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Article: Corona virus optimization (CVO): a novel optimization algorithm inspired from the Corona virus pandemic.

Salehan, Alireza / Deldari, Arash

The Journal of supercomputing

2021  Volume 78, Issue 4, Page(s) 5712–5743

Abstract: This research introduces a new probabilistic and meta-heuristic optimization approach inspired by the Corona virus pandemic. Corona is an infection that originates from an unknown animal virus, which is of three known types and COVID-19 has been rapidly ... ...

Abstract This research introduces a new probabilistic and meta-heuristic optimization approach inspired by the Corona virus pandemic. Corona is an infection that originates from an unknown animal virus, which is of three known types and COVID-19 has been rapidly spreading since late 2019. Based on the SIR model, the virus can easily transmit from one person to several, causing an epidemic over time. Considering the characteristics and behavior of this virus, the current paper presents an optimization algorithm called Corona virus optimization (CVO) which is feasible, effective, and applicable. A set of benchmark functions evaluates the performance of this algorithm for discrete and continuous problems by comparing the results with those of other well-known optimization algorithms. The CVO algorithm aims to find suitable solutions to application problems by solving several continuous mathematical functions as well as three continuous and discrete applications. Experimental results denote that the proposed optimization method has a credible, reasonable, and acceptable performance.
Language English
Publishing date 2021-10-04
Publishing country United States
Document type Journal Article
ZDB-ID 1479917-0
ISSN 1573-0484 ; 0920-8542
ISSN (online) 1573-0484
ISSN 0920-8542
DOI 10.1007/s11227-021-04100-z
Database MEDical Literature Analysis and Retrieval System OnLINE

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