| 自适应分组差分萤火虫算法求解连续空间优化问题 |
| |
| 引用本文： | 张强,李盼池.自适应分组差分萤火虫算法求解连续空间优化问题[J].控制与决策,2017,32(7):1217-1222. |
| |
| 作者姓名： | 张强 李盼池 |
| |
| 作者单位： | 东北石油大学计算机与信息技术学院,黑龙江大庆163318,东北石油大学计算机与信息技术学院,黑龙江大庆163318 |
| |
| 基金项目： | 国家自然科学基金项目(61170132, 61502094)；黑龙江省自然科学基金项目(F2015020)；黑龙江省教育厅项目(12541086). |
| |
| 摘 要： | 提出一种自适应分组差分萤火虫算法求解连续空间优化问题.利用自适应分组策略对种群进行分子群寻优,基于均匀设计理论调整算法参数,通过云模型算法来改进最优个体的随机扰动行为,引入个体能效吸引力来改进非最优个体更新方式.最后,利用差分变异算法和混沌理论完成个体变异.典型复杂函数测试表明,所提出的算法具有很好的收敛精度和计算速度.
|
| 关 键 词： | 萤火虫算法 云模型 均匀设计 混沌 连续空间优化 |
Adaptive grouping difference firefly algorithm for continuous space optimization problems |
| |
| ZHANG Qiang and LI Pan-chi.Adaptive grouping difference firefly algorithm for continuous space optimization problems[J].Control and Decision,2017,32(7):1217-1222. |
| |
| Authors: | ZHANG Qiang and LI Pan-chi |
| |
| Affiliation: | School of Computer and Information Technology,Northeast Petroleum University,Daqing 163318, China and School of Computer and Information Technology,Northeast Petroleum University,Daqing 163318, China |
| |
| Abstract: | An adaptive grouping difference firefly algorithm is proposed to solve the continuous space optimization problem. In the algorithm, the population is divided into subgroups for optimization based on adaptive grouping strategy and the parametors are adjusted based on the uniform design theory the stochastic perturbation behavior of optimal individuals is updated by using the cloud model algorithm. The updating method of the non-optimal individual is improved by introducing the individual energy efficiency attraction. Finally, the individual variation is completed by using the differential mutation algorithm and chaos theory. Simulation results of the typical complex functions show that the algorithm has good the convergence precision and computing speed. |
| |
| Keywords: | |
|
| 点击此处可从《控制与决策》浏览原始摘要信息 |
|
点击此处可从《控制与决策》下载全文 |
|
