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CENSO is a framework for global optimization of nonconvex, spline-constrained MINLP problems

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CENSO

CENSO is a framework for global optimization of nonconvex, possibly spline-constrained, MINLP problems.

Dependencies:

  • Eigen for linear algebra.
  • SPLINTER to compute with splines and other approximations.
  • GUROBI for solving LP and MIP problems.
  • IPOPT for solving NLP problems.
  • BONMIN for solving convex MINLP problems and for heuristically solving non-convex MINLP problems.

Notes:

  • The code examples in the user guide (Docs/UserGuide/manual.pdf) are currently outdated. Refer to the test problems (TestProblems/*) for examples on how to create and solve optimization problems.

Reference:

If you use CENSO in a scientific work we kindly ask you to cite it. You can cite it as shown in the bibtex entry below (remember to update the date accessed).

@article{Grimstad2015,
year={2015},
issn={0925-5001},
journal={Journal of Global Optimization},
doi={10.1007/s10898-015-0358-4},
title={Global optimization with spline constraints: a new branch-and-bound method based on B-splines},
url={http://dx.doi.org/10.1007/s10898-015-0358-4},
publisher={Springer US},
keywords={Branch-and-bound; B-splines; Knot insertion; Piecewise polynomials; Nonconvex; Mixed-integer; Nonlinear},
author={Grimstad, Bjarne and Sandnes, Anders},
pages={1-39},
language={English}
}

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