A Novel Cultural Algorithm based on Particle Swarm Optimization and Whale Optimization Algorithm

Abstract

An ameliorative cultural algorithm (CA) based on particle swarm optimization (PSO) and whale optimization algorithm (WOA) is raised (CA-PSOWOA), so as to conquer the defects of WOA and PSO, such as poor global exploration ability and easy fall into local optimal solution. Firstly, a nonlinear inertia weight strategy is leaded to optimize the PSO and WOA, then CA is introduced to regulate the ability of global exploration and local exploitation of PSO and WOA. By testing on benchmark functions, it is proved that CA-PSOWOA improves the global exploration ability and solution accuracy, and its performance is better than the traditional PSO and WOA, and other algorithms.