M-elite coevolutionary kinetic-molecular theory optimization algorithm

Chao-dong FAN; Jing ZHANG; Ling-zhi YI

doi:10.11959/j.issn.1000-436x.2015200

您当前的位置：

首页 >

文章列表页 >

M-elite coevolutionary kinetic-molecular theory optimization algorithm

Academic paper | 更新时间：2024-06-05

- M-elite coevolutionary kinetic-molecular theory optimization algorithm
- Journal on Communications Vol. 36, Issue 7, Pages: 144-152(2015)
- 作者机构：
  
  湘潭大学信息工程学院，湖南湘潭 411105
- 作者简介：
- 基金信息：
  
  The National Natural Science Foundation of China(61440026);Scientific Research Project of Hunan Provincial Education Department(15C1327)
- DOI：10.11959/j.issn.1000-436x.2015200
  CLC： TP18
- Online First：2015-07，
  
  Published：25 July 2015
- 稿件说明：
移动端阅览
Chao-dong FAN, Jing ZHANG, Ling-zhi YI. M-elite coevolutionary kinetic-molecular theory optimization algorithm[J]. Journal on Communications, 2015, 36(7): 144-152.
DOI：

Chao-dong FAN, Jing ZHANG, Ling-zhi YI. M-elite coevolutionary kinetic-molecular theory optimization algorithm[J]. Journal on Communications, 2015, 36(7): 144-152. DOI： 10.11959/j.issn.1000-436x.2015200.

摘要

提出了一种M-精英协同进化分子动理论优化算法(MECKMTOA

M-elite coevolutionary KMTOA)。该算法基于M个精英以尽量防止算法陷入按维早熟。测试结果表明，MECKMTOA在求解精度、算法稳定性、高维函数求解等方面均表现出避免发生错误引导，通过精英间的学习与协作提高算法的收敛精度，采用新型的波动算子良好性能。

Abstract

M-elite coevolutionary kinetic-molecular theory optimization algorithm (MECKMTOA) was proposed.MECKMTOA uses M elites to avoid misleading

improves the convergence precision by learning and collaboration among the elites

employs a new wave operator to prevent premature by dimension.The results show that MECKMTOA has good performance in precision and stability

and can solve the high-dimensional function optimization problems well.

关键词

Keywords

references

LIN C H,CHOY K L , HO G T S , NG T W . A genetic algorithm-based optimization model for supporting green transportation operations [J ] . Expert Systems with Applications , 2014 , 41 ( 7 ): 3284 - 3296 .

DONG W Y , ZHOU M C . Gaussian classifier-based evolutionary strategy for multimodal optimization [J ] . IEEE Transactions on Neural Networks ＆ Learning Systems , 2014 , 25 ( 6 ): 1200 - 1216 .

KHATOD D K , PANT V , SHARMA J . Evolutionary programming based optimal placement of renewable distributed generators [J ] . IEEE Transactions on Power Systems , 2013 , 28 ( 2 ): 683 - 695 .

MIRJALILI S , LEWIS A , SADIQ A S . Autonomous particles groups for particle swarm optimization [J ] . Arabian Journal for Science and Engineering , 2014 , 39 ( 6 ): 4683 - 4697 .

ZHENG L . An improved monkey algorithm with dynamic adaptation [J ] . Applied Mathematics and Computation , 2013 , 222 ( 1 ): 645 - 657 .

张冬丽 , 唐英干 , 关新平 . 用改进的人工蜂群算法设计AVR系统最优分数阶PID控制器 [J ] . 自动化学报 , 2014 , 40 ( 5 ): 973 - 979 .

ZHANG D L , TANG Y G , GUAN X P . Optimum design of fractional order pid controller for an avr system using an improved artificial bee colony algorithm [J ] . Acta Automatica Sinica , 2014 , 40 ( 5 ): 973 - 979 .

ZHANG C J , LI X Y , GAO L WU Q . An improved electromagnetism-like mechanism algorithm for constrained optimization [J ] . Expert Systems with Applications , 2013 , 40 ( 14 ): 5621 - 5634 .

FORMATO R A . Central force optimization with variable initial probes and adaptive decision space [J ] . Applied Mathematics and Computation , 2011 , 2 ( 17 ): 8866 - 8872 .

MIRJALILI S , LEWIS A . Adaptive gbest-guided gravitational search algorithm [J ] . Neural Computing and Applications , 2014 , 25 ( 7 ): 1569 - 1584 .

