摘要
研究了一种新的群体智能优化算法——鲸鱼群算法(whale swarm algorithm,WSA).系统介绍了鲸鱼群算法的原理、基本步骤及与其他典型群体智能优化算法相比的特点,并针对多峰优化问题的特点改进了WSA的迭代规则,引入稳定性阈值和适应度阈值两个参数,提出带迭代计数器的WSA(WSA with iterative counter,WSA-IC).实验证明,WSA-IC在最优解数量、最优解质量和收敛速度方面均有着优秀的表现,将WSA-IC应用于炼钢连铸调度问题,通过实验验证WSA-IC具有良好的寻优能力和稳定性,并提出从理论研究和实际应用两方面深化鲸鱼群算法的研究.
A new swam intelligent optimization algorithm named whale swarm algorithm (WSA)was studied. The principle and essential procedures of WSA were introduced;and the characteristics of WSA were presented through comparison with other classical swam intelligent optimization algorithms.For multimodal optimization,the iteration rule of WSA was improved,two parameters namely stability threshold and fitness threshold were introduced,and thus WSA with iterative counter (WSA-IC)was developed.The experimental results demonstrated that WSA-IC showed good performance in terms of the number and quality of optimal solutions and convergence speed.Then WSA-IC was applied to the steelmaking continuous casting scheduling problem, and proved to have good optimization ability and strong stability through the experiments.Finally,with the above research results,it was summarized that WSA had much value in practice,and further research of WSA could be carried out in theoretical study and practical application.
作者
曾冰
王梦雨
高亮
董昊臻
ZENG Bing;WANG Mengyu;GAO Liang;DONG Haozhen(School of Mechanical Science and Engineering,Huazhong University of Science and Technology,Wuhan 430074,China)
出处
《郑州大学学报（工学版）》
CAS
北大核心
2018年第6期14-22,35,共10页
Journal of Zhengzhou University（Engineering Science）
基金
国家自然科学基金资助项目(51575212)
华中科技大学学术前沿青年团队项目
关键词
群体智能优化算法
鲸鱼群算法
多峰优化
炼钢连铸调度
swam intelligent optimization algorithm
whale swarm algorithm
multimodal optimization
steelmaking continuous casting scheduling
