Unconstrained Optimization Problem Source Code Collection

The compressed package contains source code implementations for several common unconstrained optimization methods: Variable Rotation Method (variable_rotation.m), Steepest Descent Method (steepest_descent.m), Modified Newton's Method (modified_newton.m), and Conjugate Gradient Method (conjugate_gradient.m). Additional utility functions include coefficient_matrix.m for obtaining objective function coefficient matrices, minval.m for minimum value computation, and gradient.m for gradient calculation functions, all implemented with MATLAB optimization algorithms.

Direct Utilization of MATLAB Genetic Algorithm Toolbox

The weight optimization of BP neural networks represents an unconstrained optimization problem with real-number encoding, making it suitable for direct implementation using MATLAB's genetic algorithm toolbox. The provided code demonstrates nonlinear regression for a system with 19 input variables and 1 output variable. For adaptation to different scenarios, users need only modify the encoding/decoding functions. The implementation requires the GAOT (Genetic Algorithm Optimization Toolbox) with enhancements including optimization algorithm selection, automated parameter tuning, and parallel computation capabilities.

MATLAB Implementation of Differential Evolution Algorithm

Differential Evolution Algorithm is an emerging intelligent computational method capable of solving various unconstrained optimization problems. It operates through mutation, crossover, and selection operations to evolve population solutions.

Basic Particle Swarm Optimization Algorithms and Enhanced PSO Variants

Implementation of fundamental and improved Particle Swarm Optimization algorithms, including: Basic PSO for unconstrained optimization, Constriction Factor PSO, Linearly Decreasing Weight PSO, Adaptive Weight PSO, Random Weight PSO, Synchronous Learning Factor PSO, Asynchronous Learning Factor PSO, Second Order PSO, Second Order Oscillatory PSO, Chaotic PSO, Selection-based PSO