Inertia weight adaption in particle swarm optimization algorithm

Zheng Zhou; Yuhui Shi

doi:10.1007/978-3-642-21515-5_9

Inertia weight adaption in particle swarm optimization algorithm

Zheng Zhou^*
, Yuhui Shi

^*Corresponding author for this work

Xi'an Jiaotong-Liverpool University

Research output: Chapter in Book or Report/Conference proceeding › Conference Proceeding › peer-review

21 Citations (Scopus)

Abstract

In Particle Swarm Optimization (PSO), setting the inertia weight w is one of the most important topics. The inertia weight was introduced into PSO to balance between itsglobal and local search abilities. In this paper, first, wepropose a method to adaptively adjust the inertia weight based on particle's velocity information. Second, we utilize both position and velocity information to adaptively adjust the inertia weight. The proposed methodsare then tested on benchmark functions. The simulation results illustrate the effectiveness and efficiency of the proposed algorithm by comparing it with other existingPSOs.

Original language	English
Title of host publication	Advances in Swarm Intelligence - Second International Conference, ICSI 2011, Proceedings
Pages	71-79
Number of pages	9
Edition	PART 1
DOIs	https://doi.org/10.1007/978-3-642-21515-5_9
Publication status	Published - 2011
Event	2nd International Conference on Swarm Intelligence, ICSI 2011 - Chongqing, China Duration: 12 Jun 2011 → 15 Jun 2011

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Number	PART 1
Volume	6728 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	2nd International Conference on Swarm Intelligence, ICSI 2011
Country/Territory	China
City	Chongqing
Period	12/06/11 → 15/06/11

Keywords

PSO
adaption
inertia weight
velocity information

Access to Document

10.1007/978-3-642-21515-5_9

Cite this

Zhou, Z., & Shi, Y. (2011). Inertia weight adaption in particle swarm optimization algorithm. In Advances in Swarm Intelligence - Second International Conference, ICSI 2011, Proceedings (PART 1 ed., pp. 71-79). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6728 LNCS, No. PART 1). https://doi.org/10.1007/978-3-642-21515-5_9

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title = "Inertia weight adaption in particle swarm optimization algorithm",

abstract = "In Particle Swarm Optimization (PSO), setting the inertia weight w is one of the most important topics. The inertia weight was introduced into PSO to balance between itsglobal and local search abilities. In this paper, first, wepropose a method to adaptively adjust the inertia weight based on particle's velocity information. Second, we utilize both position and velocity information to adaptively adjust the inertia weight. The proposed methodsare then tested on benchmark functions. The simulation results illustrate the effectiveness and efficiency of the proposed algorithm by comparing it with other existingPSOs.",

keywords = "PSO, adaption, inertia weight, velocity information",

author = "Zheng Zhou and Yuhui Shi",

note = "Funding Information: This work is supported by National Natural Science Foundation of China under Grant No.60975080, and Suzhou Science and Technology Project under Grant No. SYJG0919.; 2nd International Conference on Swarm Intelligence, ICSI 2011 ; Conference date: 12-06-2011 Through 15-06-2011",

year = "2011",

doi = "10.1007/978-3-642-21515-5\_9",

language = "English",

isbn = "9783642215148",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

number = "PART 1",

pages = "71--79",

booktitle = "Advances in Swarm Intelligence - Second International Conference, ICSI 2011, Proceedings",

edition = "PART 1",

}

Zhou, Z & Shi, Y 2011, Inertia weight adaption in particle swarm optimization algorithm. in Advances in Swarm Intelligence - Second International Conference, ICSI 2011, Proceedings. PART 1 edn, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 1, vol. 6728 LNCS, pp. 71-79, 2nd International Conference on Swarm Intelligence, ICSI 2011, Chongqing, China, 12/06/11. https://doi.org/10.1007/978-3-642-21515-5_9

Inertia weight adaption in particle swarm optimization algorithm. / Zhou, Zheng; Shi, Yuhui.
Advances in Swarm Intelligence - Second International Conference, ICSI 2011, Proceedings. PART 1. ed. 2011. p. 71-79 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6728 LNCS, No. PART 1).

Research output: Chapter in Book or Report/Conference proceeding › Conference Proceeding › peer-review

TY - GEN

T1 - Inertia weight adaption in particle swarm optimization algorithm

AU - Zhou, Zheng

AU - Shi, Yuhui

N1 - Funding Information: This work is supported by National Natural Science Foundation of China under Grant No.60975080, and Suzhou Science and Technology Project under Grant No. SYJG0919.

PY - 2011

Y1 - 2011

N2 - In Particle Swarm Optimization (PSO), setting the inertia weight w is one of the most important topics. The inertia weight was introduced into PSO to balance between itsglobal and local search abilities. In this paper, first, wepropose a method to adaptively adjust the inertia weight based on particle's velocity information. Second, we utilize both position and velocity information to adaptively adjust the inertia weight. The proposed methodsare then tested on benchmark functions. The simulation results illustrate the effectiveness and efficiency of the proposed algorithm by comparing it with other existingPSOs.

AB - In Particle Swarm Optimization (PSO), setting the inertia weight w is one of the most important topics. The inertia weight was introduced into PSO to balance between itsglobal and local search abilities. In this paper, first, wepropose a method to adaptively adjust the inertia weight based on particle's velocity information. Second, we utilize both position and velocity information to adaptively adjust the inertia weight. The proposed methodsare then tested on benchmark functions. The simulation results illustrate the effectiveness and efficiency of the proposed algorithm by comparing it with other existingPSOs.

KW - PSO

KW - adaption

KW - inertia weight

KW - velocity information

UR - https://www.scopus.com/pages/publications/79958195183

U2 - 10.1007/978-3-642-21515-5_9

DO - 10.1007/978-3-642-21515-5_9

M3 - Conference Proceeding

AN - SCOPUS:79958195183

SN - 9783642215148

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 71

EP - 79

BT - Advances in Swarm Intelligence - Second International Conference, ICSI 2011, Proceedings

T2 - 2nd International Conference on Swarm Intelligence, ICSI 2011

Y2 - 12 June 2011 through 15 June 2011

ER -

Zhou Z, Shi Y. Inertia weight adaption in particle swarm optimization algorithm. In Advances in Swarm Intelligence - Second International Conference, ICSI 2011, Proceedings. PART 1 ed. 2011. p. 71-79. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 1). doi: 10.1007/978-3-642-21515-5_9

Inertia weight adaption in particle swarm optimization algorithm

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