ALGLIB 3.6.0 was released today, with new algorithms and fixes: Quadratic optimizer now supports arbitrary combination of boundary and linear equality/inequality constraints. New version of the optimizer uses combination of the augmented Lagrangian and active set methods. Spline1D unit now supports monotone cubic spline interpolation Support for vector-valued bilinear and bicubic splines Support for scalar and vector-valued trilinear (3D) splines Better support for sparse matrices: efficient enumeration of non-zero elements with SparseEnumerate(), faster SparseGet() for matrices stored in CRS format. Optmization and nonlinear fitting algorithms (LSFit, MinLM, MinBLEIC, MinLBFGS, MinCG subpackages) can verify correctness of the user-supplied gradient (the most common source of errors in numerical programs). Several minor fixes (see Change Log).
Commercial version of ALGLIB 3.6.0 will be delivered to customers with active support/maintenance agreement within few days. Good luck with ALGLIB!
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