Explore MATLAB source code curated for "无约束优化" with clean implementations, documentation, and examples.
An efficient Python implementation of the conjugate gradient algorithm for unconstrained optimization problems, ready to use after extraction with comprehensive code documentation
Custom implementation of L-BFGS algorithm for solving unconstrained optimization problems
Conjugate Gradient Method for unconstrained optimization - this implementation requires knowledge of both the objective function and its gradient to solve optimization problems efficiently. The algorithm is particularly suitable for large-scale problems due to its iterative nature and memory efficiency.
This repository provides fundamental MATLAB implementation examples for solving optimization problems including unconstrained optimization, linear programming, and nonlinear programming using MATLAB's Optimization Toolbox functions.
MATLAB code implementation for finding minimum values of functions with optimization techniques
Implementation of Powell's Optimization Algorithm in MATLAB with Code Explanations
An efficient optimization method combining cone models, quasi-Newton techniques, and trust region strategies for solving unconstrained optimization problems.
Implementation of Ant Colony Algorithm for Continuous Optimization Problems with Code Integration