正余混沌双弦鲸鱼优化算法

针对基本鲸鱼优化（WOA）算法容易陷入局部最优解和收敛速度慢的缺点，提出一种正余混沌双弦鲸鱼优化（CSCWOA）算法。为鲸鱼的觅食加入信息交流强化机制，并在捕食引入正余混沌双弦机制，通过正弦全局搜索减少寻优盲点，余弦局部开发加快收敛速度，以及混沌算子增强跳出局部最优的能力，个体信息在种群中双弦混沌交叉快速传播。通过仿真对比实验，证明了该算法具有较好的收敛速度、求解精度和稳定性。

Whale optimization algorithm based on chaotic sine cosine operator

For the Whale Optimization Algorithm’s falling into the partial optimization easily and slow convergence speed, a method of Whale Optimization Algorithm based on Chaotic Sine Cosine（CSCWOA） operator is proposed. By adding the intensive information mechanism to the whale searching and the chaotic sine cosine operator during whale scratching, global exploration blind spots are reduced through sine optimizing and the convergence speed is accelerated through cosine exploitation. Meanwhile the chaos operator enhances the ability to jump out of local optimum. The individual information in the population is spread quickly by double sine cross. Through simulation and experiment, it is proven that the algorithm has better convergence speed, accuracy and stability.