Porcellio scaber algorithm (PSA) for solving constrained optimization problems

Yinyan Zhang; Shuai Li; Hongliang Guo

doi:10.1051/matecconf/201713900033

Porcellio scaber algorithm (PSA) for solving constrained optimization problems

Yinyan Zhang, Shuai Li, Hongliang Guo

Research output: Journal article publication › Conference article › Academic research › peer-review

2 Citations (Scopus)

Abstract

In this paper, we extend a bio-inspired algorithm called the porcellio scaber algorithm (PSA) to solve constrained optimization problems, including a constrained mixed discrete-continuous nonlinear optimization problem. Our extensive experiment results based on benchmark optimization problems show that the PSA has a better performance than many existing methods or algorithms. The results indicate that the PSA is a promising algorithm for constrained optimization.

Original language	English
Article number	00033
Journal	MATEC Web of Conferences
Volume	139
DOIs	https://doi.org/10.1051/matecconf/201713900033
Publication status	Published - 5 Dec 2017
Event	3rd International Conference on Mechanical, Electronic and Information Technology Engineering, ICMITE 2017 - Chengdu, China Duration: 16 Dec 2017 → 17 Dec 2017

ASJC Scopus subject areas

General Chemistry
General Materials Science
General Engineering

More information

10.1051/matecconf/201713900033

http://hdl.handle.net/10397/77236

Cite this

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title = "Porcellio scaber algorithm (PSA) for solving constrained optimization problems",

abstract = "In this paper, we extend a bio-inspired algorithm called the porcellio scaber algorithm (PSA) to solve constrained optimization problems, including a constrained mixed discrete-continuous nonlinear optimization problem. Our extensive experiment results based on benchmark optimization problems show that the PSA has a better performance than many existing methods or algorithms. The results indicate that the PSA is a promising algorithm for constrained optimization.",

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AU - Zhang, Yinyan

AU - Li, Shuai

AU - Guo, Hongliang

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Y1 - 2017/12/5

N2 - In this paper, we extend a bio-inspired algorithm called the porcellio scaber algorithm (PSA) to solve constrained optimization problems, including a constrained mixed discrete-continuous nonlinear optimization problem. Our extensive experiment results based on benchmark optimization problems show that the PSA has a better performance than many existing methods or algorithms. The results indicate that the PSA is a promising algorithm for constrained optimization.

AB - In this paper, we extend a bio-inspired algorithm called the porcellio scaber algorithm (PSA) to solve constrained optimization problems, including a constrained mixed discrete-continuous nonlinear optimization problem. Our extensive experiment results based on benchmark optimization problems show that the PSA has a better performance than many existing methods or algorithms. The results indicate that the PSA is a promising algorithm for constrained optimization.

UR - https://www.scopus.com/pages/publications/85039460177

U2 - 10.1051/matecconf/201713900033

DO - 10.1051/matecconf/201713900033

M3 - Conference article

AN - SCOPUS:85039460177

SN - 2261-236X

VL - 139

JO - MATEC Web of Conferences

JF - MATEC Web of Conferences

M1 - 00033

T2 - 3rd International Conference on Mechanical, Electronic and Information Technology Engineering, ICMITE 2017

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ER -

Porcellio scaber algorithm (PSA) for solving constrained optimization problems

Abstract

ASJC Scopus subject areas

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