear semidefinite programming (2016)
  3. Curtis, Frank E.; Jiang, Hao; Robinson, Daniel P.: An adaptive augmented Lagrangian method for large-scale constrained optimization (2015)
  4. Gould, Nicholas I.M.; Loh, Yueling; Robinson, Daniel P.: A nonmonotone filter SQP method: local convergence and numerical results (2015)
  5. Gould, Nicholas I.M.; Orban, Dominique; Toint, Philippe L.: CUTEst: a constrained and unconstrained testing environment with safe threads for mathematical optimization (2015)
  6. Kato, Atsushi; Yabe, Hiroshi; Yamashita, Hiroshi: An interior point method with a primal-dual quadratic barrier penalty function for nonlinear semidefinite programming (2015)
  7. Mohy-ud-Din, Hassan; Robinson, Daniel P.: A solver for nonconvex bound-constrained quadratic optimization (2015)
  8. Robinson, Daniel P.: Primal-dual active-set methods for large-scale optimization (2015)
  9. Weldeyesus, Alemseged Gebrehiwot; Stolpe, Mathias: A primal-dual interior point method for large-scale free material optimization (2015)
  10. Yang, Li; Yu, Bo; Li, YanXi: A homotopy method based on penalty function for nonlinear semidefinite programming (2015)
  11. Chamanbaz, Mohammadreza; Dabbene, Fabrizio; Tempo, Roberto; Venkataramanan, Venkatakrishnan; Wang, Qing-Guo: A statistical learning theory approach for uncertain linear and bilinear matrix inequalities (2014)
  12. Habermehl, Kai: Robust optimization of active trusses via mixed-integer semidefinite programming (2014)
  13. Kirches, Christian; Leyffer, Sven: TACO: a toolkit for AMPL control optimization (2013)
  14. Wu, Min; Yang, Zhengfeng; Lin, Wang: Exact asymptotic stability analysis and region-of-attraction estimation for nonlinear systems (2013)
  15. Yang, Li; Yu, Bo: A homotopy method for nonlinear semidefinite programming (2013)
  16. Forni, Fulvio; Galeani, Sergio; Zaccarian, Luca: Model recovery anti-windup for continuous-time rate and magnitude saturated linear plants (2012)
  17. Henrion, Didier; Malick, Jér^ome: Projection methods in conic optimization (2012)
  18. Kočvara, Michal; Stingl, Michael: PENNON: software for linear and nonlinear matrix inequalities (2012)
  19. Mittelmann, Hans D.: The state-of-the-art in conic optimization software (2012)
  20. Schellewald, Christian: A convex relaxation bound for subgraph isomorphism (2012)

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