Sparse Optimal Control Software (SOCS). The Sparse Optimal Control Family, developed by The Boeing Company, contains two advanced software packages, available separately or together. Sparse Optimal Control Software (SOCS) is general-purpose software for solving optimal control problems. Applications include trajectory optimization, chemical process control and machine tool path definition. Sparse Nonlinear Programming exploits state-of-the-art sparse linear algebra technology to solve very large optimization problems orders of magnitude faster than traditional methods. Applications with more than 100,000 variables and constraints can now be solved efficiently on desktop computers. The Sparse Nonlinear Programming software is available as an integral part of SOCS or as a separate package.

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  1. Berahas, Albert S.; Curtis, Frank E.; Robinson, Daniel; Zhou, Baoyu: Sequential quadratic optimization for nonlinear equality constrained stochastic optimization (2021)
  2. Goverde, Rob M. P.; Scheepmaker, Gerben M.; Wang, Pengling: Pseudospectral optimal train control (2021)
  3. Lohéac, Jérôme; Trélat, Emmanuel; Zuazua, Enrique: Nonnegative control of finite-dimensional linear systems (2021)
  4. Robuschi, Nicolò; Zeile, Clemens; Sager, Sebastian; Braghin, Francesco: Multiphase mixed-integer nonlinear optimal control of hybrid electric vehicles (2021)
  5. Bastos, Guaraci jun.; Brüls, Olivier: Analysis of open-loop control design and parallel computation for underactuated manipulators (2020)
  6. Bolhasani, Ehsan; Azizi, Yousef; Abdollahpour, Daryoush; Amjad, Jafar M.; Perc, Matjaž: Control of dynamics via identical time-lagged stochastic inputs (2020)
  7. Chertovskih, R.; Karamzin, D.; Khalil, N. T.; Lobo Pereira, F.: Regular path-constrained time-optimal control problems in three-dimensional flow fields (2020)
  8. Delanoue, Nicolas; Lhommeau, Mehdi; Lagrange, Sébastien: Nonlinear optimal control: a numerical scheme based on occupation measures and interval analysis (2020)
  9. Dutra, Dimas Abreu Archanjo: Uncertainty estimation in equality-constrained MAP and maximum likelihood estimation with applications to system identification and state estimation (2020)
  10. Hoffmann, Ramona; Taetz, Bertram; Miezal, Markus; Bleser, Gabriele; Leyendecker, Sigrid: On optical data-guided optimal control simulations of human motion (2020)
  11. Kuřátko, Jan; Ratschan, Stefan: Solving reachability problems by a scalable constrained optimization method (2020)
  12. Yazdaniyan, Z.; Shamsi, M.; Foroozandeh, Z.; de Pinho, Maria do Rosário: A numerical method based on the complementarity and optimal control formulations for solving a family of zero-sum pursuit-evasion differential games (2020)
  13. Zhao, Jisong; Li, Shuang: Adaptive mesh refinement method for solving optimal control problems using interpolation error analysis and improved data compression (2020)
  14. Zhu, Qiang; Wang, Kexin; Shao, Zhijiang; Biegler, Lorenz T.: Simultaneous orthogonal collocation decomposition method for extended \textitLionand Man problems (2020)
  15. Foroozandeh, Z.; Shamsi, M.; de Pinho, M. d. R.: A mixed-binary non-linear programming approach for the numerical solution of a family of singular optimal control problems (2019)
  16. Ha, Jung-Su; Choi, Han-Lim: On periodic optimal solutions of persistent sensor planning for continuous-time linear systems (2019)
  17. Lismonde, Arthur; Sonneville, Valentin; Brüls, Olivier: A geometric optimization method for the trajectory planning of flexible manipulators (2019)
  18. Liu, Ping; Liu, Xinggao; Wang, Ping; Li, Guodong; Xiao, Long; Yan, Jie; Ren, Zhang: Control variable parameterisation with penalty approach for hypersonic vehicle reentry optimisation (2019)
  19. Miyaoka, Tiago Yuzo; Lenhart, Suzanne; Meyer, João F. C. A.: Optimal control of vaccination in a vector-Borne reaction -- diffusion model applied to Zika virus (2019)
  20. Ramezani, Mohammad Hossein; Sadati, Nasser: Hierarchical optimal control of a binary distillation column (2019)

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