Abstract: Aiming at the disadvantages of whale optimization algorithm,such as low convergence accuracy and easy to fall into local optimization,an integrating multi-strategy Improved Whale Optimization Algorithm(IWOA)was proposed.The theory of good point set was introduced to increase the diversity of the initial population.Then,the mutation dimension by dimension optimization strategy was adopted for the optimal individual to enhance the local development ability of the algorithm.Finally,the chaotic interference was carried out on inferior individuals to enhance the global search ability of the algorithm.IWOA and five other swarm intelligence optimization algorithms were used to simulate the test function and applied to optimize the load distribution of parallel chillers.The experimental results showed that IWOA had good optimization performance.

Key words: whale optimization algorithm, multi-strategy, good point set, chaotic interference, load distribution

摘要： 针对鲸鱼优化算法存在的收敛精度低和易陷入局部最优的缺陷,提出一种融合多策略改进鲸鱼优化算法(IWOA)。首先在生成初始种群时引入佳点集理论以增加初始种群多样性;然后通过对最优个体采用变异逐维优化策略以增强算法的局部开发能力;最后对劣等个体进行混沌干扰,增强算法的全局搜索能力。将IWOA与5种其他群体智能优化算法对测试函数进行仿真实验,并将其应用到优化冷水机组负荷分配问题中,实验结果表明IWOA具有良好的寻优性能。

关键词: 鲸鱼优化算法, 多策略, 佳点集, 混沌干扰, 负荷分配