Chameleon Algorithm Implementation in MATLAB

This article explores the Chameleon Algorithm and its implementation in MATLAB. The Chameleon Algorithm is a population-based metaheuristic optimization method that mimics the adaptive color-changing strategies of chameleons. This algorithm demonstrates excellent performance in solving optimization problems, particularly in applications such as community detection and image segmentation. In MATLAB implementation, developers can utilize built-in toolbox functions or manually code the algorithm structure. The core implementation typically involves creating a population initialization function, defining color adaptation mechanisms through dynamic parameter adjustment, and implementing the hunting behavior simulation using position update equations. To enhance algorithm effectiveness, parameter optimization techniques such as adaptive step size control and neighborhood search strategies can be incorporated. Algorithm improvements may include hybrid approaches combining Chameleon with local search methods or parallel computing implementation using MATLAB's Parallel Computing Toolbox. This article discusses practical implementation techniques in MATLAB and provides suggestions for algorithm enhancement, including code structure optimization and performance evaluation metrics.