Goat Optimization Algorithm (GOA)

GOA is a nature-inspired metaheuristic optimization technique that simulates the adaptive foraging behavior of goats.

The Goat Optimization Algorithm (GOA) is a nature-inspired metaheuristic optimization technique that simulates the adaptive foraging behavior of goats. Designed to balance exploration and exploitation, GOA incorporates movement strategies that allow solutions to dynamically adjust within the search space while avoiding local optima. The MATLAB implementation of GOA provides a powerful framework for solving multi-objective optimization problems with constraints, making it suitable for real-world applications in engineering, supply chain management, and artificial intelligence. This implementation allows users to define custom constraints, set optimization parameters, and visualize Pareto-optimal solutions. With built-in adaptability, GOA can efficiently handle complex decision-making problems, offering a reliable alternative to traditional optimization algorithms. The MATLAB code includes key functionalities such as adaptive search mechanisms, constraint handling, and graphical visualization of results, ensuring an intuitive and flexible approach to solving multi-objective problems.