A novel multi-level quantization scheme for discrete particle swarm optimization

Hwachang Song; Ryan B. Diolata; Young Hoon Joo

doi:10.1109/FUZZY.2009.5277306

A novel multi-level quantization scheme for discrete particle swarm optimization

Hwachang Song
, Ryan B. Diolata
, Young Hoon Joo

Dept. of Electrical and Information Engineering

Kunsan National University

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

1 Scopus citations

Abstract

This paper presents a novel multi-level quantization scheme which best approximates the sigmoid function for multi-value discrete variable transformation in PSO. We define the set of multi-level quantization as integer multiples of powers-of-two terms to efficiently approximate the sigmoid function in transforming particle's position into multilevel discrete values. In this paper, the feasibility of the proposed technique was tested in photovoltaic (PV) system allocation problem, and a comparison study with genetic algorithm (GA) is performed to show the quality of the solutions obtained.

Original language	English
Title of host publication	2009 IEEE International Conference on Fuzzy Systems - Proceedings
Pages	1834-1838
Number of pages	5
DOIs	https://doi.org/10.1109/FUZZY.2009.5277306
State	Published - 2009
Event	2009 IEEE International Conference on Fuzzy Systems - Jeju Island, Korea, Republic of Duration: 20 Aug 2009 → 24 Aug 2009

Publication series

Name	IEEE International Conference on Fuzzy Systems
ISSN (Print)	1098-7584

Conference

Conference	2009 IEEE International Conference on Fuzzy Systems
Country/Territory	Korea, Republic of
City	Jeju Island
Period	20/08/09 → 24/08/09

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

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10.1109/FUZZY.2009.5277306

Cite this

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title = "A novel multi-level quantization scheme for discrete particle swarm optimization",

abstract = "This paper presents a novel multi-level quantization scheme which best approximates the sigmoid function for multi-value discrete variable transformation in PSO. We define the set of multi-level quantization as integer multiples of powers-of-two terms to efficiently approximate the sigmoid function in transforming particle's position into multilevel discrete values. In this paper, the feasibility of the proposed technique was tested in photovoltaic (PV) system allocation problem, and a comparison study with genetic algorithm (GA) is performed to show the quality of the solutions obtained.",

author = "Hwachang Song and Diolata, \{Ryan B.\} and Joo, \{Young Hoon\}",

year = "2009",

doi = "10.1109/FUZZY.2009.5277306",

language = "English",

isbn = "9781424435975",

series = "IEEE International Conference on Fuzzy Systems",

pages = "1834--1838",

booktitle = "2009 IEEE International Conference on Fuzzy Systems - Proceedings",

note = "2009 IEEE International Conference on Fuzzy Systems ; Conference date: 20-08-2009 Through 24-08-2009",

}

Song, H, Diolata, RB & Joo, YH 2009, A novel multi-level quantization scheme for discrete particle swarm optimization. in 2009 IEEE International Conference on Fuzzy Systems - Proceedings., 5277306, IEEE International Conference on Fuzzy Systems, pp. 1834-1838, 2009 IEEE International Conference on Fuzzy Systems, Jeju Island, Korea, Republic of, 20/08/09. https://doi.org/10.1109/FUZZY.2009.5277306

A novel multi-level quantization scheme for discrete particle swarm optimization. / Song, Hwachang; Diolata, Ryan B.; Joo, Young Hoon.
2009 IEEE International Conference on Fuzzy Systems - Proceedings. 2009. p. 1834-1838 5277306 (IEEE International Conference on Fuzzy Systems).

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

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AB - This paper presents a novel multi-level quantization scheme which best approximates the sigmoid function for multi-value discrete variable transformation in PSO. We define the set of multi-level quantization as integer multiples of powers-of-two terms to efficiently approximate the sigmoid function in transforming particle's position into multilevel discrete values. In this paper, the feasibility of the proposed technique was tested in photovoltaic (PV) system allocation problem, and a comparison study with genetic algorithm (GA) is performed to show the quality of the solutions obtained.

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A novel multi-level quantization scheme for discrete particle swarm optimization

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