MATLAB Implementation of Cuckoo Search Optimization Algorithm for Spring Design Applications

In modern engineering systems, springs serve as crucial mechanical components where design considerations must account for multiple factors including functional requirements, load capacities, and spatial constraints. The Cuckoo Search algorithm represents a nature-inspired metaheuristic optimization technique that mimics the brood parasitism behavior of cuckoo birds. Our MATLAB implementation leverages this algorithm's powerful global search capabilities through Levy flight distributions and host nest replacement strategies to efficiently explore spring design parameter spaces. The computational framework integrates objective functions for spring performance metrics (such as stress, deflection, and natural frequency) with constraint handling mechanisms for dimensional limitations. By implementing adaptive step sizes and elitism preservation through MATLAB's matrix operations and function handlers, the application significantly streamlines the spring design optimization process while enhancing solution quality and convergence speed. This developed MATLAB application provides engineers with an intelligent tool for automated spring design optimization, combining algorithmic efficiency with practical engineering requirements.