Comparison and analysis of particle swarm optimization method based on genetic operator

Computer Engineering and Applications ›› 2008, Vol. 44 ›› Issue (14): 65-66.

• 理论研究 • Previous Articles Next Articles

Comparison and analysis of particle swarm optimization method based on genetic operator

LEI Xiu-juan^1,2,SHI Zhong-ke²,SUN Gui-qi¹

1.College of Computer Science，Shaanxi Normal University，Xi’an 710062,China
2.College of Automation，Northwestern Polytechnical University，Xi’an 710072，China

Received:2007-08-31 Revised:2007-11-12 Online:2008-05-11 Published:2008-05-11
Contact: LEI Xiu-juan

基于遗传算子的粒子群优化算法的比较分析

雷秀娟^1,2,史忠科²,孙瑰琪¹

1.陕西师范大学计算机科学学院，西安 710062
2.西北工业大学自动化学院，西安 710072

通讯作者: 雷秀娟

Abstract

Abstract: To analyse the performance of improved particle swarm optimization method deeply，three strategies are designed to experiment several standard test functions optimization problem.One of the strategies is linear inertia weight reduction,the second is the PSO with genetic operator,and the third is rejoining the constriction factor based on the second strategy.Through the optimization and simulation of the test functions in MATLAB 7.0 software，the performance of the PSO mixed the genetic operator and constriction factor is best of all.

Key words: Particle Swarm Optimization(PSO), Linearly Decreasing Weight(LDW), genetic operator, constriction factor

摘要： 为了深入分析探讨改进的粒子群优化算法的性能，针对典型的函数优化问题，设计了3种方案：(1)采用线性递减惯性权重的PSO；(2)基于遗传算子的PSO；(3)在方案(2)基础上，加入收缩因子χ。在MATLAB 7.0中对常用的测试函数进行优化仿真，发现当融合遗传算子和收缩因子时，算法性能最优。

关键词: 粒子群优化, 线性递减惯性权重, 遗传算子, 收缩因子

LEI Xiu-juan^1,2,SHI Zhong-ke²,SUN Gui-qi¹. Comparison and analysis of particle swarm optimization method based on genetic operator[J]. Computer Engineering and Applications, 2008, 44(14): 65-66.

雷秀娟^1,2,史忠科²,孙瑰琪¹. 基于遗传算子的粒子群优化算法的比较分析[J]. 计算机工程与应用, 2008, 44(14): 65-66.

[1]	HU Xiaomin, WANG Mingfeng, ZHANG Shourong, LI Min. New Differential Evolution with Particle Swarm Optimization Algorithm for Text Clustering [J]. Computer Engineering and Applications, 2021, 57(4): 61-67.
[2]	WANG Jiayue, SHI Li. Research on Path Optimization and Charging Strategy of Electric Refrigerated Vehicle Considering Cost of Battery Capacity Degradation [J]. Computer Engineering and Applications, 2021, 57(24): 283-289.
[3]	LIN Weixing, WANG Yujia, CHEN Wanfen, LIANG Haina. High-Dimensional Data Feature Selection Algorithm Based on Multifactor Particle Swarm Optimization [J]. Computer Engineering and Applications, 2021, 57(22): 199-207.
[4]	LIAO Weilin, CHENG Shan, SHANG Dongdong, WEI Zhaobin. Particle Swarm Optimization Algorithm Integrated with Multiple-Strategies [J]. Computer Engineering and Applications, 2021, 57(1): 69-76.
[5]	ZHOU Rong, LI Jun, WANG Hao. Reverse Learning Particle Swarm Optimization Based on Grey Wolf Optimization [J]. Computer Engineering and Applications, 2020, 56(7): 48-56.
[6]	CHEN Qiuju, XU Jianguo. Optimized Orthogonal Matching Pursuit and Short-Time Spectrum Estimation for Sound Recognition [J]. Computer Engineering and Applications, 2020, 56(7): 162-169.
[7]	YANG Yanrong, SONG Rongjie, ZHOU Zhaoyong. Network Intrusion Detection Method Based on GAN-PSO-ELM [J]. Computer Engineering and Applications, 2020, 56(12): 66-72.
[8]	JIANG Li1，2, YE Runzhou1，2, LIANG Changyong1，2, LU Wenxing1，2. Improved Second-Order Oscillatory Particle Swarm Optimization [J]. Computer Engineering and Applications, 2019, 55(9): 130-138.
[9]	FENG Jianxin1，2, LI Hui1，2, LIU Zhiguo1，2. New Flame Color Space—IFCS [J]. Computer Engineering and Applications, 2019, 55(5): 203-210.
[10]	YUAN Luo1，2, GE Hongwei1，2. Dispersion Particle Swarm Optimization Algorithm Based on Random Whip Mechanism [J]. Computer Engineering and Applications, 2019, 55(4): 66-71.
[11]	YAN Xuelong, CHEN Zhuo. Analog Circuit Fault Prognostic Utilizing Particle Swarm Optimized Multi-Kernel Relevance Vector Machine [J]. Computer Engineering and Applications, 2019, 55(12): 140-144.
[12]	HONG Tianlong, XIE Lijun, HE Lisha, NI Zhongyi, ZHENG Yao. Auto Tunning for In-Situ Volume Depth Image Generation Based on Particle Swarm Optimization Algorithm [J]. Computer Engineering and Applications, 2019, 55(11): 237-243.
[13]	KANG Kai, PU Wei, HAN Jie, MA Yanfang. Inventory-allocation planning problem with defective item disposal under fuzzy random environment [J]. Computer Engineering and Applications, 2018, 54(24): 241-251.
[14]	HU Min, WANG Tengfei, HUANG Hongcheng. Software-defined wireless sensor networks routing algorithm based on extremum disturbed particle swarm optimization [J]. Computer Engineering and Applications, 2018, 54(22): 113-118.
[15]	SHI Jianli1, ZHANG Jin2. Particle swarm optimization for split delivery vehicle routing problem with stochastic demands [J]. Computer Engineering and Applications, 2018, 54(21): 230-239.

Comparison and analysis of particle swarm optimization method based on genetic operator

基于遗传算子的粒子群优化算法的比较分析

PDF

Knowledge

Abstract

Cite this article

share this article

References

Related Articles 15

Recommended Articles

Metrics