Inertial geometric particle swarm optimization

Alberto Moraglio; Julian Togelius

doi:10.1109/CEC.2009.4983182

Inertial geometric particle swarm optimization

Alberto Moraglio, Julian Togelius

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Geometric particle swarm optimization (GPSO) is a recently introduced formal generalization of a simplified form of traditional particle swarm optimization (PSO) without the inertia term that applies naturally to both continuous and combinatorial spaces. In this paper, we propose an extension of GPSO, the inertial GPSO (IGPSO), that generalizes the traditional PSO endowed with the full equation of motion of particles to generic search spaces. We then formally derive the specific IGPSO for the Hamming space associated with binary strings and present experimental results for this new algorithm.

Original language	English (US)
Title of host publication	2009 IEEE Congress on Evolutionary Computation, CEC 2009
Pages	1973-1980
Number of pages	8
DOIs	https://doi.org/10.1109/CEC.2009.4983182
State	Published - 2009
Event	2009 IEEE Congress on Evolutionary Computation, CEC 2009 - Trondheim, Norway Duration: May 18 2009 → May 21 2009

Publication series

Name	2009 IEEE Congress on Evolutionary Computation, CEC 2009

Other

Other	2009 IEEE Congress on Evolutionary Computation, CEC 2009
Country/Territory	Norway
City	Trondheim
Period	5/18/09 → 5/21/09

ASJC Scopus subject areas

Artificial Intelligence
Computational Theory and Mathematics
Theoretical Computer Science

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10.1109/CEC.2009.4983182

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abstract = "Geometric particle swarm optimization (GPSO) is a recently introduced formal generalization of a simplified form of traditional particle swarm optimization (PSO) without the inertia term that applies naturally to both continuous and combinatorial spaces. In this paper, we propose an extension of GPSO, the inertial GPSO (IGPSO), that generalizes the traditional PSO endowed with the full equation of motion of particles to generic search spaces. We then formally derive the specific IGPSO for the Hamming space associated with binary strings and present experimental results for this new algorithm.",

author = "Alberto Moraglio and Julian Togelius",

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doi = "10.1109/CEC.2009.4983182",

language = "English (US)",

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AB - Geometric particle swarm optimization (GPSO) is a recently introduced formal generalization of a simplified form of traditional particle swarm optimization (PSO) without the inertia term that applies naturally to both continuous and combinatorial spaces. In this paper, we propose an extension of GPSO, the inertial GPSO (IGPSO), that generalizes the traditional PSO endowed with the full equation of motion of particles to generic search spaces. We then formally derive the specific IGPSO for the Hamming space associated with binary strings and present experimental results for this new algorithm.

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BT - 2009 IEEE Congress on Evolutionary Computation, CEC 2009

T2 - 2009 IEEE Congress on Evolutionary Computation, CEC 2009

Y2 - 18 May 2009 through 21 May 2009

ER -

Inertial geometric particle swarm optimization

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