Hybrid Optimization Parallel Search PACKage. HOPSPACK solves derivative-free optimization problems in a C++ software framework. The framework enables parallel operation using MPI (for distributed machine architectures) and multithreading (for single machines with multiple processors or cores). Optimization problems can be very general: functions can be noisy, nonsmooth and nonconvex, linear and nonlinear constraints are supported, and variables may be continuous or integer-valued. HOPSPACK is released with two user communities in mind: those who need an optimization problem solved, and those who wish to experiment with writing their own derivative-free solvers.
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References in zbMATH (referenced in 12 articles )
Showing results 1 to 12 of 12.
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- Porcelli, Margherita; Toint, Philippe L.: BFO, a trainable derivative-free brute force optimizer for nonlinear bound-constrained optimization and equilibrium computations with continuous and discrete variables (2017)
- Rahmanpour, Fardin; Hosseini, Mohammad Mehdi; Maalek Ghaini, Farid Mohammad: Penalty-free method for nonsmooth constrained optimization via radial basis functions (2017)
- Audet, Charles; Le Digabel, Sébastien; Peyrega, Mathilde: Linear equalities in blackbox optimization (2015)
- Mondal, Sukanto; Lucet, Yves; Hare, Warren: Optimizing horizontal alignment of roads in a specified corridor (2015)
- Hingerl, Ferdinand F.; Kosakowski, Georg; Wagner, Thomas; Kulik, Dmitrii A.; Driesner, Thomas: GEMSFIT: a generic fitting tool for geochemical activity models (2014)
- Martínez, J. M.; Sobral, F. N. C.: Constrained derivative-free optimization on thin domains (2013)
- Rios, Luis Miguel; Sahinidis, Nikolaos V.: Derivative-free optimization: a review of algorithms and comparison of software implementations (2013)
- Reif, Matthias; Shafait, Faisal; Dengel, Andreas: Meta-learning for evolutionary parameter optimization of classifiers (2012) ioport
- Rocklin, Matthew; Pinar, Ali: Computing an aggregate edge-weight function for clustering graphs with multiple edge types (2010)