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CENSO is a framework for global optimization of nonconvex, spline-constrained MINLP problems
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CENSO is a framework for global optimization of nonconvex, possibly spline-constrained, MINLP problems.
- 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.
- The code examples in the user guide (Docs/UserGuide/manual.pdf) are currently outdated.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.
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}}