SoPlex

SoPlex is a Linear Programming (LP) solver based on the revised simplex algorithm. It features preprocessing techniques, exploits sparsity, and offers primal and dual solving routines. It can be used as a standalone solver reading MPS or LP format files as well as embedded into other programs via a C++ class library. SoPlex has been implemented as a part of Roland Wunderling’s Ph.D. thesis Paralleler und Objektorientierter Simplex-Algorithmus (in German) and is available in source code. SoPlex is free for academic research and can be licensed for commercial use.

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References in zbMATH (referenced in 87 articles , 1 standard article )

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  1. Marendet, Antoine; Goldsztejn, Alexandre; Chabert, Gilles; Jermann, Christophe: A standard branch-and-bound approach for nonlinear semi-infinite problems (2020)
  2. Gamrath, Gerald; Berthold, Timo; Heinz, Stefan; Winkler, Michael: Structure-driven fix-and-propagate heuristics for mixed integer programming (2019)
  3. Lourenco, Christopher; Escobedo, Adolfo R.; Moreno-Centeno, Erick; Davis, Timothy A.: Exact solution of sparse linear systems via left-looking roundoff-error-free Lu factorization in time proportional to arithmetic work (2019)
  4. Weber, Tobias; Sager, Sebastian; Gleixner, Ambros: Solving quadratic programs to high precision using scaled iterative refinement (2019)
  5. Araya, Ignacio; Neveu, Bertrand: \textttlsmear: a variable selection strategy for interval branch and bound solvers (2018)
  6. Berthold, Timo: A computational study of primal heuristics inside an MI(NL)P solver (2018)
  7. Berthold, Timo; Hendel, Gregor; Koch, Thorsten: From feasibility to improvement to proof: three phases of solving mixed-integer programs (2018)
  8. Bus, Norbert; Mustafa, Nabil H.; Ray, Saurabh: Practical and efficient algorithms for the geometric hitting set problem (2018)
  9. Chen, Wei-Kun; Chen, Liang; Yang, Mu-Ming; Dai, Yu-Hong: Generalized coefficient strengthening cuts for mixed integer programming (2018)
  10. Huangfu, Q.; Hall, J. A. J.: Parallelizing the dual revised simplex method (2018)
  11. Kim, Kibaek; Zavala, Victor M.: Algorithmic innovations and software for the dual decomposition method applied to stochastic mixed-integer programs (2018)
  12. Malone, Brandon; Kangas, Kustaa; Järvisalo, Matti; Koivisto, Mikko; Myllymäki, Petri: Empirical hardness of finding optimal Bayesian network structures: algorithm selection and runtime prediction (2018)
  13. Thammawichai, Mason; Kerrigan, Eric C.: Energy-efficient real-time scheduling for two-type heterogeneous multiprocessors (2018)
  14. Anders Jensen, Jeff Sommars, Jan Verschelde: Computing Tropical Prevarieties in Parallel (2017) arXiv
  15. Belotti, Pietro; Berthold, Timo: Three ideas for a feasibility pump for nonconvex MINLP (2017)
  16. Escobedo, Adolfo R.; Moreno-Centeno, Erick: Roundoff-error-free basis updates of LU factorizations for the efficient validation of optimality certificates (2017)
  17. Gamrath, Gerald; Koch, Thorsten; Maher, Stephen J.; Rehfeldt, Daniel; Shinano, Yuji: SCIP-Jack -- a solver for STP and variants with parallelization extensions (2017)
  18. Gleixner, Ambros M.; Berthold, Timo; Müller, Benjamin; Weltge, Stefan: Three enhancements for optimization-based bound tightening (2017)
  19. Göttlich, Simone; Potschka, Andreas; Ziegler, Ute: Partial outer convexification for traffic light optimization in road networks (2017)
  20. Soares, Murilo Pereira; Street, Alexandre; Valladão, Davi Michel: On the solution variability reduction of stochastic dual dynamic programming applied to energy planning (2017)

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