Improving BFGO with Apical Dominance-Guided Gradient Descent for Enhanced Optimization

The Bamboo Forest Growth Optimization (BFGO) algorithm is a popular meta-heuristic for diverse optimization problems. However, its performance can be unstable due to problem-specific parameters, leading to suboptimal outcomes. To enhance efficiency and overcome these limitations, we present a novel extension—BFGO with Apical Dominance-Guided Gradient Descent (BFGO-ADGD). BFGO-ADGD leverages the modified exploitation capabilities of BFGO to function as the exploration mechanism within the frame-work, incorporating Apical Dominance guidance and employing Gradient Descent for effective exploitation. Experimental evaluations on the CEC2017 test set and engineering problems showcase BFGO-ADGD’s superior performance over existing heuristics. This approach not only advances BFGO but also showcases the integration of biological growth principles with optimization methodologies. BFGO-ADGD holds promise for tackling challenging optimization tasks and inspiring future research in this domain.