具有角色转换的自适应人工蜂群算法
发布时间：2019-07-05 12:28
【摘要】：提出一种具有引领蜂与跟随蜂动态协调机制的改进人工蜂群算法(DHABC)。根据优化函数的寻优状态,设计了引领蜂与跟随蜂动态角色转换机制,以更好地适应全局和局部搜索;为使算法能够更好地进行局部兼顾更大范围搜索,设计了引领蜂与跟随蜂间位置信息的共享方式;为提高算法的求解速度,设计了跟随蜂进化代数起始值的计算方法;通过仿真和比较实验,改进算法较其他ABC改进算法及其他智能优化算法既参数少,便于应用,又求解精度较高。
[Abstract]:An improved artificial bee swarm algorithm (DHABC). With dynamic coordination mechanism between lead bee and follower bee is proposed. According to the optimization state of the optimization function, the dynamic role transformation mechanism between the lead bee and the follower bee is designed to better adapt to the global and local search, in order to make the algorithm better take into account the local search, the sharing method of the position information between the lead bee and the following bee is designed, in order to improve the solving speed of the algorithm, the calculation method of the starting value of the following bee evolution algebra is designed. Through simulation and comparison experiments, the improved algorithm not only has fewer parameters, is convenient to be applied, but also has higher accuracy than other improved ABC algorithms and other intelligent optimization algorithms.
【作者单位】： 河北工业大学经济管理学院;天津职业技术师范大学电子工程学院;
【基金】：河北省高等学校自然科学青年基金项目(No.2011125) 天津职业技术师范大学科研项目(No.KJ15-25)
【分类号】：TP18
[Abstract]:An improved artificial bee swarm algorithm (DHABC). With dynamic coordination mechanism between lead bee and follower bee is proposed. According to the optimization state of the optimization function, the dynamic role transformation mechanism between the lead bee and the follower bee is designed to better adapt to the global and local search, in order to make the algorithm better take into account the local search, the sharing method of the position information between the lead bee and the following bee is designed, in order to improve the solving speed of the algorithm, the calculation method of the starting value of the following bee evolution algebra is designed. Through simulation and comparison experiments, the improved algorithm not only has fewer parameters, is convenient to be applied, but also has higher accuracy than other improved ABC algorithms and other intelligent optimization algorithms.
【作者单位】： 河北工业大学经济管理学院;天津职业技术师范大学电子工程学院;
【基金】：河北省高等学校自然科学青年基金项目(No.2011125) 天津职业技术师范大学科研项目(No.KJ15-25)
【分类号】：TP18
【相似文献】
相关期刊论文 前5条
1 杨世达;易亚林;单志勇;李庆华;;蜜蜂进化型的类电磁机制算法[J];计算机工程与应用;2013年06期
2 梁新华;潘泉;杨峰;王增福;;基于两级采样的粒子滤波检测前跟踪算法[J];系统工程与电子技术;2011年09期
3 张玉t，
本文编号：2510524
本文链接：https://www.wllwen.com/kejilunwen/zidonghuakongzhilunwen/2510524.html
