Advanced Bamboo Forest Growth Optimization Algorithm for Optimization of Water Pump Scheduling for Water Distribution Network

Abstract

Metaheuristic optimization algorithms are problem-solving techniques inspired by natural or abstract phenomena and find wide applications across various fields. The bamboo forest growth optimization algorithm (BFGO) is a meta-heuristic optimization algorithm inspired by the growth characteristics of bamboo forests. It has a strong convergence ability and therefore can effectively solve high-dimensional complex optimization problems. However, for multi-modal problems and composite problems, BFGO still has the disadvantage of easily falling into local optimality. In response to the above shortcomings, this article proposes a bamboo forest growth optimization algorithm based on the clustering strategy (CSBFGO). Clustering grouping and the Cauchy mutation strategy are introduced in the algorithm to improve the convergence and diversity of the algorithm. The CEC2017 benchmark test set was used to test and analyze its optimization accuracy and convergence ability to verify the effectiveness of the CSBFGO algorithm. In addition, to verify the performance of the CSBFGO algorithm in solving practical problems, integrating the CSBFGO algorithm is applied to optimize pump scheduling in water distribution networks. The experimental results show that the CSBFGO algorithm has good performance in solving practical problems.