Presentation 2022-11-18
Particle swarm optimization considering a positive and negative inertia terms by Levy distribution
Sohei Kusaka, Hidehiro Nakano,
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Abstract(in Japanese) (See Japanese page)
Abstract(in English) Particle Swarm Optimization (PSO) is known as a type of swarm intelligence algorithms. The inertia constant of each search particle in PSO is a parameter that affects the convergence speed and diversity of the search, and is generally a positive value. In this paper, we apply the Levy distribution to the behavior of each search particle and propose a method that incorporates behavior with a negative inertia constant. Numerical experiments with benchmark functions are conducted to confirm the basic search performance.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) Swarm Intelligence / Particle Swarm Optimization / Levy distribution
Paper # CCS2022-57
Date of Issue 2022-11-10 (CCS)

Conference Information
Committee CCS
Conference Date 2022/11/17(2days)
Place (in Japanese) (See Japanese page)
Place (in English)
Topics (in Japanese) (See Japanese page)
Topics (in English)
Chair Megumi Akai(Hokkaido Univ.)
Vice Chair Hidehiro Nakano(Tokyo City Univ.) / Masaki Aida(TMU)
Secretary Hidehiro Nakano(Shibaura Inst. of Tech.) / Masaki Aida(Mie Univ.)
Assistant Hiroyuki Yasuda(Univ. of Tokyo) / Hiroyasu Ando(Tsukuba Univ.) / Tomoyuki Sasaki(Shonan Inst. of Tech.) / Miki Kobayashi(Rissho Univ.)

Paper Information
Registration To Technical Committee on Complex Communication Sciences
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Particle swarm optimization considering a positive and negative inertia terms by Levy distribution
Sub Title (in English)
Keyword(1) Swarm Intelligence
Keyword(2) Particle Swarm Optimization
Keyword(3) Levy distribution
1st Author's Name Sohei Kusaka
1st Author's Affiliation Tokyo City University(Tokyo City Univ.)
2nd Author's Name Hidehiro Nakano
2nd Author's Affiliation Tokyo City University(Tokyo City Univ.)
Date 2022-11-18
Paper # CCS2022-57
Volume (vol) vol.122
Number (no) CCS-255
Page pp.pp.71-75(CCS),
#Pages 5
Date of Issue 2022-11-10 (CCS)