The Study of a New Complex System Evolutionary Algorithm for Global Optimal Problems

HAO Hai-qing; MA Hang; ZHUANG Jian

doi:10.3969/j.issn.0372-2112.2013.04.013

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The Study of a New Complex System Evolutionary Algorithm for Global Optimal Problems

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- The Study of a New Complex System Evolutionary Algorithm for Global Optimal Problems
- Acta Electronica Sinica Vol. 41, Issue 4, Pages: 704-709(2013)
- 作者机构：
  
  1. 华南理工大学机械与汽车工程学院,广东,广州,510006
  2. 广州大学土木工程学院,广东,广州,510006
  3. 南通大学附属第二医院呼吸内科,江苏,南通,226001
  4. 西安交通大学机械学院,陕西,西安,710049
  5. 华南理工大学机械与汽车工程学院广东广州,510006
  6. 广州大学土木工程学院广东广州,510006
  7. 南通大学附属第二医院呼吸内科江苏南通,226001
  8. 西安交通大学机械学院陕西西安,710049
- 作者简介：
- 基金信息：
  
  Strategic Emerging Industry Core Technology Research Project of Guangdong Province (No.2011A091101004);Industrial Technology Research and Development Program of Science and Technology Department of Shaanxi Province (No.2011K09-45);Fundamental Research Funds for the Central Universities(3072021CF0806)
- DOI：10.3969/j.issn.0372-2112.2013.04.013
  CLC： TP391.41
- Published：2013
- 稿件说明：
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HAO Hai-qing, MA Hang, ZHUANG Jian. The Study of a New Complex System Evolutionary Algorithm for Global Optimal Problems[J]. Acta Electronica Sinica, 2013, 41(4): 704-709.
DOI：

HAO Hai-qing, MA Hang, ZHUANG Jian. The Study of a New Complex System Evolutionary Algorithm for Global Optimal Problems[J]. Acta Electronica Sinica, 2013, 41(4): 704-709. DOI： 10.3969/j.issn.0372-2112.2013.04.013.

摘要

文章在复杂系统思想激励下设计了一种新型的基于复杂系统改进的进化算法

该算法改进了进化算法的交叉、选择、变异和进化策略

体现了进化过程中能量分布、空间搜索、信息利用的复杂性

并保持了进化算法的简单结构框架;进而通过计算实例分析了新型复杂系统进化算法两个主要参数对算法性能影响;最后

新算法测试了CEC'2012大规模全局优化竞赛中的函数集合

并与其他优秀算法的测试结果进行了对比

结果表明本文所提出的基于复杂系统改进的进化算法综合性能强于所有的对比算法.

Abstract

Inspired by some complex system concepts

a new evolutionary algorithm is designed in paper.In the new algorithm

crossover

selecting operator

mutating operator and evolutionary strategy are improved by some characteristic properties of complex system.These improvements represent the complexity of energy distribution

space searching and information use during the evolution.And the simple procedure structure of evolutionary algorithm is reserved.Then

the influences of two parameters are discussed in paper.Finally

all functions of CEC'2012 competition on large scale problems are tested by the new evolutionary algorithm.And testing results of the new evolutionary algorithm are compared with those of other excellent algorithms.The results show that comprehensive capabilities of the new evolutionary algorithm

presented in the paper

are better than all comparing algorithms.

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School of Applied Mathematics,University of Electronic Science and Technology of China

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