Explore MATLAB source code curated for "乘子法" with clean implementations, documentation, and examples.
A teacher-developed program implementing the Lagrange multiplier method for constrained equation optimization, featuring comprehensive annotations that elucidate the mathematical algorithms and code structure.
MATLAB implementations of contemporary nonlinear programming algorithms including SQP (Sequential Quadratic Programming) with active-set strategy, Augmented Lagrangian method for constraint handling, Quadratic Programming solvers, Nonlinear Least Squares using Gauss-Newton iterations, Conjugate Gradient methods for large-scale problems, Quasi-Newton techniques (BFGS/DFP), Line Search implementations with Wolfe conditions, Trust Region methods with dogleg steps, Steepest Descent with adaptive step sizes, and Newton's method with Hessian modifications.
MATLAB implementations for constrained optimization algorithms including: minRosen.m - Rosen's gradient projection method, minFactor.m - multiplier method (method of multipliers), minconPS.m - coordinate rotation method, minPF.m - exterior penalty function method, minMixFun.m - mixed penalty function method, minJSMixFun.m - accelerated mixed penalty function method