A Novel Intelligent Algorithm - Glowworm Swarm Optimization (GSO) Algorithm
- Login to Download
- 1 Credits
Resource Overview
A novel intelligent algorithm called Glowworm Swarm Optimization (GSO), specifically designed for multimodal function optimization. The implementation includes two MATLAB files: GSO.m serves as the main algorithm driver containing the optimization loop and glowworm movement logic, while J1.m defines the benchmark test function. Users can execute the algorithm directly by running GSO.m in MATLAB, and customize optimization problems by modifying the objective function in J1.m.
Detailed Documentation
Glowworm Swarm Optimization (GSO) represents a novel intelligent algorithm primarily designed for solving multimodal function optimization problems. The algorithm implementation consists of two core MATLAB files. To execute the algorithm, simply run the main script GSO.m in MATLAB environment, which handles the swarm initialization, attraction movement between glowworms based on luminance intensity, and iterative optimization process. For modifying test functions, users can edit the J1.m function file that contains the objective function definition and landscape parameters. The GSO algorithm demonstrates high efficiency and strong optimization capabilities through its bioluminescent-inspired attraction mechanism, making it suitable for various complex optimization scenarios including multi-peak function searching, dynamic optimization, and engineering design problems. This biologically-inspired approach shows significant promise for handling optimization challenges where traditional methods struggle with local optima convergence.
- Login to Download
- 1 Credits