Explore MATLAB source code curated for "单目标优化问题" with clean implementations, documentation, and examples.
Moth-Flame Optimization (MFO) is a novel meta-heuristic algorithm inspired by the biological behavior of moths navigating at night using transverse orientation. Proposed in 2015, it solves optimization problems by tracking optimal positions and implementing spiral search mechanisms. Suitable for single-objective optimization problems. Copyright belongs to the original authors, with honors to their innovation.
MATLAB implementation of genetic algorithm for solving single-objective optimization problems to find maximum values of binary functions, featuring population initialization, fitness evaluation, selection, crossover, and mutation operations.
Whale Optimization Algorithm (WOA) is a novel metaheuristic optimization technique designed for solving optimization problems. The algorithm employs three core operators to simulate humpback whales' predatory behaviors: encircling prey, bubble-net feeding, and hunting mechanisms. It is specifically tailored for single-objective optimization tasks. The copyright belongs to the original developers, to whom we extend our respect. Key implementations include mathematical modeling of whale movement patterns and position updates using logarithmic spiral equations.