An Extension of Bamboo Forest Growth Optimization Algorithm

Jeng-Shyang Pan, Li lin, Vaclav Snasel, Shu-Chuan Chu

Keywords: Bamboo forest growth optimization algorithm, Swarm intelligence algorithm, Logistic growth model, Natural selection strategy

Abstract: The Bamboo Forest Growth Optimization Algorithm (BFGO) is an innovative and flexible meta-heuristic optimization algorithm inspired by the growth pattern of bamboo forests, which first establish roots and extend before growing freely. This algorithm has achieved good results in solving optimization and engineering problems. However, it suffers from insufficient global exploration capabilities and is prone to getting stuck in local optima. Drawing on additional growth characteristics of bamboo forests, this paper extends BFGO's search strategy, reconstructs the bamboo growth model, and designs an elimination strategy to select elite individuals. Comparative testing against several classical meta-heuristic algorithms and their improved variants on the CEC2017 and CEC2013 test set. The results demonstrate that the extended BFGO algorithm achieve the best performance, fully demonstrates the effectiveness and competitiveness of the improved strategy.

Submission Number: 104