Whale Optimization Algorithm (WOA) Complete MATLAB Implementation

This is a complete MATLAB implementation of the Whale Optimization Algorithm with detailed comments that can be executed directly. The algorithm simulates the bubble-net hunting strategy and social behavior of humpback whales to solve optimization problems. Key implementation aspects include: The code features three main mathematical operators: 1. Encircling prey mechanism using shrinkage factor calculations 2. Bubble-net attacking method through spiral updating position 3. Global search behavior using random whale selection The implementation incorporates mathematical concepts from set theory, probability theory, and numerical computation. The algorithm structure includes: - Population initialization with random position vectors - Fitness evaluation function for objective optimization - Adaptive parameter tuning (a, A, C coefficients) - Convergence criteria checking with iteration control Notably, this algorithm demonstrates excellent application potential not only for standard optimization problems but also for machine learning parameter tuning, artificial intelligence applications, and complex system modeling. The MATLAB code is organized with clear section comments, variable descriptions, and step-by-step execution flow. We recommend exploring the mathematical foundations and parameter customization options to better adapt the algorithm for specific problem domains.