×

BFO

swMATH ID: 36962
Software Authors: Porcelli, Margherita; Toint, Philippe L.
Description: BFO, a trainable derivative-free brute force optimizer for nonlinear bound-constrained optimization and equilibrium computations with continuous and discrete variables. A direct-search derivative-free Matlab optimizer for bound-constrained problems is described, whose remarkable features are its ability to handle a mix of continuous and discrete varibles, a versatile interface as well as a novel self-training option. Its performance compares favorable with that of NOMAD (Nonsmooth Optimization by Mesh Adaptive Direct Search), a well-known derivative-free optimization package. It is also applicable to multilevel equilibrium- or constrained-type problems. Its easy-to-use interface provides a number of user-oriented features, such as checkpointing and restart, variable scaling, and early termination tools.
Homepage: https://dl.acm.org/doi/10.1145/3085592
Keywords: derivative-free optimization; direct-search methods; mixed-integer optimization; bound constraints; trainable algorithms
Related Software: NOMAD; MISO; DFL; SO-I; DFLBOX; BOBYQA; OrthoMADS; DFLGEN; MCS; MultiMin; DFBOX_IMPR; SDBOX; KELLEY; DFN; RBFOpt; UOBYQA; SNOBFIT; NEWUOA; OPAL; CUTEst
Cited in: 13 Publications

Citations by Year