改进的樽海鞘群算法及在焊接梁问题中的应用  

An improved salp swarm algorithm and its application to welding beam problem

作　　者：王彦军 王秋萍[1] 王晓峰[1] WANG Yanjun;WANG Qiuping;WANG Xiaofeng(School of Sciences,Xi’an University of Technology,Xi’an 710054,China)

机构地区：[1]西安理工大学理学院

出　　处：《西安理工大学学报》2019年第4期484-493,共10页Journal of Xi'an University of Technology

基　　金：国家自然科学基金资助项目(61772416)

摘　　要：针对樽海鞘群算法的求解精度较低,收敛速度较慢等缺陷,提出一种改进的樽海鞘群算法。首先,对领导者个体执行精英反向学习策略以平衡算法的勘探和开发能力;然后,为提高算法的求解精度,受差分进化算法的启发,引入一种差分策略来更新追随者位置;最后,在搜索过程中对食物位置进行Gauss变异以避免陷入局部最优,为算法进行全局搜索奠定基础。在10个标准测试函数和一个经典工程问题上进行了实验,结果表明,改进的樽海鞘群算法的搜索性能明显优于其对比算法。An improved salp swarm algorithm is proposed to solve the problems of low accuracy and slow convergence.Firstly,elite opposition-based learning strategy is applied to leader individual to balance the exploration and exploitation ability of the algorithm.Then,in order to improve the accuracy of the algorithm,a difference strategy is introduced to update the follower position inspired by the difference evolution.Finally,Gaussian mutation of food location is carried out in the search process to avoid falling into local optima,laying a foundation for the global search for the algorithm.Experiment results on 10 standard test functions and a classical engineering problem show that the search performance of the improved salp swarm algorithm is better than that of the contrast algorithm.

关 键 词：樽海鞘群算法 精英反向学习 差分策略 Gauss变异 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]