|Table of Contents|

Particle Swarm Algorithm for Linear Constrained Optimization Problem(PDF)

南京师范大学学报（工程技术版）[ISSN:1006-6977/CN:61-1281/TN]

Issue:
2010年04期
Page:
26-30
Research Field:
Publishing date:

Info

Title:
Particle Swarm Algorithm for Linear Constrained Optimization Problem
Author(s):
Chen Zhanping1; 2
1.School of Computer Science and Technology,Nanjing Normal University,Nanjing 210046,China;2.Jiangsu Research Center of Information Security and Privacy Technology,Nanjing 210097,China
Keywords:
linea r constra int;  optim iza tion;  partic le sw arm a lgo rithm
PACS:
TP301.6
DOI:
-
Abstract:
The shortage in slow convergence rate and low conv ergence prec ision ex istw hen the particle swa rm a lgo rithm is d irectly used to so lve the constra ined optim ization problem. In th is paper, w e are concerned w ith an new particle swarm algorithm, w hich can be used to so lve the linear constra ined prob lem s. In our me thod, the constrained optim ization problem is first trans lated into a non- constra ined optim ization one by introducing the Lag rang emu ltip liers, and then by us ing the Lagrange dua lity princ ip le, the Lag range mu ltip liers and op tim ization param eters a re separated, which w ill be optim ized respective ly by using the particle swa rm a lgo rithm. M oreover, in order tom ake the pa rtic le sw arm a lgo rithm conv erge to the g loba l optim ization so lution, an improved particle swa rm a lgo rithm w ith muta tion is propo sed. Fina lly, a design exam ple of a low-pass FIR filter show s tha t ourm ethod is be tter than the particle sw arm algor ithm w ithout constra ints.

References:

[ 1] Bouche r C, Noyer J. A hybr id par tic le approach for GNSS applications w ith partia l GPS outages [ J]. IEEE Trans Instrum M eas, 2010, 59( 3): 498-505.
[ 2] 陈保娣, 曾建潮. 改进的吸引扩散微粒群算法[ J]. 控制理论与应用, 2010, 27( 4): 451-456. Chen Baod,i Zeng Jianchao. M od ified a ttractive and repu lsive particle sw arm op tim ization [ J]. Con tro l Theory and App lications, 2010, 27( 4): 451-456. ( in Chinese)
[ 3] Naka S, Gen jiT, YuraT, et a.l A hybrid partic le sw arm optim ization for distribution sta te estim ation[ J]. IEEE T rans on Powe r System s, 2003, 18( 1): 60-68.
[ 4] 王万雷, 杨静萍, 薄洪光. 基于微粒群和满足质量约束的组炉方案优化方法[ J] . 控制理论与应用, 2010, 27 ( 4): 509-512. W angW anle,i Y ang Jingp ing, BoH ongguang. Optim iza tion of charge design w ith quality constra ints based on pa rtic le sw arm optim iza tion[ J] . Contro l Theory and App lications, 2010, 27( 4): 509-512. ( in Ch inese)
[ 5] 朱海梅, 吴永萍. 一种高速收敛粒子群优化算法[ J]. 控制与决策, 2010, 25( 1): 20-24. Zhu H aim e ,i W u Yongp ing. A PSO algorithm w ith high speed conv ergence [ J]. Contro l and Dec is ion, 2010, 25( 1): 20-24. ( in Chinese)
[ 6] 胡适耕, 施保昌. 最优化原理[M ]. 武汉: 华中理工大学出版社, 2000: 134-138. H u Sh igeng, Sh i Baochang. Optim ization Theory [M ]. W uhan: H uazhong University of Techno logy Press, 2000: 134-138. ( in Chinese)
[ 7] ShiYuhu,i Eberhart R. A m odified particle sw arm op tim izer [ C] / / Proc IEEE Int Con f on Evo lu tionary Com puta tion. Anchorage, 1998: 69-73.
[ 8] 赖晓平. FIR滤波器约束M inM ax设计算法[ J]. 系统工程与电子技术, 2002, 24( 2): 84-88. La i X iaoping. Constra ined m in im ax design a lgo rithm fo r FIR filters[ J]. System s Eng ineer ing and E lectronics, 2002, 24( 2):84-88. ( in Chinese)

Memo

Memo:
-
Last Update: 2013-04-02