FAN C D , OUYANG H L , ZHANG Y J , et al . Optimization algorithm based on kinetic-molecular theory [J ] . Journal of Central South University , 2013 , 20 ( 12 ): 3504 - 3512 .

范朝冬 , 张英杰 , 欧阳红林等 . 基于改进斜分Otsu法的回转窑火焰图像分割 [J ] . 自动化学报 , 2014 , 40 ( 11 ): 2480 - 2489 .

FAN C D , ZHANG Y J , OUYANG H L , et al . Improved Otsu method based on histogram oblique segmentation for segmentation of rotary kiln flame image [J ] . Acta Automatica Sinica , 2014 , 40 ( 11 ): 2480 - 2489 .

JIAO L C , WANG H D , SHANG R H , et al . A co-evolutionary multi-objective optimization algorithm based on direction vectors [J ] . Information Sciences , 2013 , 228 ( 10 ): 90 - 112 .

LI H C , FANG L . Co-evolutionary algorithm:an efficient approach for bilevel programming problems [J ] . Engineering Optimization , 2014 , 46 ( 3 ): 361 - 376 .

CHEN P H . Two-level hierarchical approach to unit commitment using expert system and elite PSO [J ] . IEEE Transactions on Power Systems , 2012 , 27 ( 2 ): 780 - 789 .

YOUSEFIKHOSHBAKHT M , DIDEHVAR F , RAHMATI F . An efficient solution for the vrp by using a hybrid elite ant system [J ] . International Journal of Computers Communications ＆ Control , 2014 , 9 ( 3 ): 340 - 347 .

慕彩红 , 焦李成 , 刘逸 . M-精英协同进化数值优化算法 [J ] . 软件学报 , 2009 , 20 ( 11 ): 2925 - 2938 .

MU C H , JIAO L C , LIU Y . M-elite coevolutionary algorithm for numerical optimization [J ] . Journal of Software , 2009 , 20 ( 11 ): 2925 - 2938 .

慕彩红 , 焦李成 , 刘逸 . M-精英协同进化算法及其在 V-BLAST 系统中的应用 [J ] . 电子与信息学报 , 2009 , 31 ( 10 ): 2443 - 2448 .

MU C H , JIAO L C , LIU Y . M-elitist evolutionary algorithm and its application to v-blast system [J ] . Journal of Electronics ＆ Information Technology , 2009 , 31 ( 10 ): 2443 - 2448 .

秦进 , 李歆 . 一种简单的资源受限的群体演化模型 [J ] . 复杂系统与复杂性科学 , 2009 , 6 ( 2 ): 82 - 86 .

QIN J , LI X . A simple model of population evolution with limited resource [J ] . Complex Systems and Complexity Science , 2009 , 6 ( 2 ): 82 - 86 .

范朝冬 , 欧阳红林 , 肖乐意 . 基于空间截面投影的Otsu图像分割算法 . 通信学报 , 2014 , 35 ( 5 ): 70 - 78 .

FAN C D , OUYANG H L , XIAO L Y . Otsu thresholding method based on projection of cross section for image segmentation [J ] . Journal on Communications , 2014 , 35 ( 5 ): 70 - 78 .

杜海峰 , 公茂果 , 焦李成等 . 用于高维函数优化的免疫记忆克隆规划算法 [J ] . 自然科学进展 , 2004 , 14 ( 8 ): 925 - 933 .

DU H F , GONG M G , LIAO L C , et al . Immune memory clonal programming algorithm for high dimension function optimization [J ] . Progress in Natural Science , 2004 , 14 ( 8 ): 925 - 93 .

Views

1722

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

MQHOA algorithm with energy level stabilizing process

Lossless sharing visual cryptography

New chaos-particle swarm optimization algorithm

Related Author

Peng WANG

Yan HUANG

Bin YU

Zheng-xin FU

Xiao-bo XU

Kang-feng ZHENG

Dan LI

Bin WU

Related Institution

School of Computer Science and Technology,Southwest University for Nationalities

School of Computer Science and Technology,Huaiyin Normal University,Huaian

Institute of Electronic Technology, Information Engineering University

Information Security Center,Beijing University of Posts and Telecommunications

National Engineering Laboratory for Disaster Backup and Recovery,Beijing University of Posts and Telecommunications

AI问答

⁰