PyGlobalSearch provides Python bindings for the globalsearch-rs Rust library, implementing the OQNLP algorithm for global optimization.
The OQNLP algorithm combines scatter search metaheuristics with local optimization to effectively find global minima in nonlinear optimization problems.
Practical examples for different types of optimization problems.
Complete Python API documentation with all classes, functions, and parameters.
Key Features#
Multiple Solvers: COBYLA, L-BFGS, Newton-CG, Trust Region, Nelder-Mead, Steepest Descent
Constraint Support: Inequality constraints via COBYLA solver
Gradient Support: Optional gradient and Hessian functions for faster convergence
Flexible Configuration: Builder pattern for detailed solver customization
Performance: Built in Rust for speed with Python convenience
Note: For practical examples and usage patterns, please refer to the Book Website. The API reference here provides detailed documentation of all classes and functions available in PyGlobalSearch.