Solving Two-Dimensional Function Maximization Problems Using Genetic Algorithms
Implementing a genetic algorithm in MATLAB to solve two-dimensional function maximization problems without using MATLAB's built-in Genetic Algorithm Toolbox
Integration and Comparative Experiments of Genetic Algorithms, Simulated Annealing, and Particle Swarm Optimization – Ready-to-Use with Minor Modifications
A practical study on combining and comparing Genetic Algorithms, Simulated Annealing, and Particle Swarm Optimization. Includes implementation insights and reusable code structure for easy adaptation.
Understanding Genetic Algorithm Concepts and Applications
Comprehension of genetic algorithm principles and their application in function minimization using optimization techniques such as crossover and mutation operations with code implementation insights
Hybrid Ant Colony Algorithm Integrating Greedy Strategy and Genetic Algorithm Mutation Strategy
Enhanced Hybrid Ant Colony Optimization Algorithm Incorporating Greedy Selection and Genetic Mutation Strategies for Improved Solution Quality
Function Extremum Optimization
Genetic Algorithm for Function Extremum Optimization and Neural Network Decoupling Control Algorithm
Static Friction Parameter Identification Using Genetic Algorithm
MATLAB 6.5 Implementation of Static Friction Parameter Identification Based on Genetic Algorithm
Simple Genetic Algorithm Implementation in Genetic Algorithms
Implementation of a Simple Genetic Algorithm in Genetic Algorithms using MATLAB with code-related explanations.
MATLAB Implementation Combining Genetic Algorithm and Fuzzy C-means Clustering
MATLAB program integrating Genetic Algorithm and Fuzzy C-means Clustering for complex optimization problems
Rewritten Multivariable Constrained Genetic Algorithm MATLAB Source Code
An optimized MATLAB implementation for constrained multi-variable genetic algorithms with enhanced code structure and functionality
Personally Collected Various Intelligent Algorithms with Source Code
My personal collection of intelligent algorithms includes over 20 source code implementations covering: Genetic Algorithm (GA), Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO), Differential Evolution (DE), hybrid algorithms like Genetic-Neural Network, PSO-SVM, and PSO-Neural Network, each featuring distinct optimization strategies and parameter tuning approaches.