Solver-o-matic

Solver-o-matic: Decision Tree for Nonsmooth Optimization Software. Solver-o-matic 1.0 is an online decision tree for choosing a nonsmooth optimization solver. The tree is loosely based on the paper ”Empirical and Numerical Comparison of Several Nonsmooth Minimization Methods and Software” by N. Karmitsa, A. Bagirov and M.M. Mäkelä. Solver-o-matic will tell you which method/solver is the most suitable for solving your problem. With this first version you can only search for unconstrained optimization solvers (although some of the solvers can handle constrained problems as well).

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References in zbMATH (referenced in 1 article )

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  1. Milz, Johannes; Ulbrich, Michael: An approximation scheme for distributionally robust nonlinear optimization (2020)