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nonlinear-optimization

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Mathematical Optimization in Julia. Local, global, gradient-based and derivative-free. Linear, Quadratic, Convex, Mixed-Integer, and Nonlinear Optimization in one simple, fast, and differentiable interface.

  • Updated Feb 6, 2025
  • Julia

PRIMA is a package for solving general nonlinear optimization problems without using derivatives. It provides the reference implementation for Powell's derivative-free optimization methods, i.e., COBYLA, UOBYQA, NEWUOA, BOBYQA, and LINCOA. PRIMA means Reference Implementation for Powell's methods with Modernization and Amelioration, P for Powell.

  • Updated Nov 27, 2024
  • Fortran

A next-gen Lagrange-Newton solver for nonconvex constrained optimization. Unifies barrier and SQP methods in a generic way, and implements various globalization flavors (line search/trust region and merit function/filter method/funnel method). Competitive against filterSQP, IPOPT, SNOPT, MINOS and CONOPT.

  • Updated Feb 2, 2025
  • C++

PyPop7: A Pure-Python Library for POPulation-based Black-Box Optimization (BBO), especially *Large-Scale* variants (including evolutionary algorithms, swarm-based random optimizers, pattern search, and even random search). [https://jmlr.org/papers/v25/23-0386.html (CCF-A)] (Its Planned Extensions: *PyCoPop7*, *PyNoPop7*, *PyPop77*, and *PyMePop7*)

  • Updated Feb 11, 2025
  • Python

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