精英反向黄金正弦海洋捕食者算法  

An elite opposition-based golden sine marine predator algorithm

作　　者：张磊[1] 刘升[1] 高文欣 郭雨鑫 ZHANG Lei;LIU Sheng;GAO Wen-xin;GUO Yu-xin(School of Management,Shanghai University of Engineering Science,Shanghai 201620,China)

机构地区：[1]上海工程技术大学管理学院,上海201620

出　　处：《计算机工程与科学》2023年第2期355-362,共8页Computer Engineering & Science

基　　金：国家自然科学基金(61075115,61673258);上海市自然科学基金(19ZR1421600)。

摘　　要：由于基本的海洋捕食者算法在运行时存在求解准确度低和稳定性差等缺点,提出一种精英反向学习黄金正弦的海洋捕食者算法。加入精英反向学习机制,提升了海洋捕食者的种群质量,使得算法全面探索的范围得到了有效扩大;加入黄金正弦策略,改进了海洋捕食者捕食猎物的方法,缩小了海洋捕食者的搜索空间,使得算法的局部开发性能得到了有效提高。对12个基准测试函数和12个CEC2017函数进行求解测试,测试结果显示,2种改进策略有助于提高海洋捕食者算法的性能。Because the basic ocean predator algorithm has shortcomings such as low solution accuracy and poor stability at runtime,this paper proposes an elite reverse learning golden sine ocean predator algorithm.The elite reverse learning mechanism is added to improve the population quality of marine predators,and the comprehensive exploration scope of the algorithm is effectively expanded.The golden sine strategy is added to improve the way of hunting their prey of marine predators and reduce the search space of marine predators,and the performance of local development of the algorithm is effectively enhanced.The effectiveness of the improved strategy is evaluated by solving 12 benchmark functions and 12 CEC2017 functions.The solution test results show that the two strategies have an excellent effect on improving the performance of the ocean predator algorithm.

关 键 词：精英反向学习 黄金正弦 海洋捕食者算法 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]