A new adaptive inertia weight strategy in particle swarm optimization

被引：20

作者：

Feng, C. S. ^{[1
]}

Cong, S. ^{[1
]}

Feng, X. Y. ^{[1
]}

机构：

[1] Univ Sci & Technol China, Dept Automat, Hefei 230027, Peoples R China

来源：

2007 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION, VOLS 1-10, PROCEEDINGS | 2007年

关键词：

particle swarm optimization (PSO); principle of mechanics; inertia weight strategy; convergence speed; global search;

D O I：

10.1109/CEC.2007.4425017

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

According to the principle of mechanics, a new adaptive inertia weight strategy is proposed. The strategy depends on particle's search states including its location and velocity instead of iteration times. Based on the proposed strategy, an inertia weight function is designed, which is continuous in real domain, thus it's easy to be implemented and the computation cost is low. Experiments on three benchmark functions, comparison between convergence speed, the ability to search the global solution of the linear decreasing strategy (LPOS) and the proposed strategy are done. The experimental results are also analyzed in detail.

引用

页码：4186 / 4190

页数：5

共 9 条

[1]

[Anonymous], EV COMP P 1998 IEEE

[2]

ARACHCHI F, 2005, ICIP 2005 IEEE INT C, V2, P329

[3] Nonlinear inertia weight variation for dynamic adaptation in particle swarm optimization [J].

Chatterjee, A ;

Siarry, P .

COMPUTERS & OPERATIONS RESEARCH, 2006, 33 (03) :859-871

[4]

Chen GM, 2006, WCICA 2006: SIXTH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION, VOLS 1-12, CONFERENCE PROCEEDINGS, P3672

[5] A particle swarm optimization approach for optimum design of PID controller in AVR system [J].

Gaing, ZL .

IEEE TRANSACTIONS ON ENERGY CONVERSION, 2004, 19 (02) :384-391

[6]

Kennedy J, 1995, 1995 IEEE INTERNATIONAL CONFERENCE ON NEURAL NETWORKS PROCEEDINGS, VOLS 1-6, P1942, DOI 10.1109/icnn.1995.488968

[7]

Shi Y., 1999, Proceedings of the 1999 Congress on Evolutionary Computation-CEC99 (Cat. No. 99TH8406), P1945, DOI 10.1109/CEC.1999.785511

[8]

Shi YH, 2001, IEEE C EVOL COMPUTAT, P101, DOI 10.1109/CEC.2001.934377

[9]

ZHANG C, 2000, 2000 IEEE INT C MAN, V4, P2487

← 1 →