Enhanced Niche Genetic Algorithm with MATLAB Implementation

The implementation of an improved niche genetic algorithm with MATLAB source code provides superior computational efficiency and more accurate results. This algorithm integrates genetic algorithms with niche theory, enabling effective identification of optimal solutions within complex search spaces. The niche preservation mechanism is implemented through specialized fitness sharing functions that maintain population diversity by penalizing similar solutions. Key MATLAB functions include niche-based selection operators, specialized crossover routines that preserve building blocks, and dynamic mutation rates adapted to population density. By employing this enhanced niche genetic algorithm, we can more thoroughly explore the solution space and discover multiple promising solutions simultaneously. The MATLAB implementation allows for clear visualization of convergence patterns and niche formation through plotting capabilities. Furthermore, the source code implementation facilitates deeper understanding of algorithm mechanics and enables performance optimization through parameter tuning and operator customization. Thus, this improved niche genetic algorithm with MATLAB source code serves as a powerful tool for solving various complex computational problems requiring multimodal optimization.