Ant Colony Optimization Simulation Platform Developed with MATLAB

This document presents a simulation platform for Ant Colony Optimization (ACO) algorithm developed using MATLAB. The platform is designed to support comprehensive algorithm implementation featuring path optimization visualization and interactive human-machine control capabilities. Through MATLAB's graphical user interface (GUI) components, users can dynamically adjust parameters like pheromone evaporation rates and ant population size to observe real-time optimization processes. The simulation environment allows users to deeply understand ACO's working mechanism, including pheromone updating rules and probability-based path selection algorithms. Additionally, the platform integrates experimental tools for benchmarking algorithm performance through metrics like convergence speed and solution quality analysis. Key MATLAB functions implemented include route optimization using matrix operations, visualization through plotting functions, and interactive controls via GUI callbacks. Overall, this ACO simulation platform serves as an effective educational and research tool for mastering this sophisticated optimization algorithm, with modular code structure enabling easy customization for specific optimization scenarios.